Title: Integrated Regulatory and Metabolic Networks of the Marine Diatom Phaeodactylum tricornutum Predict the Response to Rising CO ₂ Levels

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. 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 involvedmore » 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.« less

Authors:

Levering, Jennifer  ^[1];

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Dupont, Christopher L. ^[2]; Allen, Andrew E. ^[3]; Palsson, Bernhard O. ^[1]; Zengler, Karsten ^[1]; Lin, ed., Xiaoxia

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+ Show Author Affiliations

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

Publication Date:

Tue Feb 28 00:00:00 EST 2017

Research Org.:

J. Craig Venter Inst., La Jolla, CA (United States); Univ. of California, San Diego, CA (United States)

Sponsoring Org.:

USDOE Office of Science (SC), Biological and Environmental Research (BER); National Science Foundation (NSF); Gordon and Betty Moore Foundation (United States)

OSTI Identifier:

1618373

Alternate Identifier(s):

OSTI ID: 1423796

Grant/Contract Number:  

DOE-DE-SC0008593; DOE-DE-SC0006719; SC0008593; SC0006719; MCB-1024913; MCB-1129303; GBMF3828

Resource Type:

Published Article

Journal Name:

mSystems

Additional Journal Information:

Journal Name: mSystems Journal Volume: 2 Journal Issue: 1; Journal ID: ISSN 2379-5077

Publisher:

American Society for Microbiology

Country of Publication:

United States

Language:

English

Subject:

59 BASIC BIOLOGICAL SCIENCES; Phaeodactylum tricornutum; coregulated genes; genome-scale metabolic network reconstruction; integrated network modeling; regulatory network inference