%0 Journal Article %1 Colasanti2014Tapping %A Colasanti, Ric %A Edirisinghe, Janaka N. %A Khazaei, Tahmineh %A Faria, José P. %A Seaver, Sam %A Xia, Fangfang %A Henry, Christopher %D 2014 %J Methods in molecular biology (Clifton, N.J.) %K genome-scale metabolic-networks protocol reconstruction %P 19--45 %R 10.1007/978-1-4939-1170-7\_2 %T Tapping the wealth of microbial data in high-throughput metabolic model reconstruction. %U http://dx.doi.org/10.1007/978-1-4939-1170-7\_2 %V 1191 %X Genome-scale metabolic models are valuable tools in the metabolic engineering process, based on the ability of these models to integrate diverse sources of data to produce global predictions of organism behavior. At the most basic level, these models require only a genome sequence to construct, and once built, they may be used to predict essential genes, culture conditions, pathway utilization, and the modifications required to enhance a desired organism behavior. In this chapter, we address two key challenges associated with the reconstruction of metabolic models: (a) leveraging existing knowledge of microbiology, biochemistry, and available 'omics data to produce the best possible model; and (b) applying available tools and data to automate the reconstruction process. We consider these challenges as we progress through the model reconstruction process, beginning with genome assembly, and culminating in the integration of constraints to capture the impact of transcriptional regulation. We divide the reconstruction process into ten distinct steps: (1) genome assembly from sequenced reads; (2) automated structural and functional annotation; (3) phylogenetic tree-based curation of genome annotations; (4) assembly and standardization of biochemistry database; (5) genome-scale metabolic reconstruction; (6) generation of core metabolic model; (7) generation of biomass composition reaction; (8) completion of draft metabolic model; (9) curation of metabolic model; and (10) integration of regulatory constraints. Each of these ten steps is documented in detail.

@article{Colasanti2014Tapping, abstract = {Genome-scale metabolic models are valuable tools in the metabolic engineering process, based on the ability of these models to integrate diverse sources of data to produce global predictions of organism behavior. At the most basic level, these models require only a genome sequence to construct, and once built, they may be used to predict essential genes, culture conditions, pathway utilization, and the modifications required to enhance a desired organism behavior. In this chapter, we address two key challenges associated with the reconstruction of metabolic models: (a) leveraging existing knowledge of microbiology, biochemistry, and available 'omics data to produce the best possible model; and (b) applying available tools and data to automate the reconstruction process. We consider these challenges as we progress through the model reconstruction process, beginning with genome assembly, and culminating in the integration of constraints to capture the impact of transcriptional regulation. We divide the reconstruction process into ten distinct steps: (1) genome assembly from sequenced reads; (2) automated structural and functional annotation; (3) phylogenetic tree-based curation of genome annotations; (4) assembly and standardization of biochemistry database; (5) genome-scale metabolic reconstruction; (6) generation of core metabolic model; (7) generation of biomass composition reaction; (8) completion of draft metabolic model; (9) curation of metabolic model; and (10) integration of regulatory constraints. Each of these ten steps is documented in detail.}, added-at = {2018-12-02T16:09:07.000+0100}, author = {Colasanti, Ric and Edirisinghe, Janaka N. and Khazaei, Tahmineh and Faria, Jos\'{e} P. and Seaver, Sam and Xia, Fangfang and Henry, Christopher}, biburl = {https://www.bibsonomy.org/bibtex/27f546401676740e81bcc21d58f295545/karthikraman}, citeulike-article-id = {13367290}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/978-1-4939-1170-7\_2}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/25178782}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=25178782}, doi = {10.1007/978-1-4939-1170-7\_2}, interhash = {a40a5cacb2c3aa562c7927e932624223}, intrahash = {7f546401676740e81bcc21d58f295545}, issn = {1940-6029}, journal = {Methods in molecular biology (Clifton, N.J.)}, keywords = {genome-scale metabolic-networks protocol reconstruction}, pages = {19--45}, pmid = {25178782}, posted-at = {2014-09-19 06:17:38}, priority = {2}, timestamp = {2018-12-02T16:09:07.000+0100}, title = {Tapping the wealth of microbial data in high-throughput metabolic model reconstruction.}, url = {http://dx.doi.org/10.1007/978-1-4939-1170-7\_2}, volume = 1191, year = 2014 }