Reconstruction and flux‐balance analysis of the Plasmodium falciparum metabolic network
Genome‐scale metabolic reconstructions can serve as important tools for hypothesis generation and high‐throughput data integration. Here, we present a metabolic network reconstruction and flux‐balance analysis (FBA) of Plasmodium falciparum, the primary agent of malaria. The compartmentalized metabo...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Springer Nature
2010-01-01
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| Series: | Molecular Systems Biology |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/msb.2010.60 |
| _version_ | 1797281833394634752 |
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| author | Germán Plata Tzu‐Lin Hsiao Kellen L Olszewski Manuel Llinás Dennis Vitkup |
| author_facet | Germán Plata Tzu‐Lin Hsiao Kellen L Olszewski Manuel Llinás Dennis Vitkup |
| author_sort | Germán Plata |
| collection | DOAJ |
| description | Genome‐scale metabolic reconstructions can serve as important tools for hypothesis generation and high‐throughput data integration. Here, we present a metabolic network reconstruction and flux‐balance analysis (FBA) of Plasmodium falciparum, the primary agent of malaria. The compartmentalized metabolic network accounts for 1001 reactions and 616 metabolites. Enzyme–gene associations were established for 366 genes and 75% of all enzymatic reactions. Compared with other microbes, the P. falciparum metabolic network contains a relatively high number of essential genes, suggesting little redundancy of the parasite metabolism. The model was able to reproduce phenotypes of experimental gene knockout and drug inhibition assays with up to 90% accuracy. Moreover, using constraints based on gene‐expression data, the model was able to predict the direction of concentration changes for external metabolites with 70% accuracy. Using FBA of the reconstructed network, we identified 40 enzymatic drug targets (i.e. in silico essential genes), with no or very low sequence identity to human proteins. To demonstrate that the model can be used to make clinically relevant predictions, we experimentally tested one of the identified drug targets, nicotinate mononucleotide adenylyltransferase, using a recently discovered small‐molecule inhibitor. |
| first_indexed | 2024-03-07T17:03:08Z |
| format | Article |
| id | doaj.art-aa54f29d20cf486f8ff7286518d9e058 |
| institution | Directory Open Access Journal |
| issn | 1744-4292 |
| language | English |
| last_indexed | 2024-03-07T17:03:08Z |
| publishDate | 2010-01-01 |
| publisher | Springer Nature |
| record_format | Article |
| series | Molecular Systems Biology |
| spelling | doaj.art-aa54f29d20cf486f8ff7286518d9e0582024-03-03T03:11:51ZengSpringer NatureMolecular Systems Biology1744-42922010-01-0161n/an/a10.1038/msb.2010.60Reconstruction and flux‐balance analysis of the Plasmodium falciparum metabolic networkGermán Plata0Tzu‐Lin Hsiao1Kellen L Olszewski2Manuel Llinás3Dennis Vitkup4Center for Computational Biology and Bioinformatics, Columbia University New York City NY USACenter for Computational Biology and Bioinformatics, Columbia University New York City NY USADepartment of Molecular Biology, Princeton University Princeton NJ USADepartment of Molecular Biology, Princeton University Princeton NJ USACenter for Computational Biology and Bioinformatics, Columbia University New York City NY USAGenome‐scale metabolic reconstructions can serve as important tools for hypothesis generation and high‐throughput data integration. Here, we present a metabolic network reconstruction and flux‐balance analysis (FBA) of Plasmodium falciparum, the primary agent of malaria. The compartmentalized metabolic network accounts for 1001 reactions and 616 metabolites. Enzyme–gene associations were established for 366 genes and 75% of all enzymatic reactions. Compared with other microbes, the P. falciparum metabolic network contains a relatively high number of essential genes, suggesting little redundancy of the parasite metabolism. The model was able to reproduce phenotypes of experimental gene knockout and drug inhibition assays with up to 90% accuracy. Moreover, using constraints based on gene‐expression data, the model was able to predict the direction of concentration changes for external metabolites with 70% accuracy. Using FBA of the reconstructed network, we identified 40 enzymatic drug targets (i.e. in silico essential genes), with no or very low sequence identity to human proteins. To demonstrate that the model can be used to make clinically relevant predictions, we experimentally tested one of the identified drug targets, nicotinate mononucleotide adenylyltransferase, using a recently discovered small‐molecule inhibitor.https://doi.org/10.1038/msb.2010.60flux‐balance analysisPlasmodium falciparum metabolismsystems biology |
| spellingShingle | Germán Plata Tzu‐Lin Hsiao Kellen L Olszewski Manuel Llinás Dennis Vitkup Reconstruction and flux‐balance analysis of the Plasmodium falciparum metabolic network Molecular Systems Biology flux‐balance analysis Plasmodium falciparum metabolism systems biology |
| title | Reconstruction and flux‐balance analysis of the Plasmodium falciparum metabolic network |
| title_full | Reconstruction and flux‐balance analysis of the Plasmodium falciparum metabolic network |
| title_fullStr | Reconstruction and flux‐balance analysis of the Plasmodium falciparum metabolic network |
| title_full_unstemmed | Reconstruction and flux‐balance analysis of the Plasmodium falciparum metabolic network |
| title_short | Reconstruction and flux‐balance analysis of the Plasmodium falciparum metabolic network |
| title_sort | reconstruction and flux balance analysis of the plasmodium falciparum metabolic network |
| topic | flux‐balance analysis Plasmodium falciparum metabolism systems biology |
| url | https://doi.org/10.1038/msb.2010.60 |
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