Supporting Information Legends
Figure S1. Overview of workflow for constructing and evaluating iCre1355.
Figure S2. Pathway-level expression of genes in iCre1355 across conditions. Heatmap
depicting the proportion of genes within each pathway in iCre1355 that are expressed above 3
FPKM.
Figure S3. Growth rates predicted by iCre1355 when using only measured NH4 uptake
as constraint.
Figure S4. Predicted effects of nitrogen starvation on pathway activity assessed by the
number of “low” activity state reactions in a pathway. Darker shades of blue indicate
lower predicted pathway activity based on an increased number of “low” activity state
reactions. Consistent with the observations in Figure 5, pathways like glycerolipid
biosynthesis, fatty acid elongation and porphyrin/chlorophyll metabolism are predicted to
decrease in activity (i.e., show an increased number of low activity reactions), while transport
and nitrogen metabolism are predicted to increase in activity. Some interesting difference
from Figure 5 can also be seen such as the increase in activity (i.e., decrease in number of
low activity reactions) of the purine metabolism, and valine, leucine and isoleucine
degradation pathways, which could suggest an increase in the turnover of these metabolites.
Figure S5. Predicted effects of change in light intensity on growth, pathway activity and
flux capacity. (a) Comparison of predicted growth to observed growth rate during time
course of shift in light intensity. (b) Changes in activity of pathways as a result of the change
in light intensity. (c) Correlation matrix of the predicted flux capacities for reactions in
iCre1355 and correlation matrix of gene expression data for metabolic genes in iCre1355
across time points.
Figure S6. Effect of the selected thresholds on the predictive accuracy of Eflux+iMAT.
(a) Graph depicting the mean squared error (i.e., the mean of the squared difference between
predicted and observed growth rates from the chemostat grown cells (Mettler et al., 2014))
for high expression cutoff values ranging from the 40th to the 95th percentile. This analysis
indicates that the growth rate predictions are relatively robust to this threshold. The low
expression threshold was set to the 15th percentile for this analysis. Equivalent results were
obtained for low expression thresholds between the 5th and 15th percentile. The red data point
corresponds to the high expression cutoff selected for our analysis. (b) Graph depicting the
mean squared error for low expression cutoff values ranging from the 5 th to the 30th
percentile. The predictive accuracy is sensitive to this cutoff as the mean squared error
significantly increases at values greater than or equal to the 20th percentile. Within this range
Eflux+iMAT predicts no growth under any condition (either high or low light). The high
expression threshold was set to the 85th percentile for this analysis. Equivalent results were
obtained for high expression thresholds between the 80th and 95th percentile. The red data
point corresponds to the low expression cutoff selected for our analysis.
Table S1: Details of the 312 nuclear, chloroplast and mitochondrial genes included in
iCre1355 after manual curation.
Table S2: Identified metabolic genes not included in iCre1355.
Table S3: Mapping of genes from iRC1080 to JGI v5.5 of the C. reinhardtii genome.
Table S4: Modifications made to network components from iRC1080.
Table S5: Reactions in iCre1355 in tabular format including all metadata.
Table S6: Metabolites in iCre1355 in tabular format including all metadata.
Table S7: Literature references for components included in iCre1355.
Table S8: List of 81 defined mutants in C. reinhardtii used for assessing the performance
of iCre1355.
Table S9. Comparison of experimentally observed and predicted gene deletion
phenotypes across photoautotrophic, mixotrophic and heterotrophic conditions.
iRC1080 and iCre1355 predictions provided, as well as predictions from iCre1355 using
the biomass reactions from iRC1080.
Dataset S1. iCre1355 in GAMS format.
Dataset S2. iCre1355 in SBML format.