Model-assisted analysis of sugar metabolism throughout tomato fruit development reveals enzyme and carrier properties in relation to vacuole expansion

Abstract

A kinetic model combining enzyme activity measurements and subcellular compartmentation was parameterized to fit the sucrose, hexose, and glucose-6-P contents of pericarp throughout tomato (Solanum lycopersicum) fruit development. The model was further validated using independent data obtained from domesticated and wild tomato species and on transgenic lines. A hierarchical clustering analysis of the calculated fluxes and enzyme capacities together revealed stage-dependent features. Cell division was characterized by a high sucrolytic activity of the vacuole, whereas sucrose cleavage during expansion was sustained by both sucrose synthase and neutral invertase, associated with minimal futile cycling. Most importantly, a tight correlation between flux rate and enzyme capacity was found for fructokinase and PPi-dependent phosphofructokinase during cell division and for sucrose synthase, UDP-glucopyrophosphorylase, and phosphoglucomutase during expansion, thus suggesting an adaptation of enzyme abundance to metabolic needs. In contrast, for most enzymes, flux rates varied irrespectively of enzyme capacities, and most enzymes functioned at <5% of their maximal catalytic capacity. One of the major findings with the model was the high accumulation of soluble sugars within the vacuole together with organic acids, thus enabling the osmotic-driven vacuole expansion that was found during cell division.

Figure 1.

Time-Course Evolution of Fresh Weight and Cellular and Subcellular Volumes throughout Fruit Development. (A) Growth curve of Moneymaker tomato fruit. Continuous line represents regression analysis using a three-parameter logistic function. (B) Mean volume of parenchyma cells of Moneymaker (closed circles) and Ailsa Craig (open circles) pericarp (mean ± sd, n = 3 fruits). (C) Fractional volume of vacuole (circles), cytoplasm (triangles), and cell wall (squares) within cells of Moneymaker (closed symbols) and Ailsa Craig (open symbols) tomato pericarp (mean ± sd, n = 3 fruits). Continuous lines represent nonlinear regression of vacuole and cytoplasm volume fractions and dashed line, that of the cell wall (see Supplemental Table 4 for details). (D) Water flow across tonoplast resulting from vacuole expansion within cell (dashed line), cell expansion within fruit (dotted line), or both (continuous line).

Figure 2.

Schematic Network of Metabolism and Compartmentation of Carbohydrates in Tomato Fruit Pericarp. Network reactions: v1, sucrose import; v2, GK; v3, FK; v4, SPS; v5, sucrose-6-phosphatase (SPase); v6, Susy; v7, NI; v8 and v9, ATP- and PPi-dependent phosphofructokinase (PFK and PFP, respectively); v10, sucrose carrier; v11, AI; v12, sucrose storage; v13, glucose storage; v14, fructose storage; v15 and v16, hexose carrier; v17, PGI; v18, PGM; v19, UDP-glucopyrophosphorylase (UGPase); v20, ALD; v21, starch synthesis; v22, cell wall synthesis; v23, glucose-6-P/Pi translocase; v24, FBPase. Output fluxes are italicized. Chemical reactions, rate equations, and kinetic parameters are detailed in Supplemental Tables 2 and 3.

Figure 3.

Comparison between Simulated and Experimentally Measured Soluble Sugars and Glucose-6P Contents of Pericarp. Open squares represent pericarp content (in μmol min⁻¹ g⁻¹ FW, mean ± sd, n = 3 to 6 fruits) of glucose (A), fructose (B), sucrose (C), and glucose-6P (D) from Biais et al. (2014). At each developmental stage, parameter optimization (V1, V_max10 and V_max15 = V_max16) was performed as described in Methods. Steady state concentrations of Glc, Fru, Suc, and Glc-6P contents were calculated for each parameter combination (n = 300 to 400 parameter sets depending on stage) and their means ± sd are represented by green symbols. Alternatively, a new set of parameters was built from the median values of the 300 to 400 combinations and the model run with this new set of parameters gives the calculated Glc, Fru, Suc, and Glc-6P contents represented by magenta symbols. For glucose-6P (D), calculations were performed using a plastid-to-cytoplasm Pi concentration ratio of either 10 (circles) or 30 (triangles).

Figure 4.

Intra- and Interspecies Cross-Validation of Model. (A) Model was parameterized using enzyme capacities measured with Moneymaker pericarp sampled at 35, 42, and 49 DPA (Steinhauser et al., 2010). Sucrose, glucose, and fructose contents (circles, squares, and triangles, respectively) are expressed relatively to 7-DPA-aged fruit as described by Carrari et al. (2006). (B) Model was parameterized using enzyme capacities measured at breaker stage on ten transgenic lines of L. esculentum underexpressing acid invertase (Klann et al., 1996) (gray circles) and at seven developmental stages of L. chmielewskii wild tomato and its introgression lines (Yelle et al., 1988, 1991) (white and black circles, respectively). Suc content is expressed as percentage of total sugars, as described by Klann et al. (1996). Diagonals represent 100% match between simulations and experiments.

