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Table 1.

Comparison of frequently used approaches in fluxomics.

Parameter A is used in the extended Debye-Hückel equation.

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Table 1 Expand

Table 2.

Factors considered in mod-matTFA.

Values 0/1 refer to the binary codification for the full factorial design (S3 Table). In total, 26 combinations were tested.

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Table 2 Expand

Fig 1.

Calculation of the parameter A.

The red line refers to the temperature-dependent function (Eq 5), whereas the surface is the temperature/salinity-dependent function (Eq 6).

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Fig 1 Expand

Table 3.

Relative factor importance.

The type of analysis depended on the nature of the response: classification was selected for TFA (full), TFA (match 13C-MFA), concentration values (full) and concentration values (match experimental), and regression for r (fluxomics) and r (metabolomics). The former was suited for categorical responses (i.e. which solution is achieved, as shown in S4 Table), and the latter for continuous responses (for Pearson's r, from -1 to +1).

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Table 3 Expand

Table 4.

Tests with the highest score in the joint ranking.

The full list is available in (S4 Table). *(run #3) reflects the conditions used in the original matTFA.

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Table 4 Expand

Table 5.

Quantified metabolites in the top 50% of PageRank (PR) based analysis.

The last position in the ranking (#622) was L-Tyrosine (PR score = 0.0004), which had been quantified. The full list can be found in (S4 Dataset).

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Table 5 Expand

Fig 2.

Anaplerotic node for E. coli.

Set of carboxylation/decarboxylation reactions including phosphoenolpyruvate, pyruvate, oxaloacetate, and malate. Arrows indicate the expected direction of carbon fluxes. Boxes refer to reactions: blue when they are defined in both the GSM and the metabolic network used for 13C-MFA, and orange when they are exclusively considered in the GSM. In the latter case no mapping was possible (S1 Table).

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Fig 2 Expand

Table 6.

Flux pattern changes between 13C-MFA data and matTFA predictions.

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Table 6 Expand