Global connectivity in genome-scale metabolic networks revealed by comprehensive FBA-based pathway analysis
Abstract Background Graph-based analysis (GBA) of genome-scale metabolic networks has revealed system-level structures such as the bow-tie connectivity that describes the overall mass flow in a network. However, many pathways obtained by GBA are biologically impossible, making it difficult to study...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2021-10-01
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| Series: | BMC Microbiology |
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| Online Access: | https://doi.org/10.1186/s12866-021-02357-1 |
| _version_ | 1831763013821005824 |
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| author | Yajie Gao Qianqian Yuan Zhitao Mao Hao Liu Hongwu Ma |
| author_facet | Yajie Gao Qianqian Yuan Zhitao Mao Hao Liu Hongwu Ma |
| author_sort | Yajie Gao |
| collection | DOAJ |
| description | Abstract Background Graph-based analysis (GBA) of genome-scale metabolic networks has revealed system-level structures such as the bow-tie connectivity that describes the overall mass flow in a network. However, many pathways obtained by GBA are biologically impossible, making it difficult to study how the global structures affect the biological functions of a network. New method that can calculate the biologically relevant pathways is desirable for structural analysis of metabolic networks. Results Here, we present a new method to determine the bow-tie connectivity structure by calculating possible pathways between any pairs of metabolites in the metabolic network using a flux balance analysis (FBA) approach to ensure that the obtained pathways are biologically relevant. We tested this method with 15 selected high-quality genome-scale metabolic models from BiGG database. The results confirmed the key roles of central metabolites in network connectivity, locating in the core part of the bow-tie structure, the giant strongly connected component (GSC). However, the sizes of GSCs revealed by GBA are significantly larger than those by FBA approach. A great number of metabolites in the GSC from GBA actually cannot be produced from or converted to other metabolites through a mass balanced pathway and thus should not be in GSC but in other subsets of the bow-tie structure. In contrast, the bow-tie structural classification of metabolites obtained by FBA is more biologically relevant and suitable for the study of the structure-function relationships of genome scale metabolic networks. Conclusions The FBA based pathway calculation improve the biologically relevant classification of metabolites in the bow-tie connectivity structure of the metabolic network, taking us one step further toward understanding how such system-level structures impact the biological functions of an organism. |
| first_indexed | 2024-12-22T05:17:35Z |
| format | Article |
| id | doaj.art-51acf4abc3804ece8294d52992496899 |
| institution | Directory Open Access Journal |
| issn | 1471-2180 |
| language | English |
| last_indexed | 2024-12-22T05:17:35Z |
| publishDate | 2021-10-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Microbiology |
| spelling | doaj.art-51acf4abc3804ece8294d529924968992022-12-21T18:37:48ZengBMCBMC Microbiology1471-21802021-10-0121111510.1186/s12866-021-02357-1Global connectivity in genome-scale metabolic networks revealed by comprehensive FBA-based pathway analysisYajie Gao0Qianqian Yuan1Zhitao Mao2Hao Liu3Hongwu Ma4Biodesign Center, Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of SciencesBiodesign Center, Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of SciencesBiodesign Center, Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of SciencesCollege of Biotechnology, Tianjin University of Science & TechnologyBiodesign Center, Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of SciencesAbstract Background Graph-based analysis (GBA) of genome-scale metabolic networks has revealed system-level structures such as the bow-tie connectivity that describes the overall mass flow in a network. However, many pathways obtained by GBA are biologically impossible, making it difficult to study how the global structures affect the biological functions of a network. New method that can calculate the biologically relevant pathways is desirable for structural analysis of metabolic networks. Results Here, we present a new method to determine the bow-tie connectivity structure by calculating possible pathways between any pairs of metabolites in the metabolic network using a flux balance analysis (FBA) approach to ensure that the obtained pathways are biologically relevant. We tested this method with 15 selected high-quality genome-scale metabolic models from BiGG database. The results confirmed the key roles of central metabolites in network connectivity, locating in the core part of the bow-tie structure, the giant strongly connected component (GSC). However, the sizes of GSCs revealed by GBA are significantly larger than those by FBA approach. A great number of metabolites in the GSC from GBA actually cannot be produced from or converted to other metabolites through a mass balanced pathway and thus should not be in GSC but in other subsets of the bow-tie structure. In contrast, the bow-tie structural classification of metabolites obtained by FBA is more biologically relevant and suitable for the study of the structure-function relationships of genome scale metabolic networks. Conclusions The FBA based pathway calculation improve the biologically relevant classification of metabolites in the bow-tie connectivity structure of the metabolic network, taking us one step further toward understanding how such system-level structures impact the biological functions of an organism.https://doi.org/10.1186/s12866-021-02357-1Genome-scale metabolic networkFlux balance analysisBow-tie structureGiant strongly connected component (GSC)Network connectivityPathway analysis |
| spellingShingle | Yajie Gao Qianqian Yuan Zhitao Mao Hao Liu Hongwu Ma Global connectivity in genome-scale metabolic networks revealed by comprehensive FBA-based pathway analysis BMC Microbiology Genome-scale metabolic network Flux balance analysis Bow-tie structure Giant strongly connected component (GSC) Network connectivity Pathway analysis |
| title | Global connectivity in genome-scale metabolic networks revealed by comprehensive FBA-based pathway analysis |
| title_full | Global connectivity in genome-scale metabolic networks revealed by comprehensive FBA-based pathway analysis |
| title_fullStr | Global connectivity in genome-scale metabolic networks revealed by comprehensive FBA-based pathway analysis |
| title_full_unstemmed | Global connectivity in genome-scale metabolic networks revealed by comprehensive FBA-based pathway analysis |
| title_short | Global connectivity in genome-scale metabolic networks revealed by comprehensive FBA-based pathway analysis |
| title_sort | global connectivity in genome scale metabolic networks revealed by comprehensive fba based pathway analysis |
| topic | Genome-scale metabolic network Flux balance analysis Bow-tie structure Giant strongly connected component (GSC) Network connectivity Pathway analysis |
| url | https://doi.org/10.1186/s12866-021-02357-1 |
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