scholarly journals Using a Genome-Scale Metabolic Model of Enterococcus faecalis V583 To Assess Amino Acid Uptake and Its Impact on Central Metabolism

2014 ◽  
Vol 81 (5) ◽  
pp. 1622-1633 ◽  
Author(s):  
Nadine Veith ◽  
Margrete Solheim ◽  
Koen W. A. van Grinsven ◽  
Brett G. Olivier ◽  
Jennifer Levering ◽  
...  
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Metabolic Network ◽  
Drug Targets ◽  
Metabolic Model ◽  
Content Type ◽  
A Genome ◽  
Genome Scale ◽  
Novel Drug ◽  
Novel Drug Targets

ABSTRACTIncreasing antibiotic resistance in pathogenic bacteria necessitates the development of new medication strategies. Interfering with the metabolic network of the pathogen can provide novel drug targets but simultaneously requires a deeper and more detailed organism-specific understanding of the metabolism, which is often surprisingly sparse. In light of this, we reconstructed a genome-scale metabolic model of the pathogenEnterococcus faecalisV583. The manually curated metabolic network comprises 642 metabolites and 706 reactions. We experimentally determined metabolic profiles ofE. faecalisgrown in chemically defined medium in an anaerobic chemostat setup at different dilution rates and calculated the net uptake and product fluxes to constrain the model. We computed growth-associated energy and maintenance parameters and studied flux distributions through the metabolic network. Amino acid auxotrophies were identified experimentally for model validation and revealed seven essential amino acids. In addition, the important metabolic hub of glutamine/glutamate was altered by constructing a glutamine synthetase knockout mutant. The metabolic profile showed a slight shift in the fermentation pattern toward ethanol production and increased uptake rates of multiple amino acids, especiallyl-glutamine andl-glutamate. The model was used to understand the altered flux distributions in the mutant and provided an explanation for the experimentally observed redirection of the metabolic flux. We further highlighted the importance of gene-regulatory effects on the redirection of the metabolic fluxes upon perturbation. The genome-scale metabolic model presented here includes gene-protein-reaction associations, allowing a further use for biotechnological applications, for studying essential genes, proteins, or reactions, and the search for novel drug targets.

scholarly journals Modeling the metabolic interplay between a parasitic worm and its bacterial endosymbiont allows the identification of novel drug targets

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
David M Curran ◽  
Alexandra Grote ◽  
Nirvana Nursimulu ◽  
Adam Geber ◽  
Dennis Voronin ◽  
...  
Keyword(s):  
Drug Targets ◽  
Metabolic Networks ◽  
Metabolic Model ◽  
Endosymbiotic Bacteria ◽  
Parasitic Worm ◽  
Eukaryotic Organisms ◽  
New Treatments ◽  
Genome Scale ◽  
Novel Drug ◽  
Novel Drug Targets

The filarial nematode Brugia malayi represents a leading cause of disability in the developing world, causing lymphatic filariasis in nearly 40 million people. Currently available drugs are not well-suited to mass drug administration efforts, so new treatments are urgently required. One potential vulnerability is the endosymbiotic bacteria Wolbachia—present in many filariae—which is vital to the worm. Genome scale metabolic networks have been used to study prokaryotes and protists and have proven valuable in identifying therapeutic targets, but have only been applied to multicellular eukaryotic organisms more recently. Here, we present iDC625, the first compartmentalized metabolic model of a parasitic worm. We used this model to show how metabolic pathway usage allows the worm to adapt to different environments, and predict a set of 102 reactions essential to the survival of B. malayi. We validated three of those reactions with drug tests and demonstrated novel antifilarial properties for all three compounds.

scholarly journals Modeling the metabolic interplay between a parasitic worm and its bacterial endosymbiont allows the identification of novel drug targets

2019 ◽  
Author(s):  
DM Curran ◽  
A Grote ◽  
N Nursimulu ◽  
A Geber ◽  
D Voronin ◽  
...  
Keyword(s):  
Drug Targets ◽  
Metabolic Networks ◽  
Metabolic Model ◽  
Endosymbiotic Bacteria ◽  
Parasitic Worm ◽  
Eukaryotic Organisms ◽  
New Treatments ◽  
Genome Scale ◽  
Novel Drug ◽  
Novel Drug Targets

AbstractThe filarial nematodeBrugia malayirepresents a leading cause of disability in the developing world, causing lymphatic filariasis in nearly 40 million people. Currently available drugs are not well-suited to mass drug administration efforts, so new treatments are urgently required. One potential vulnerability is the endosymbiotic bacteriaWolbachia—present in many filariae—which is vital to the worm.Genome scale metabolic networks have been used to study prokaryotes and protists and have proven valuable in identifying therapeutic targets, but only recently have been applied to eukaryotic organisms. Here, we presentiDC625, the first compartmentalized metabolic model of a parasitic worm. We used this model to show how metabolic pathway usage allows the worm to adapt to different environments, and predict a set of 99 reactions essential to the survival ofB. malayi. We validated three of those reactions with drug tests and demonstrated novel antifilarial properties for all three compounds.

