scholarly journals Identification of flux trade-offs in metabolic networks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Seirana Hashemi ◽  
Zahra Razaghi-Moghadam ◽  
Zoran Nikoloski
Keyword(s):  
Metabolic Network ◽  
Large Scale ◽  
Metabolic Networks ◽  
Carbon Sources ◽  
Biochemical Networks ◽  
Cellular Functions ◽  
Tight Coupling ◽  
Prosthetic Group ◽  
Absolute Flux ◽  
Trade Offs

AbstractTrade-offs are inherent to biochemical networks governing diverse cellular functions, from gene expression to metabolism. Yet, trade-offs between fluxes of biochemical reactions in a metabolic network have not been formally studied. Here, we introduce the concept of absolute flux trade-offs and devise a constraint-based approach, termed FluTO, to identify and enumerate flux trade-offs in a given genome-scale metabolic network. By employing the metabolic networks of Escherichia coli and Saccharomyces cerevisiae, we demonstrate that the flux trade-offs are specific to carbon sources provided but that reactions involved in the cofactor and prosthetic group biosynthesis are present in trade-offs across all carbon sources supporting growth. We also show that absolute flux trade-offs depend on the biomass reaction used to model the growth of Arabidopsis thaliana under different carbon and nitrogen conditions. The identified flux trade-offs reflect the tight coupling between nitrogen, carbon, and sulphur metabolisms in leaves of C3 plants. Altogether, FluTO provides the means to explore the space of alternative metabolic routes reflecting the constraints imposed by inherent flux trade-offs in large-scale metabolic networks.

scholarly journals The unraveling of balanced complexes in metabolic networks

2021 ◽  
Author(s):  
Damoun Langary ◽  
Anika Kueken ◽  
Zoran Nikoloski
Keyword(s):  
Steady State ◽  
Large Scale ◽  
Metabolic Networks ◽  
Network Models ◽  
Steady States ◽  
Biochemical Networks ◽  
Computational Approaches ◽  
Metabolic Models ◽  
Large Scale Networks ◽  
General Conditions

Balanced complexes in biochemical networks are at core of several theoretical and computational approaches that make statements about the properties of the steady states supported by the network. Recent computational approaches have employed balanced complexes to reduce metabolic networks, while ensuring preservation of particular steady-state properties; however, the underlying factors leading to the formation of balanced complexes have not been studied, yet. Here, we present a number of factorizations providing insights in mechanisms that lead to the origins of the corresponding balanced complexes. The proposed factorizations enable us to categorize balanced complexes into four distinct classes, each with specific origins and characteristics. They also provide the means to efficiently determine if a balanced complex in large-scale networks belongs to a particular class from the categorization. The results are obtained under very general conditions and irrespective of the network kinetics, rendering them broadly applicable across variety of network models. Application of the categorization shows that all classes of balanced complexes are present in large-scale metabolic models across all kingdoms of life, therefore paving the way to study their relevance with respect to different properties of steady states supported by these networks.

Graph methods for the investigation of metabolic networks in parasitology

Parasitology ◽  
2010 ◽  
Vol 137 (9) ◽  
pp. 1393-1407 ◽  
Author(s):  
LUDOVIC COTTRET ◽  
FABIEN JOURDAN
Keyword(s):  
Metabolic Network ◽  
Large Scale ◽  
Metabolic Networks ◽  
Graph Model ◽  
New Drugs ◽  
Mathematical Methods ◽  
Graph Models ◽  
Metabolic Network Reconstruction ◽  
Network Analyses ◽  
Genome Scale

SUMMARYRecently, a way was opened with the development of many mathematical methods to model and analyze genome-scale metabolic networks. Among them, methods based on graph models enable to us quickly perform large-scale analyses on large metabolic networks. However, it could be difficult for parasitologists to select the graph model and methods adapted to their biological questions. In this review, after briefly addressing the problem of the metabolic network reconstruction, we propose an overview of the graph-based approaches used in whole metabolic network analyses. Applications highlight the usefulness of this kind of approach in the field of parasitology, especially by suggesting metabolic targets for new drugs. Their development still represents a major challenge to fight against the numerous diseases caused by parasites.

REVISITING MODULES (AND CENTERS) IN STAPHYLOCOCCUS AUREUS METABOLIC NETWORK WITH LINK CLUSTERING

2012 ◽  
Vol 20 (01) ◽  
pp. 57-66
Author(s):  
DE-WU DING ◽  
LONG YING
Keyword(s):  
Staphylococcus Aureus ◽  
Community Structure ◽  
Metabolic Network ◽  
Structure Analysis ◽  
Large Scale ◽  
Metabolic Networks ◽  
Clustering Algorithm ◽  
Functional Modules ◽  
Analysis Methods

