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                            Dynamic models of metabolism can be useful in identifying potential drug targets, especially in unicellular organisms. A model of glycolysis in the causative agent of human African trypanosomiasis, Trypanosoma brucei, has already shown the utility of this approach. Here we add the pentose phosphate pathway (PPP) of T. brucei to the glycolytic model. The PPP is localized to both the cytosol and the glycosome and adding it to the glycolytic model without further adjustments leads to a draining of the essential bound-phosphate moiety within the glycosome. This phosphate "leak" must be resolved for the model to be a reasonable representation of parasite physiology. Two main types of theoretical solution to the problem could be identified: (i) including additional enzymatic reactions in the glycosome, or (ii) adding a mechanism to transfer bound phosphates between cytosol and glycosome. One example of the first type of solution would be the presence of a glycosomal ribokinase to regenerate ATP from ribose 5-phosphate and ADP. Experimental characterization of ribokinase in T. brucei showed that very low enzyme levels are sufficient for parasite survival, indicating that other mechanisms are required in controlling the phosphate leak. Examples of the second type would involve the presence of an ATP:ADP exchanger or recently described permeability pores in the glycosomal membrane, although the current absence of identified genes encoding such molecules impedes experimental testing by genetic manipulation. Confronted with this uncertainty, we present a modeling strategy that identifies robust predictions in the context of incomplete system characterization. We illustrate this strategy by exploring the mechanism underlying the essential function of one of the PPP enzymes, and validate it by confirming the model predictions experimentally.. 12, 9.
                            Wellcome Trust Centre for Molecular Parasitology, Institute of Infection, Immunity and Inflammation and Glasgow Polyomics, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom ; Systems and Synthetic Biology Group, Department of Chemical and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.</publication><submitter_mail>viji@ebi.ac.uk</submitter_mail><submitter_affiliation>EMBL-EBI</submitter_affiliation><publicationId>BIOMD0000000516</publicationId><pubmed_abstract>Dynamic models of metabolism can be useful in identifying potential drug targets, especially in unicellular organisms. A model of glycolysis in the causative agent of human African trypanosomiasis, Trypanosoma brucei, has already shown the utility of this approach. Here we add the pentose phosphate pathway (PPP) of T. brucei to the glycolytic model. The PPP is localized to both the cytosol and the glycosome and adding it to the glycolytic model without further adjustments leads to a draining of the essential bound-phosphate moiety within the glycosome. This phosphate "leak" must be resolved for the model to be a reasonable representation of parasite physiology. Two main types of theoretical solution to the problem could be identified: (i) including additional enzymatic reactions in the glycosome, or (ii) adding a mechanism to transfer bound phosphates between cytosol and glycosome. One example of the first type of solution would be the presence of a glycosomal ribokinase to regenerate ATP from ribose 5-phosphate and ADP. Experimental characterization of ribokinase in T. brucei showed that very low enzyme levels are sufficient for parasite survival, indicating that other mechanisms are required in controlling the phosphate leak. Examples of the second type would involve the presence of an ATP:ADP exchanger or recently described permeability pores in the glycosomal membrane, although the current absence of identified genes encoding such molecules impedes experimental testing by genetic manipulation. Confronted with this uncertainty, we present a modeling strategy that identifies robust predictions in the context of incomplete system characterization. We illustrate this strategy by exploring the mechanism underlying the essential function of one of the PPP enzymes, and validate it by confirming the model predictions experimentally.</pubmed_abstract><pubmed_title>Handling uncertainty in dynamic models: the pentose phosphate pathway in Trypanosoma brucei.</pubmed_title><pubmed_authors>Kerkhoven Eduard J EJ, Achcar Fiona F, Alibu Vincent P VP, Burchmore Richard J RJ, Gilbert Ian H IH, Trybiło Maciej M, Driessen Nicole N NN, Gilbert David D, Breitling Rainer R, Bakker Barbara M BM, Barrett Michael P MP</pubmed_authors><pubmed_abstract_synonyms>ribose phosphate, Striadyne, Materials, DCAF9, Product, Metabolic Concepts, A4, Embden-Meyerhof, Pentose, Pentose Phosphate Shunt, (D-ribofuranose)-isomer, 1B1, countertransporter activity, anon-EST:Posey9, solute:solute exchange, Hexose Monophosphate Shunts, Metabolism Concept, study treatment, Transfer, Bind, Theory, catabolism, D-ribokinase, Tissue, coding, Pathways, metabolic process resulting 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Additional, Manipulation, EST D, Limit, Revised International Prognostic Scoring System for Myelodysplastic Syndrome Very Low Risk Category, Pharmaceutical Preparation, pustulosis of palm and sole</pubmed_abstract_synonyms><name_synonyms>Striadyne, Fru, DCAF9, Fleboplast, Magnesium Adenosine Triphosphate, Adenosine Triphosphate, Plast Apyr Levulosa Mein, ATP-MgCl2, Embden-Meyerhof, Pentosephosphate Shunts, CG5124, Pentose, Gm695, pentose phosphate shunt, IB, Pentose Shunts, Pentose Phosphate Shunt, Embden Meyerhof Parnas Pathway, Pentosephosphate, Adenylpyrophosphate, Levulosa Mein, Hexose Monophosphate Shunts, pentose-phosphate pathway, Apir Levulosa, ATP-synbeta, modified Embden-Meyerhof pathway, pentose phosphate pathway, Fleboplast Levulosa, Embden-Meyerhof Pathway, Adenosine 5'-Pyrophosphate, anon-WO0196371.27, Hexose Monophosphate Shunt, Pentose-Phosphate Pathway, H4atp, arabino-Hexulose, Chromium Adenosine Triphosphate, DmelCG11154, beta-ATPase, ATP MgCl2, Pentose Phosphate 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        Kerkhoven2013 - Glycolysis and Pentose Phosphate Pathway in T.brucei - MODEL D in fructose medium (with ATP:ADP antiporter)
                  There are six models (Model A, B, C, C-fruc, D, D-fruc) described in the paper. Model A (        BIOMD0000000513
            ) is the model developed originally by Achar et al. (2012) (        BIOMD0000000428
            ), which describes glycolysis in T.brucei. This glycolysis model is extended to include pentose phosphate pathway (PPP), which is Model B ((        BIOMD0000000514
            ). Model B is further extended to include glycosomal ribokinase, leading to Model C (        BIOMD0000000510
            ). Model D (        BIOMD0000000511
            ) is again an extension of Model B, which includes an ATP:ADP antiporter. Model C-fruc (        BIOMD0000000515
            ) and Model D-fruc (        BIOMD0000000516
            ) are extensions of Model C and D, respectively, which includes fructose transporter and its subsequent utilizing reactions. This model correspond to Model D-fruc of the paper.        
                
