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mSystems. 2017 Feb 14;2(1). pii: e00142-16. doi: 10.1128/mSystems.00142-16. eCollection 2017 Jan-Feb.

Integrated Regulatory and Metabolic Networks of the Marine Diatom Phaeodactylum tricornutum Predict the Response to Rising CO2 Levels.

Author information

1
Department of Bioengineering, University of California San Diego, La Jolla, California, USA.
2
Microbial and Environmental Genomics, J. Craig Venter Institute, La Jolla, California, USA.
3
Microbial and Environmental Genomics, J. Craig Venter Institute, La Jolla, California, USA; Integrative Oceanography Division, Scripps Institute of Oceanography, University of California San Diego, La Jolla, California, USA.

Abstract

Diatoms are eukaryotic microalgae that are responsible for up to 40% of the ocean's primary productivity. How diatoms respond to environmental perturbations such as elevated carbon concentrations in the atmosphere is currently poorly understood. We developed a transcriptional regulatory network based on various transcriptome sequencing expression libraries for different environmental responses to gain insight into the marine diatom's metabolic and regulatory interactions and provide a comprehensive framework of responses to increasing atmospheric carbon levels. This transcriptional regulatory network was integrated with a recently published genome-scale metabolic model of Phaeodactylum tricornutum to explore the connectivity of the regulatory network and shared metabolites. The integrated regulatory and metabolic model revealed highly connected modules within carbon and nitrogen metabolism. P. tricornutum's response to rising carbon levels was analyzed by using the recent genome-scale metabolic model with cross comparison to experimental manipulations of carbon dioxide. IMPORTANCE Using a systems biology approach, we studied the response of the marine diatom Phaeodactylum tricornutum to changing atmospheric carbon concentrations on an ocean-wide scale. By integrating an available genome-scale metabolic model and a newly developed transcriptional regulatory network inferred from transcriptome sequencing expression data, we demonstrate that carbon metabolism and nitrogen metabolism are strongly connected and the genes involved are coregulated in this model diatom. These tight regulatory constraints could play a major role during the adaptation of P. tricornutum to increasing carbon levels. The transcriptional regulatory network developed can be further used to study the effects of different environmental perturbations on P. tricornutum's metabolism.

KEYWORDS:

Phaeodactylum tricornutum; coregulated genes; genome-scale metabolic network reconstruction; integrated network modeling; regulatory network inference

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