Figure 5.

Influence of Parameterization of Vacuolar Acid Invertase, Glucokinase, and Vacuolar Carriers on Model Fitness. (A) Model was parameterized with (black bars) or without retroinhibition of glucokinase (dark-gray bars) and acid invertase (white bars) or without H⁺-coupling of vacuolar carriers (light-gray bars). (B) Model was parameterized with a K_m value of the hexose carrier equal to either 40, 4, or 0.4 mM and that of the sucrose carrier, to either 120, 12, or 1.2 mM, corresponding to very low (white bars), low (gray bars), and high (black bars) affinity conditions, respectively. At each developmental stage and for each condition, parameter optimization (V1, V_max10 and V_max15 = V_max16) was performed and the sum of squared residuals between measurements and calculations of Glc, Fru, and Suc (see Supplemental Figure 6 for raw results) weighted by the sd of each measurement was calculated to score the model fitness. Inserts show cumulative sum of squared residuals over all stages. Error bars were calculated from data of Supplemental Figure 6.

Figure 6.

Model Predictions of Capacity of Vacuolar Carriers and Sucrose Import of Pericarp Cells. At each developmental stage, parameter optimization (V1, V_max10 and V_max15 = V_max16) was performed for three different models parameterized using either a very low (triangles), low (circles), or high (squares) affinity of the vacuolar carriers, as in Figure 5B. Plotted values are the median (n = 300 to 400 parameter sets) of the respective parameters and come from the box plot graphs of Supplemental Figure 7. Open circles represent values predicted by the fruit construction cost model of Heuvelink (1995). (A) V_max of sucrose carrier (V_max10). (B) V_max of hexose carrier (V_max15 = V_max16). (C) Sucrose import (V1).

Figure 7.

Flux Partitioning within Network during Fruit Growth. At each developmental stage, fluxes were calculated at steady state using the optimized parameters (V1, V_max10 and V_max15 = V_max16) in Figure 6. Values are means ± sd of n = 3 values calculated under conditions of very low, low, and high affinity vacuolar carriers. (A) Output fluxes of polysaccharide synthesis (V21+V22) (blue squares), sugar storage (V12*2+V13+V14) (green triangles), and glycolysis (V20) (magenta circles). (B) Fluxes of sucrose cycle enzymes, i.e., acid (V11) (magenta squares) and neutral invertase (V7) (green circles), Susy (V6) (blue triangles), and SPS (V4) (black diamonds). (C) Fluxes of Fru-1,6-bis-P cycle enzymes, i.e., PFP (V9) (green squares), PFK (V8) (blue circles), and FBPase (V24) (magenta triangles). Note that flux values of SPS and FBPase are negative. Abbreviations are the same as in Figure 2.

Figure 8.

Role of Sugars and Organic Acids in Osmotic Strength of Vacuole during Fruit Growth. At each developmental stage, fluxes and concentrations were calculated at steady state using the optimized parameters (V1, V_max10 and V_max15 = V_max16) of Figure 6. Values are means ± sd of n = 3 values calculated under conditions of very low, low, and high affinity vacuolar carriers. (A) Partitioning of sucrose transported into vacuole between sugar storage (V12*2+V13+V14) and hexose efflux (V15+V16) (gray and white bars, respectively). (B) Net sugar influx across tonoplast (V10+V15+V16). (C) Contribution of sugars (open circles), organic acids (open triangles), and both (closed squares) to osmotic strength of vacuole. (D) Control of the sum of vacuolar Glc, Fru, and Suc concentrations by acid invertase (closed triangles), vacuolar sucrose carrier (closed circles), and cellular sucrose import (open circles).

Figure 9.

Hierarchical Clustering of Fluxes and Enzyme Capacities during Fruit Growth. Heat map was obtained after two-dimensional hierarchical clustering analysis, where columns correspond to the 10 developmental stages and rows to mean-centered values scaled to unit variance of fluxes and enzyme capacities. Numbers next to dendograms reflect correlation-based distance measures. Three main clusters are highlighted corresponding to colored bars on the right. Color code: blue, higher values during cell division; green, higher values during cell division and beginning of cell expansion; yellow, higher values at mid expansion. Abbreviations are the same as in Figure 2.

Figure 10.

Fractional Velocity of Enzymes during Fruit Growth. Fractional velocity, i.e., flux-to-V_max ratio, was calculated from flux and V_max values of the respective enzymes. Values are means ± sd of n = 3 values calculated under conditions of very low, low, and high affinity vacuolar carriers. (A) Enzymes of sucrose cycle. (B) Aldolase, glucokinase, and fructokinase. (C) Enzymes of Fru-1,6BP cycle. (D) Hexose-P interconverting enzymes. Abbreviations are the same as in Figure 2.