                  This model is described in the article:
                        Handling uncertainty in dynamic models: the pentose phosphate pathway in Trypanosoma brucei.
                    
                Kerkhoven EJ, Achcar F, Alibu VP, Burchmore RJ, Gilbert IH, Trybiło M, Driessen NN, Gilbert D, Breitling R, Bakker BM, Barrett MP.
                PLoS Comput Biol. 2013 Dec;9(12):e1003371.
                Abstract:
                        Dynamic models of metabolism can be useful in identifying potential drug targets, especially in unicellular organisms. A model of glycolysis in the causative agent of human African trypanosomiasis, Trypanosoma brucei, has already shown the utility of this approach. Here we add the pentose phosphate pathway (PPP) of T. brucei to the glycolytic model. The PPP is localized to both the cytosol and the glycosome and adding it to the glycolytic model without further adjustments leads to a draining of the essential bound-phosphate moiety within the glycosome. This phosphate "leak" must be resolved for the model to be a reasonable representation of parasite physiology. Two main types of theoretical solution to the problem could be identified: (i) including additional enzymatic reactions in the glycosome, or (ii) adding a mechanism to transfer bound phosphates between cytosol and glycosome. One example of the first type of solution would be the presence of a glycosomal ribokinase to regenerate ATP from ribose 5-phosphate and ADP. Experimental characterization of ribokinase in T. brucei showed that very low enzyme levels are sufficient for parasite survival, indicating that other mechanisms are required in controlling the phosphate leak. Examples of the second type would involve the presence of an ATP:ADP exchanger or recently described permeability pores in the glycosomal membrane, although the current absence of identified genes encoding such molecules impedes experimental testing by genetic manipulation. Confronted with this uncertainty, we present a modeling strategy that identifies robust predictions in the context of incomplete system characterization. We illustrate this strategy by exploring the mechanism underlying the essential function of one of the PPP enzymes, and validate it by confirming the model predictions experimentally.
                    
                
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    </description><dates><last_modification>2024-08-21</last_modification><publication>2024-09-02</publication><submission>2014-01-31</submission></dates><accession>BIOMD0000000516</accession><cross_references><pubmed>24339766</pubmed><chebi>CHEBI:28757</chebi><chebi>CHEBI:57642</chebi><chebi>CHEBI:15422</chebi><chebi>CHEBI:16761</chebi><chebi>CHEBI:4170</chebi><chebi>CHEBI:17794</chebi><chebi>CHEBI:28874</chebi><chebi>CHEBI:15379</chebi><chebi>CHEBI:18009</chebi><chebi>CHEBI:48928</chebi><chebi>CHEBI:16526</chebi><chebi>CHEBI:58121</chebi><chebi>CHEBI:58273</chebi><chebi>CHEBI:17234</chebi><chebi>CHEBI:16474</chebi><chebi>CHEBI:15361</chebi><chebi>CHEBI:13389</chebi><chebi>CHEBI:40595</chebi><chebi>CHEBI:17138</chebi><chebi>CHEBI:17754</chebi><chebi>CHEBI:35490</chebi><chebi>CHEBI:14336</chebi><chebi>CHEBI:17842</chebi><chebi>CHEBI:18021</chebi><chebi>CHEBI:16027</chebi><chebi>CHEBI:16908</chebi><biomodels__db>MODEL1401310003</biomodels__db><biomodels__db>BIOMD0000000516</biomodels__db><pubchem__compound>59</pubchem__compound><pubchem__compound>444848</pubchem__compound><pubchem__compound>683</pubchem__compound><go>GO:0006096</go><go>GO:0006098</go><go>GO:0005829</go><go>GO:0020015</go><go>GO:0005623</go><taxonomy>5691</taxonomy><bto>BTO:0035490</bto><uniprot>Q9GRG6</uniprot></cross_references></HashMap>