scholarly journals Evaluation of a Genome-ScaleIn SilicoMetabolic Model for Geobacter metallireducens by Using Proteomic Data from a Field Biostimulation Experiment

2012 ◽  
Vol 78 (24) ◽  
pp. 8735-8742 ◽  
Author(s):  
Yilin Fang ◽  
Michael J. Wilkins ◽  
Steven B. Yabusaki ◽  
Mary S. Lipton ◽  
Philip E. Long
Keyword(s):  
Proteomic Analysis ◽  
In Silico ◽  
Field Experiments ◽  
Metabolic Model ◽  
Geobacter Metallireducens ◽  
Content Type ◽  
Proteomic Data ◽  
Subsurface Environment ◽  
A Genome ◽  
Genome Scale

ABSTRACTAccurately predicting the interactions between microbial metabolism and the physical subsurface environment is necessary to enhance subsurface energy development, soil and groundwater cleanup, and carbon management. This study was an initial attempt to confirm the metabolic functional roles within anin silicomodel using environmental proteomic data collected during field experiments. Shotgun global proteomics data collected during a subsurface biostimulation experiment were used to validate a genome-scale metabolic model ofGeobacter metallireducens—specifically, the ability of the metabolic model to predict metal reduction, biomass yield, and growth rate under dynamic field conditions. The constraint-basedin silicomodelof G. metallireducensrelates an annotated genome sequence to the physiological functions with 697 reactions controlled by 747 enzyme-coding genes. Proteomic analysis showed that 180 of the 637G. metallireducensproteins detected during the 2008 experiment were associated with specific metabolic reactions in thein silicomodel. When the field-calibrated Fe(III) terminal electron acceptor process reaction in a reactive transport model for the field experiments was replaced with the genome-scale model, the model predicted that the largest metabolic fluxes through thein silicomodel reactions generally correspond to the highest abundances of proteins that catalyze those reactions. Central metabolism predicted by the model agrees well with protein abundance profiles inferred from proteomic analysis. Model discrepancies with the proteomic data, such as the relatively low abundances of proteins associated with amino acid transport and metabolism, revealed pathways or flux constraints in thein silicomodel that could be updated to more accurately predict metabolic processes that occur in the subsurface environment.

scholarly journals Identification of potential drug targets in Salmonella enterica sv. Typhimurium using metabolic modelling and experimental validation

Microbiology ◽  
2014 ◽  
Vol 160 (6) ◽  
pp. 1252-1266 ◽  
Author(s):  
Hassan B. Hartman ◽  
David A. Fell ◽  
Sergio Rossell ◽  
Peter Ruhdal Jensen ◽  
Martin J. Woodward ◽  
...  
Keyword(s):  
Salmonella Enterica ◽  
Energy Demand ◽  
Drug Targets ◽  
Minimal Medium ◽  
Model Organism ◽  
Metabolic Model ◽  
Scale Model ◽  
Glucose Minimal Medium ◽  
A Genome ◽  
Genome Scale

Salmonella enterica sv. Typhimurium is an established model organism for Gram-negative, intracellular pathogens. Owing to the rapid spread of resistance to antibiotics among this group of pathogens, new approaches to identify suitable target proteins are required. Based on the genome sequence of S. Typhimurium and associated databases, a genome-scale metabolic model was constructed. Output was based on an experimental determination of the biomass of Salmonella when growing in glucose minimal medium. Linear programming was used to simulate variations in the energy demand while growing in glucose minimal medium. By grouping reactions with similar flux responses, a subnetwork of 34 reactions responding to this variation was identified (the catabolic core). This network was used to identify sets of one and two reactions that when removed from the genome-scale model interfered with energy and biomass generation. Eleven such sets were found to be essential for the production of biomass precursors. Experimental investigation of seven of these showed that knockouts of the associated genes resulted in attenuated growth for four pairs of reactions, whilst three single reactions were shown to be essential for growth.

