7Integrating Metabolic Modeling and High-Throughput Data to Characterize Diatoms Metabolism

Juan D. Tibocha-Bonilla1, Manish Kumar2, Karsten Zengler2,3,4 and Cristal Zuniga2,5*

1 Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, California, USA

2 Department of Pediatrics, University of California, San Diego, La Jolla, California, USA

3 Department of Bioengineering, University of California, San Diego, California, USA

4 Center for Microbiome Innovation, University of California, San Diego, La Jolla, California, USA

5 Department of Biology, San Diego State University, San Diego, California, USA


Metabolic modeling is a quantitative tool that uses genome-scale networks to predict growth phenotypes with high accuracy. During the reconstruction of metabolic networks of diatoms the genome annotation is manually improved by including new gene-protein-reaction associations of organelle-specific pathways, as well as intra- and extracellular transporters. Metabolic modeling combined with omic data of diatoms has been applied to identify suitable culture conditions, unravel interwoven regulatory mechanisms, explore genetic enhancement strategies for bioproduction, and quantify changes in resource allocation under nutrients limitation.

Computational models offer insights into the function of pathways critical for diatom physiology, from central carbon metabolism to lipid, pigment, and pathways involved in photon uptake. Here, we ...

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