OptFill: A Tool for Infeasible Cycle-Free Gapfilling of Stoichiometric Metabolic Models
Summary: Stoichiometric metabolic modeling, particularly genome-scale models (GSMs), is now an indispensable tool for systems biology. The model reconstruction process typically involves collecting information from public databases; however, incomplete systems knowledge leaves gaps in any reconstruc...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2020-01-01
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| Series: | iScience |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2589004219305280 |
| _version_ | 1818573380833509376 |
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| author | Wheaton L. Schroeder Rajib Saha |
| author_facet | Wheaton L. Schroeder Rajib Saha |
| author_sort | Wheaton L. Schroeder |
| collection | DOAJ |
| description | Summary: Stoichiometric metabolic modeling, particularly genome-scale models (GSMs), is now an indispensable tool for systems biology. The model reconstruction process typically involves collecting information from public databases; however, incomplete systems knowledge leaves gaps in any reconstruction. Current tools for addressing gaps use databases of biochemical functionalities to address gaps on a per-metabolite basis and can provide multiple solutions but cannot avoid thermodynamically infeasible cycles (TICs), invariably requiring lengthy manual curation. To address these limitations, this work introduces an optimization-based multi-step method named OptFill, which performs TIC-avoiding whole-model gapfilling. We applied OptFill to three fictional prokaryotic models of increasing sizes and to a published GSM of Escherichia coli, iJR904. This application resulted in holistic and infeasible cycle-free gapfilling solutions. In addition, OptFill can be adapted to automate inherent TICs identification in any GSM. Overall, OptFill can address critical issues in automated development of high-quality GSMs. : Metabolic Engineering; Bioinformatics; Systems Biology; Metabolic Flux Analysis Subject Areas: Metabolic Engineering, Bioinformatics, Systems Biology, Metabolic Flux Analysis |
| first_indexed | 2024-12-15T00:10:24Z |
| format | Article |
| id | doaj.art-0e2e588c42ef44d1bd9e0c31fee0d31d |
| institution | Directory Open Access Journal |
| issn | 2589-0042 |
| language | English |
| last_indexed | 2024-12-15T00:10:24Z |
| publishDate | 2020-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | iScience |
| spelling | doaj.art-0e2e588c42ef44d1bd9e0c31fee0d31d2022-12-21T22:42:35ZengElsevieriScience2589-00422020-01-01231OptFill: A Tool for Infeasible Cycle-Free Gapfilling of Stoichiometric Metabolic ModelsWheaton L. Schroeder0Rajib Saha1Department of Chemical and Biomolecular Engineering, University of Nebraska-Lincoln, Lincoln, NE 68588, USADepartment of Chemical and Biomolecular Engineering, University of Nebraska-Lincoln, Lincoln, NE 68588, USA; Corresponding authorSummary: Stoichiometric metabolic modeling, particularly genome-scale models (GSMs), is now an indispensable tool for systems biology. The model reconstruction process typically involves collecting information from public databases; however, incomplete systems knowledge leaves gaps in any reconstruction. Current tools for addressing gaps use databases of biochemical functionalities to address gaps on a per-metabolite basis and can provide multiple solutions but cannot avoid thermodynamically infeasible cycles (TICs), invariably requiring lengthy manual curation. To address these limitations, this work introduces an optimization-based multi-step method named OptFill, which performs TIC-avoiding whole-model gapfilling. We applied OptFill to three fictional prokaryotic models of increasing sizes and to a published GSM of Escherichia coli, iJR904. This application resulted in holistic and infeasible cycle-free gapfilling solutions. In addition, OptFill can be adapted to automate inherent TICs identification in any GSM. Overall, OptFill can address critical issues in automated development of high-quality GSMs. : Metabolic Engineering; Bioinformatics; Systems Biology; Metabolic Flux Analysis Subject Areas: Metabolic Engineering, Bioinformatics, Systems Biology, Metabolic Flux Analysishttp://www.sciencedirect.com/science/article/pii/S2589004219305280 |
| spellingShingle | Wheaton L. Schroeder Rajib Saha OptFill: A Tool for Infeasible Cycle-Free Gapfilling of Stoichiometric Metabolic Models iScience |
| title | OptFill: A Tool for Infeasible Cycle-Free Gapfilling of Stoichiometric Metabolic Models |
| title_full | OptFill: A Tool for Infeasible Cycle-Free Gapfilling of Stoichiometric Metabolic Models |
| title_fullStr | OptFill: A Tool for Infeasible Cycle-Free Gapfilling of Stoichiometric Metabolic Models |
| title_full_unstemmed | OptFill: A Tool for Infeasible Cycle-Free Gapfilling of Stoichiometric Metabolic Models |
| title_short | OptFill: A Tool for Infeasible Cycle-Free Gapfilling of Stoichiometric Metabolic Models |
| title_sort | optfill a tool for infeasible cycle free gapfilling of stoichiometric metabolic models |
| url | http://www.sciencedirect.com/science/article/pii/S2589004219305280 |
| work_keys_str_mv | AT wheatonlschroeder optfillatoolforinfeasiblecyclefreegapfillingofstoichiometricmetabolicmodels AT rajibsaha optfillatoolforinfeasiblecyclefreegapfillingofstoichiometricmetabolicmodels |