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 Exploring Hydrogenotrophic Methanogenesis: a Genome Scale Metabolic Reconstruction of Methanococcus maripaludis

2016 ◽  
Vol 198 (24) ◽  
pp. 3379-3390 ◽  
Author(s):  
Matthew A. Richards ◽  
Thomas J. Lie ◽  
Juan Zhang ◽  
Stephen W. Ragsdale ◽  
John A. Leigh ◽  
...  
Keyword(s):  
Energy Conservation ◽  
Metabolic Network ◽  
Hot Springs ◽  
Gene Knockout ◽  
Metabolic Reconstruction ◽  
Methanococcus Maripaludis ◽  
Content Type ◽  
Hydrogenotrophic Methanogenesis ◽  
A Genome ◽  
Genome Scale

ABSTRACTHydrogenotrophic methanogenesis occurs in multiple environments, ranging from the intestinal tracts of animals to anaerobic sediments and hot springs. Energy conservation in hydrogenotrophic methanogens was long a mystery; only within the last decade was it reported that net energy conservation for growth depends on electron bifurcation. In this work, we focus onMethanococcus maripaludis, a well-studied hydrogenotrophic marine methanogen. To better understand hydrogenotrophic methanogenesis and compare it with methylotrophic methanogenesis that utilizes oxidative phosphorylation rather than electron bifurcation, we have built iMR539, a genome scale metabolic reconstruction that accounts for 539 of the 1,722 protein-coding genes ofM. maripaludisstrain S2. Our reconstructed metabolic network uses recent literature to not only represent the central electron bifurcation reaction but also incorporate vital biosynthesis and assimilation pathways, including unique cofactor and coenzyme syntheses. We show that our model accurately predicts experimental growth and gene knockout data, with 93% accuracy and a Matthews correlation coefficient of 0.78. Furthermore, we use our metabolic network reconstruction to probe the implications of electron bifurcation by showing its essentiality, as well as investigating the infeasibility of aceticlastic methanogenesis in the network. Additionally, we demonstrate a method of applying thermodynamic constraints to a metabolic model to quickly estimate overall free-energy changes between what comes in and out of the cell. Finally, we describe a novel reconstruction-specific computational toolbox we created to improve usability. Together, our results provide a computational network for exploring hydrogenotrophic methanogenesis and confirm the importance of electron bifurcation in this process.IMPORTANCEUnderstanding and applying hydrogenotrophic methanogenesis is a promising avenue for developing new bioenergy technologies around methane gas. Although a significant portion of biological methane is generated through this environmentally ubiquitous pathway, existing methanogen models portray the more traditional energy conservation mechanisms that are found in other methanogens. We have constructed a genome scale metabolic network ofMethanococcus maripaludisthat explicitly accounts for all major reactions involved in hydrogenotrophic methanogenesis. Our reconstruction demonstrates the importance of electron bifurcation in central metabolism, providing both a window into hydrogenotrophic methanogenesis and a hypothesis-generating platform to fuel metabolic engineering efforts.

scholarly journals The Rhoptry Pseudokinase ROP54 Modulates Toxoplasma gondii Virulence and Host GBP2 Loading

mSphere ◽  
2016 ◽  
Vol 1 (2) ◽  
Author(s):  
Elliot W. Kim ◽  
Santhosh M. Nadipuram ◽  
Ashley L. Tetlow ◽  
William D. Barshop ◽  
Philip T. Liu ◽  
...  
Keyword(s):  
Immune Response ◽  
Drug Targets ◽  
Parasitophorous Vacuole ◽  
Effector Proteins ◽  
Host Cells ◽  
Content Type ◽  
Immune Factor ◽  
Novel Drug ◽  
Novel Drug Targets ◽  
Distinct Role