Community structure analysis methods are important tools in modeling and analyzing large-scale metabolic networks. However, traditional community structure methods are mainly solved by clustering nodes, which results in each metabolite belonging to only a single community, which limits their usefulness in the study of metabolic networks. In the present paper, we analyze the community structure and functional modules in the Staphylococcus aureus (S. aureus) metabolic network, using a link clustering algorithm, and we obtain 10 functional modules with better biological insights, which give better results than our previous study. We also evaluate the essentiality of nodes in S. aureus metabolic networks. We suggest that link clustering could identify functional modules and key metabolites in metabolic networks.

scholarly journals Effective Dynamic Models of Metabolic Networks

2016 ◽  
Author(s):  
Michael Vilkhovoy ◽  
Mason Minot ◽  
Jeffrey D. Varner
Keyword(s):  
Metabolic Network ◽  
Metabolic Networks ◽  
Dynamic Models ◽  
Biochemical Networks ◽  
Promising Alternative ◽  
E Coli ◽  
Flux Balance ◽  
Comparable Performance ◽  
Elementary Modes ◽  
Balance Analysis

AbstractMathematical models of biochemical networks are useful tools to understand and ultimately predict how cells utilize nutrients to produce valuable products. Hybrid cybernetic models in combination with elementary modes (HCM) is a tool to model cellular metabolism. However, HCM is limited to reduced metabolic networks because of the computational burden of calculating elementary modes. In this study, we developed the hybrid cybernetic modeling with flux balance analysis or HCM-FBA technique which uses flux balance solutions instead of elementary modes to dynamically model metabolism. We show HCM-FBA has comparable performance to HCM for a proof of concept metabolic network and for a reduced anaerobicE. colinetwork. Next, HCM-FBA was applied to a larger metabolic network of aerobicE. colimetabolism which was infeasible for HCM (29 FBA modes versus more than 153,000 elementary modes). Global sensitivity analysis further reduced the number of FBA modes required to describe the aerobicE. colidata, while maintaining model fit. Thus, HCM-FBA is a promising alternative to HCM for large networks where the generation of elementary modes is infeasible.

scholarly journals Von der Stöchiometrie zur Kontrolle metabolischer Netzwerke

BIOspektrum ◽  
2021 ◽  
Vol 27 (1) ◽  
pp. 34-36
Author(s):  
Thorben Schramm ◽  
Hannes Link
Keyword(s):  
Metabolic Network ◽  
Metabolic Networks ◽  
Cellular Metabolism ◽  
Bacterial Metabolism ◽  
Cellular Functions ◽  
Biochemical Reactions ◽  
Complete Set

AbstractCellular metabolism is very complex and extensively regulated. For many organisms we know almost the complete set of biochemical reactions in their metabolic network. However, it is not well understood how these reactions are regulated and how they interact in order to enable cellular functions. In this review, we describe recent methodological advances to study metabolic networks with a focus on bacterial metabolism.

Evaluation of the growth and sporulation of different entomopathogenic fungi in different liquid and solid media at varied concentrations

2017 ◽  
Vol 6 (8) ◽  
pp. 5459
Author(s):  
Chandra Teja K. ◽  
Rahman S. J.
Keyword(s):  
Entomopathogenic Fungi ◽  
Large Scale ◽  
Insect Pests ◽  
Culture Media ◽  
Virulent Strain ◽  
Carbon Sources ◽  
Nitrogen Sources ◽  
Maximum Growth ◽  
Nutritional Requirements ◽  
Virulent Strains

Entomopathogenic fungi like Beauveria bassiana, Metarhizium anisopliae and Lecanicillium lecanii are used in biological control of agricultural insect pests. Their specific mode of action makes them an effective alternative to the chemical Insecticides. Virulent strains of Entomopathogenic fungi are effectively formulated and used as bio-insecticides world-wide. Amenable and economical multiplication of a virulent strain in a large scale is important for them to be useful in the field. Culture media plays a major role in the large-scale multiplication of virulent strains of Entomopathogens. Different substrates and media components are being used for this purpose. Yet, each strain differs in its nutritional requirements for the maximum growth and hence it is necessary to standardize the right components and their optimum concentrations in the culture media for a given strain of Entomopathogen. In the current study, three different nitrogen sources and two different carbon sources were tried to standardize the mass multiplication media for seven test isolates of Entomopathogenic fungi. A study was also conducted to determine the ideal grain media for the optimum conidial yields of the test isolates. Yeast extract was found to be the best Nitrogen source for the isolates. The isolates tested, differed in their nutritional requirements and showed variation in the best nitrogen and carbon sources necessary for their growth. Variation was also found in the optimum concentration of both the ingredients for the growth and sporulation of the isolates. In the solid-state fermentation study, rice was found to be the best grain for the growth of most of the fungi followed by barley. The significance of such a study in the development of an effective Myco-insecticide is vital and can be successfully employed in agriculture is discussed.

scholarly journals Large-Scale Analysis of the Spatiotemporal Changes of Net Ecosystem Production in Hindu Kush Himalayan Region

