skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions

Journal Article · · Plant Physiology (Bethesda)
DOI:https://doi.org/10.1104/pp.16.00593· OSTI ID:1395087
 [1];  [2]; ORCiD logo [1]; ORCiD logo [1];  [1]; ORCiD logo [3]; ORCiD logo [3]; ORCiD logo [4]; ORCiD logo [4];  [3]; ORCiD logo [2];  [1]
  1. Univ. of California, San Diego, La Jolla, CA (United States)
  2. Johns Hopkins Univ., Baltimore, MD (United States)
  3. Univ. of Delaware, Newark, DE (United States)
  4. National Renewable Energy Lab. (NREL), Golden, CO (United States)
+ Show Author Affiliations

The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine.

Research Organization:
National Renewable Energy Laboratory (NREL), Golden, CO (United States); Johns Hopkins Univ., Baltimore, MD (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Basic Energy Sciences (BES); USDOE Office of Energy Efficiency and Renewable Energy (EERE)
Grant/Contract Number:
AC36-08GO28308; SC0012658
OSTI ID:
1395087
Alternate ID(s):
OSTI ID: 1485586
Report Number(s):
NREL/JA-5100-66824
Journal Information:
Plant Physiology (Bethesda), Vol. 172, Issue 1; ISSN 0032-0889
Publisher:
American Society of Plant BiologistsCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 69 works
Citation information provided by
Web of Science

Cited By (12)

Respirometry as a tool to quantify kinetic parameters of microalgal mixotrophic growth journal February 2019
Rapid and efficient genetic transformation of the green microalga Chlorella vulgaris journal January 2018
Utilizing genome-scale models to optimize nutrient supply for sustained algal growth and lipid productivity journal September 2019
Environmental stimuli drive a transition from cooperation to competition in synthetic phototrophic communities journal October 2019
Identification of nanoparticles and their localization in algal biofilm by 3D-imaging secondary ion mass spectrometry journal January 2019
Elucidation of complexity and prediction of interactions in microbial communities journal August 2017
Chlorella vulgaris genome assembly and annotation reveals the molecular basis for metabolic acclimation to high light conditions journal September 2019
Reconstruction of the microalga Nannochloropsis salina genome-scale metabolic model with applications to lipid production journal July 2017
Algal Cell Factories: Approaches, Applications, and Potentials journal December 2016
Effect of Delays on the Response of Microalgae When Exposed to Dynamic Environmental Conditions journal January 2020
Genome-scale metabolic reconstruction and metabolic versatility of an obligate methanotroph Methylococcus capsulatus str. Bath journal January 2019
Genome-scale metabolic reconstruction and metabolic versatility of an obligate methanotroph Methylococcus capsulatus str. Bath journal June 2018

Figures / Tables (8)

Table I(p. 38)table Table I
Table II(p. 39)table Table II
Table III(p. 40)table Table III
Figure 1(p. 42)figure Figure 1
Figure 2(p. 43)figure Figure 2
Figure 3(p. 44)figure Figure 3
Figure 4(p. 45)figure Figure 4
Figure 5(p. 46)figure Figure 5

Similar Records

Predicting Dynamic Metabolic Demands in the Photosynthetic Eukaryote Chlorella vulgaris
Journal Article · Tue Sep 26 00:00:00 EDT 2017 · Plant Physiology (Bethesda) · OSTI ID:1395087
+3 more
Phosphoproteome of the Oleaginous Green Alga, Chlorella vulgaris UTEX 395, under Nitrogen-Replete and -Deplete Conditions
Journal Article · Tue Mar 06 00:00:00 EST 2018 · Frontiers in Bioengineering and Biotechnology · OSTI ID:1395087
+1 more
Genome Sequence of the Oleaginous Green Alga, Chlorella vulgaris UTEX 395
Journal Article · Thu Apr 05 00:00:00 EDT 2018 · Frontiers in Bioengineering and Biotechnology · OSTI ID:1395087
+4 more

Related Subjects

09 BIOMASS FUELS
59 BASIC BIOLOGICAL SCIENCES
Chlorella vulgaris
genome-scale
reconstruction
validation
application