ABSTRACT The interactions between intracellular microbes and their host cells can lead to the discovery of novel drug targets. During Toxoplasma infections, host cells express an array of immunity-related GTPases (IRGs) and guanylate binding proteins (GBPs) that load onto the parasite-containing vacuole to clear the parasite. To counter this mechanism, the parasite secretes effector proteins that traffic to the vacuole to disarm the immunity-related loading proteins and evade the immune response. While the interplay between host IRGs and Toxoplasma effector proteins is well understood, little is known about how Toxoplasma neutralizes the GBP response. We describe here a T. gondii pseudokinase effector, ROP54, that localizes to the vacuole upon invasion and is critical for parasite virulence. Toxoplasma vacuoles lacking ROP54 display an increased loading of the host immune factor GBP2, but not IRGb6, indicating that ROP54 plays a distinct role in immune evasion. Toxoplasma gondii uses unique secretory organelles called rhoptries to inject an array of effector proteins into the host cytoplasm that hijack host cell functions. We have discovered a novel rhoptry pseudokinase effector, ROP54, which is injected into the host cell upon invasion and traffics to the cytoplasmic face of the parasitophorous vacuole membrane (PVM). Disruption of ROP54 in a type II strain of T. gondii does not affect growth in vitro but results in a 100-fold decrease in virulence in vivo, suggesting that ROP54 modulates some aspect of the host immune response. We show that parasites lacking ROP54 are more susceptible to macrophage-dependent clearance, further suggesting that ROP54 is involved in evasion of innate immunity. To determine how ROP54 modulates parasite virulence, we examined the loading of two known innate immune effectors, immunity-related GTPase b6 (IRGb6) and guanylate binding protein 2 (GBP2), in wild-type and ∆rop54II mutant parasites. While no difference in IRGb6 loading was seen, we observed a substantial increase in GBP2 loading on the parasitophorous vacuole (PV) of ROP54-disrupted parasites. These results demonstrate that ROP54 is a novel rhoptry effector protein that promotes Toxoplasma infections by modulating GBP2 loading onto parasite-containing vacuoles. IMPORTANCE The interactions between intracellular microbes and their host cells can lead to the discovery of novel drug targets. During Toxoplasma infections, host cells express an array of immunity-related GTPases (IRGs) and guanylate binding proteins (GBPs) that load onto the parasite-containing vacuole to clear the parasite. To counter this mechanism, the parasite secretes effector proteins that traffic to the vacuole to disarm the immunity-related loading proteins and evade the immune response. While the interplay between host IRGs and Toxoplasma effector proteins is well understood, little is known about how Toxoplasma neutralizes the GBP response. We describe here a T. gondii pseudokinase effector, ROP54, that localizes to the vacuole upon invasion and is critical for parasite virulence. Toxoplasma vacuoles lacking ROP54 display an increased loading of the host immune factor GBP2, but not IRGb6, indicating that ROP54 plays a distinct role in immune evasion.

scholarly journals Genome-Scale Model of Streptococcus thermophilus LMG18311 for Metabolic Comparison of Lactic Acid Bacteria

2009 ◽  
Vol 75 (11) ◽  
pp. 3627-3633 ◽  
Author(s):  
Margreet I. Pastink ◽  
Bas Teusink ◽  
Pascal Hols ◽  
Sanne Visser ◽  
Willem M. de Vos ◽  
...  
Keyword(s):  
Lactic Acid ◽  
Amino Acid ◽  
Lactic Acid Bacteria ◽  
Streptococcus Thermophilus ◽  
Metabolic Model ◽  
Pentose Phosphate ◽  
Scale Model ◽  
A Genome ◽  
Broad Variety ◽  
Genome Scale

ABSTRACT In this report, we describe the amino acid metabolism and amino acid dependency of the dairy bacterium Streptococcus thermophilus LMG18311 and compare them with those of two other characterized lactic acid bacteria, Lactococcus lactis and Lactobacillus plantarum. Through the construction of a genome-scale metabolic model of S. thermophilus, the metabolic differences between the three bacteria were visualized by direct projection on a metabolic map. The comparative analysis revealed the minimal amino acid auxotrophy (only histidine and methionine or cysteine) of S. thermophilus LMG18311 and the broad variety of volatiles produced from amino acids compared to the other two bacteria. It also revealed the limited number of pyruvate branches, forcing this strain to use the homofermentative metabolism for growth optimization. In addition, some industrially relevant features could be identified in S. thermophilus, such as the unique pathway for acetaldehyde (yogurt flavor) production and the absence of a complete pentose phosphate pathway.

scholarly journals Nature lessons: the whitefly bacterial endosymbiont is a minimal amino acid factory with unusual energetics

2016 ◽  
Author(s):  
Jorge Calle-Espinosa ◽  
Miguel Ponce-de-Leon ◽  
Diego Santos-Garcia ◽  
Francisco J. Silva ◽  
Francisco Montero ◽  
...  
Keyword(s):  
Amino Acid ◽  
Energy Production ◽  
Metabolic Networks ◽  
Metabolic Model ◽  
Atp Production ◽  
Symbiotic Associations ◽  
Bacterial Endosymbiont ◽  
Metabolic Functions ◽  
A Genome ◽  
Genome Scale

Bacterial lineages that establish obligate symbiotic associations with insect hosts are known to possess highly reduced genomes with streamlined metabolic functions that are commonly focused on amino acid and vitamin synthesis. We constructed a genome-scale metabolic model of the whitefly bacterial endosymbiont Candidatus Portiera aleyrodidarum to study the energy production capabilities using stoichiometric analysis. Strikingly, the results suggest that the energetic metabolism of the bacterial endosymbiont relies on the use of pathways related to the synthesis of amino acids and carotenoids. A deeper insight showed that the ATP production via carotenoid synthesis may also have a potential role in the regulation of amino acid production. The coupling of energy production to anabolism suggest that minimization of metabolic networks as a consequence of genome size reduction does not necessarily limit the biosynthetic potential of obligate endosymbionts.

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