1. Volume 2, Issue 5, Pages 312-322 (May 2016)
A Genome-Scale Database and Reconstruction of Caenorhabditis elegans Metabolism 
Juliane Gebauer, Christoph Gentsch, Johannes Mansfeld, Kathrin Schmeißer, Silvio Waschina, Susanne Brandes, Lukas Klimmasch, Nicola Zamboni, Kim Zarse, Stefan Schuster, Michael Ristow, Sascha Schäuble, Christoph Kaleta 
Cell Systems 
Volume 2, Issue 5, Pages (May 2016)
DOI: /j.cels
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2. Cell Systems 2016 2, 312-322DOI: (10.1016/j.cels.2016.04.017)
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3. Figure 1
Predicted Changes in Amino Acid Consumption after bcat-1 Knockout
Changes in the consumption of amino acids after bcat-1 knockout are shown. The y axis indicates the logarithmic fold change of the consumption of an amino acid after bcat-1 knockout. Values correspond to the logarithm of the quotient of wild-type flux and mutant flux. Thus, a positive value indicates a higher consumption in the wild-type compared to the mutant, and, hence, amino acid concentrations are increased in the mutant. Each boxblot corresponds to 100 independent runs of the sampling algorithm. The arrow above each boxplot indicates the direction of significant changes (FDR-corrected p value < 0.05) in amino acid concentration after in vivo knockdown of bcat-1: an upward arrow corresponds to a concentration increase and a downward arrow a concentration decrease in the mutant. Thick arrows correspond to significant changes (p value < 0.05). Please note the differences in plot ranges between the left and the right plots. Asterisks indicate the FDR-corrected significance of change after in silico knockout based on a paired Wilcoxon rank-sum test: ∗p < 0.05, ∗∗p < 0.01, and ∗∗∗p < See also the Supplemental Experimental Procedures, sections S1 and S2, Table S4, and Data S2.
Cell Systems 2016 2, DOI: ( /j.cels )
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4. Figure 2 NAD Biosynthesis from L-Tryptophan
The simplified pathway depicts NAD biosynthesis from L-tryptophan (gray background) with the missing reaction NNDPR. The red- and yellow-emphasized reactions represent further degradation pathways for L-tryptophan. The red-shaded reactions catalyze serotonin biosynthesis and the yellow reactions degrade aminocarboxymuconate semialdehyde (cmusa) to glutaryl-CoA. cmusa, aminocarboxymuconate semialdehyde; 2OXOADOX, 2-oxoadipate-dehydrogenase; 3HAO, 3-Hydroxyanthranilate 3,4-dioxygenase; 5HLTDL, Aromatic-L-amino-acid decarboxylase; AM6SAD, Aminomuconate-semiladehyde dehydrogenase; AMCOXO, 2-aminomuconate reductase; FKYNH, Arylformamidase; HKYNH, 3-Hydroxy-kynureninase; KYN3OX, Kynurenine 3-monooxygenase; NADS2, NAD(+)-synthase; NNAT, Nicotinate-nucleotide adenylyltransferase; NNDPR, Nicotinate-nucleotide pyrophosphorylase; PCLAD, Aminocarboxymuconate-semialdehyde decarboxylase; QUILSYN, Quinolinate Synthase; TRPHYDRO2, Tryptophan 5-monooxygenase; TRPO2, Tryptophan 2,3-dioxygenase.
Cell Systems 2016 2, DOI: ( /j.cels )
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5. Figure 3
Effect of L-tryptophan Feeding on Lifespan and Quinolinic Acid Concentration in C. elegans
(A) N2 wild-type worms supplemented with indicated concentrations of L-tryptophan show significant lifespan extension at low concentrations (0.5 and 5 mM; p < and p < ; both +5%) and significant lifespan reduction at high concentrations (0.5 and 5 mM; both p < ; −8% and −12%).
(B) HPLC measurements of nicotinamide adenine dinucleotide (NAD) after incubation of N2 wild-type worms with L-tryptophan in the concentrations of 0.2, 1, and 5 mM for 24 hr. The bars show the mean of the measurements for each concentration and the error bars show the SD.
(C) HPLC measurements of quinolinic acid (QA) after incubation of N2 wild-type worms with L-tryptophan in the concentrations of 0.2, 1, and 5 mM for 24 hr.
See also Table S5.
Cell Systems 2016 2, DOI: ( /j.cels )
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6. Figure 4 Generation of Context-Specific Metabolic Networks
Fold changes and probabilities (p values) of differential expression are calculated between the individual time points, including changes between the last and the first time points (time point 1d∗ and expression value 33∗ shown for clarity). These serve as input to discretize gene expression states into on (1) and off (0) states for the individual time points. The activity states of all genes for the individual time points are used as input to the iMAT algorithm, which reconstructs context-specific models for each time point.
Cell Systems 2016 2, DOI: ( /j.cels )
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7. Figure 5 Analysis of Context-Specific Networks
(A) Principal component analysis of context-specific networks derived for all three treatments (normal aging [DMSO], rotenone treatment, and DOG treatment). The sum of variances of the first three principal components is d, 5d, 10d, 20d, time points in days; rot, networks based on rotenone treatment data; DOG, networks based on DOG treatment data.
(B) Sizes of context-specific networks for normal aging (DMSO) and perturbed aging (Rotenone and DOG) are shown.
(C) Time-dependent similarity of context-specific networks. A ratio of one implies that both networks are equal and likewise a ratio of zero implies that both networks have no common reactions.
See also Data S1; Tables S1, S2, S3, and S6; and the Supplemental Experimental Procedures, section S4.
Cell Systems 2016 2, DOI: ( /j.cels )
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8. Figure 6 Age-Specific Pathway Regulation in Context-Specific Networks
(A) Age-specific metabolic activity in nine generalized metabolic categories is shown. The y-axis indicates the number of reactions belonging to each subsystem for each model, the x-axis the corresponding timepoint of aging.
(B) Detailed pathway categories with divergent regulation between normal and perturbed aging are shown (see also Data S1, Table S6, and the Supplemental Experimental Procedures, section S5).
Cell Systems 2016 2, DOI: ( /j.cels )
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