2021 ◽  
Vol 13 (6) ◽  
pp. 1180
Author(s):  
Da Guo ◽  
Xiaoning Song ◽  
Ronghai Hu ◽  
Xinming Zhu ◽  
Yazhen Jiang ◽  
...  
Keyword(s):  
Large Scale ◽  
Net Primary Production ◽  
Carbon Sink ◽  
Carbon Sources ◽  
Spatial Dynamics ◽  
Tibet Plateau ◽  
Geostatistical Model ◽  
Hindu Kush ◽  
Temporal And Spatial ◽  
The Difference

The Hindu Kush Himalayan (HKH) region is one of the most ecologically vulnerable regions in the world. Several studies have been conducted on the dynamic changes of grassland in the HKH region, but few have considered grassland net ecosystem productivity (NEP). In this study, we quantitatively analyzed the temporal and spatial changes of NEP magnitude and the influence of climate factors on the HKH region from 2001 to 2018. The NEP magnitude was obtained by calculating the difference between the net primary production (NPP) estimated by the Carnegie–Ames Stanford Approach (CASA) model and the heterotrophic respiration (Rh) estimated by the geostatistical model. The results showed that the grassland ecosystem in the HKH region exhibited weak net carbon uptake with NEP values of 42.03 gC∙m−2∙yr−1, and the total net carbon sequestration was 0.077 Pg C. The distribution of NEP gradually increased from west to east, and in the Qinghai–Tibet Plateau, it gradually increased from northwest to southeast. The grassland carbon sources and sinks differed at different altitudes. The grassland was a carbon sink at 3000–5000 m, while grasslands below 3000 m and above 5000 m were carbon sources. Grassland NEP exhibited the strongest correlation with precipitation, and it had a lagging effect on precipitation. The correlation between NEP and the precipitation of the previous year was stronger than that of the current year. NEP was negatively correlated with temperature but not with solar radiation. The study of the temporal and spatial dynamics of NEP in the HKH region can provide a theoretical basis to help herders balance grazing and forage.

scholarly journals On the Root Causes of the Fukushima Daiichi Disaster from the Perspective of High Complexity and Tight Coupling in Large-Scale Systems

Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 414
Author(s):  
Atsuo Murata ◽  
Waldemar Karwowski
Keyword(s):  
Nuclear Power ◽  
Power Plants ◽  
Large Scale ◽  
High Complexity ◽  
Tight Coupling ◽  
Large Scale Systems ◽  
Safety Issues ◽  
Loss Of Coolant ◽  
Station Blackout ◽  
Fukushima Daiichi

This study explores the root causes of the Fukushima Daiichi disaster and discusses how the complexity and tight coupling in large-scale systems should be reduced under emergencies such as station blackout (SBO) to prevent future disasters. First, on the basis of a summary of the published literature on the Fukushima Daiichi disaster, we found that the direct causes (i.e., malfunctions and problems) included overlooking the loss of coolant and the nuclear reactor’s failure to cool down. Second, we verified that two characteristics proposed in “normal accident” theory—high complexity and tight coupling—underlay each of the direct causes. These two characteristics were found to have made emergency management more challenging. We discuss how such disasters in large-scale systems with high complexity and tight coupling could be prevented through an organizational and managerial approach that can remove asymmetry of authority and information and foster a climate of openly discussing critical safety issues in nuclear power plants.

scholarly journals Mapping the adaptive landscape of a major agricultural pathogen reveals evolutionary constraints across heterogeneous environments

2021 ◽  
Author(s):  
Anik Dutta ◽  
Fanny E. Hartmann ◽  
Carolina Sardinha Francisco ◽  
Bruce A. McDonald ◽  
Daniel Croll
Keyword(s):  
Life History ◽  
Large Scale ◽  
Life History Traits ◽  
Genetic Correlations ◽  
Stress Factors ◽  
Life History Trait ◽  
Adaptive Landscape ◽  
Heterogeneous Environments ◽  
Growth Responses ◽  
Trade Offs

AbstractThe adaptive potential of pathogens in novel or heterogeneous environments underpins the risk of disease epidemics. Antagonistic pleiotropy or differential resource allocation among life-history traits can constrain pathogen adaptation. However, we lack understanding of how the genetic architecture of individual traits can generate trade-offs. Here, we report a large-scale study based on 145 global strains of the fungal wheat pathogen Zymoseptoria tritici from four continents. We measured 50 life-history traits, including virulence and reproduction on 12 different wheat hosts and growth responses to several abiotic stressors. To elucidate the genetic basis of adaptation, we used genome-wide association mapping coupled with genetic correlation analyses. We show that most traits are governed by polygenic architectures and are highly heritable suggesting that adaptation proceeds mainly through allele frequency shifts at many loci. We identified negative genetic correlations among traits related to host colonization and survival in stressful environments. Such genetic constraints indicate that pleiotropic effects could limit the pathogen’s ability to cause host damage. In contrast, adaptation to abiotic stress factors was likely facilitated by synergistic pleiotropy. Our study illustrates how comprehensive mapping of life-history trait architectures across diverse environments allows to predict evolutionary trajectories of pathogens confronted with environmental perturbations.

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