BackgroundSeveral methods have been developed to predict system-wide and condition-specific intracellular metabolic fluxes by integrating transcriptomic data with genome-scale metabolic models. While powerful in many settings, existing methods have several shortcomings, and it is unclear which method has the best accuracy in general because of limited validation against experimentally measured intracellular fluxes.ResultsWe present a general optimization strategy for inferring intracellular metabolic flux distributions from transcriptomic data coupled with genome-scale metabolic reconstructions. It consists of two different template models called DC (determined carbon source model) and AC (all possible carbon sources model) and two different new methods called E-Flux2 (E-Flux method combined with minimization of l2 norm) and SPOT (Simplified Pearson cOrrelation with Transcriptomic data), which can be chosen and combined depending on the availability of knowledge on carbon source or objective function. This enables us to simulate a broad range of experimental conditions. We examined E. coli and S. cerevisiae as representative prokaryotic and eukaryotic microorganisms respectively. The predictive accuracy of our algorithm was validated by calculating the uncentered Pearson correlation between predicted fluxes and measured fluxes. To this end, we compiled 20 experimental conditions (11 in E. coli and 9 in S. cerevisiae), of transcriptome measurements coupled with corresponding central carbon metabolism intracellular flux measurements determined by 13C metabolic flux analysis (13C-MFA), which is the largest dataset assembled to date for the purpose of validating inference methods for predicting intracellular fluxes. In both organisms, our method achieves an average correlation coefficient ranging from 0.59 to 0.87, outperforming a representative sample of competing methods. Easy-to-use implementations of E-Flux2 and SPOT are available as part of the open-source package MOST (http://most.ccib.rutgers.edu/).ConclusionOur method represents a significant advance over existing methods for inferring intracellular metabolic flux from transcriptomic data. It not only achieves higher accuracy, but it also combines into a single method a number of other desirable characteristics including applicability to a wide range of experimental conditions, production of a unique solution, fast running time, and the availability of a user-friendly implementation.

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A series of five experiments was conducted to determine the effect of pectin, gum arabic and agar (5%) on cholesterol absorption, biosynthesis and turnover in rats. In the study of cholesterol absorption, a tracer dose of labeled cholesterol was included in the last meal. The rats were killed 12 hours later. The proportion of the labeled cholesterol recovered in the whole body was used as an estimation of the efficiency of absorption of dietary cholesterol. Cholesterol biosynthesis was estimated by determining the activity of labeled digitonin-precipitable sterols biosynthesized from labeled glucose which was included in a test meal. In turnover studies, rats were injected intravenously with labeled cholesterol using serum as a vehicle, and the activity of labeled cholesterol in tissues was determined after various time intervals. All three complex carbohydrates decreased cholesterol absorption and pectin had the greatest effect. Pectin and gum arabic increased cholesterol biosynthesis in rats fed a cholesterol-containing diet, but had no effect in a cholesterol-free diet. Pectin slightly increased the turnover of cholesterol, but gum arabic and agar had no effect. This work supports the hypothesis that pectin lowers cholesterol levels by interfering with cholesterol absorption and by increasing cholesterol turnover. The study also suggests that complex carbohydrates differ in their effects on cholesterol metabolism. The reason for these differences remains to be determined.

Pectin, carragheenan, agar gum arabic, cellulose and wheat bran were each fed to rats at a level of 5 to 7% to examine their effect on serum, liver and tissue cholesterol levels. Diets (casein-sucrose diet containing 10-15% soybean oil, or skim milk-wheat flour diet containing 10-15% soybean oil) supplemented with either 0, 0.2, or 0.5% cholesterol were used to test the possibly dietary interactions. Among the fibers tested, pectin displayed the most hypocholesterolemic effect. In some experiments, pectin lowered the level of cholesterol in the serum, liver, and aorta, but it elevated body cholesterol levels. Carragheenan was inconsistent in lowering serum cholesterol levels and tended to increase liver and carcass cholesterol levels. These results probably suggest that pectin and carragheenan can affect the distribution of cholesterol within the body. Gum arabic and agar did not lower serum cholesterol levels and in one case gum arabic elevated them. Furthermore, in some experiments they elevated liver body cholesterol levels. It appears that feeding of gum arabic and agar probably resulted in an expansion of the whole body cholesterol pool. Feeding of wheat bran or cellulose had no significant effect on either serum or liver cholesterol levels. The study indicates that the effect of dietary fiber is dependent on the composition of the diet. Furthermore, while some fibers such as pectin may exhibit a hypocholesterolemic effect in rats, other fibers such as gum arabic and agar may actually elevate serum or tissue cholesterol levels.

dslun@rutgers.edu.