Discriminatory experiment for the kinetics of yeast glyoxalase I.

<p>A - Time courses of SDLGS concentration in the discriminatory setup experiment. Black: experimental result, average of 4 replicates (the grey shaded area is within one standard error of the mean). Blue: prediction by model 1. Red: prediction by model 2. Initial concentrations are 0.221 mM for glutathione, 2.0×10⁻³ mM for glyoxalase I, 0.441 mM for methylglyoxal and 4.0×10⁻³ mM for glyoxalase II. The initial concentrations correspond to the solution chosen from of the Pareto front highlighted in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0032749#pone-0032749-g004" target="_blank">figure 4A</a>. B and C - rates predicted by model 1 (B) and model 2 (C). Red: net rate of hemithioacetal formation, blue: rate of glyoxalase I reaction. green: rate of glyoxalase II reaction.</p

Kinetic models of the glyoxalase pathway.

<p>In model 1 (A), glutathione (GSH) and methylglyoxal (MGO) form a hemithioacetal (HTA) which is the substrate of glyoxalase I. In model 2 (B), glutathione and methylglyoxal are sequential substrates of glyoxalase I and the hemithioacetal is formed at the active centre of the enzyme. Glyoxalase II is a one-substrate-one-product irreversible Michaelis Menten enzyme, catalyzing the hydrolysis of <i>S</i>-D-lactoylglutatione (SDLGS) into D-lactate (D-Lac) and glutathione. The rate laws assumed in the models are expressed in equations 15 to 18.</p

Optimization of experimental design for model discrimination.

<p>A - Optimal initial concentrations of methylglyoxal and glutathione (solutions approximating the Pareto front) for the discrimination of the two models presented in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0032749#pone-0032749-g002" target="_blank">figure 2</a>. B – Corresponding values of the extended Kullback-Leibler distances (optimization objectives); Concentration of glyoxalase I is 2.0×10⁻³ mM and concentration of glyoxalase II is 4.0×10⁻⁴ mM. The red dot indicates the initial concentrations used in the discriminatory experiment.</p

Discrimination of kinetic models by maximization of the extended Kullback-Leibler distance (<i>I </i>).

<p>Conditions are sought that maximize <i>I</i> in both directions between any two models. In a two candidate model scenario (A) two functions must be simultaneously optimized. In a three candidate model scenario (B) six functions must be simultaneously optimized. After optimization, the set of solutions approximate a Pareto front and represent a compromise between the various objectives in the sense that, for any solution, the value of any objective could only be increased if the value of another objective was simultaneously decreased.</p

Landscapes of different measures of model divergences in the allowed optimization range of concentrations of pathway substrates.

<p>Measures of model distances are <i>I</i>_1,2 : extended Kullback-Leibler distance of model 2 from model 1 (equation 6). <i>I</i>_2,1 : extended Kullback-Leibler distance of model 1 from model 2 (equation 6). <i>L</i>₂ : simple <i>L</i>₂ norm (equation 4). <i>L</i>_2<i>w</i> : weighted <i>L</i>₂ norm (equation 5).</p

Transthyretin Amyloidosis: Chaperone Concentration Changes and Increased Proteolysis in the Pathway to Disease

<div><p>Transthyretin amyloidosis is a conformational pathology characterized by the extracellular formation of amyloid deposits and the progressive impairment of the peripheral nervous system. Point mutations in this tetrameric plasma protein decrease its stability and are linked to disease onset and progression. Since non-mutated transthyretin also forms amyloid in systemic senile amyloidosis and some mutation bearers are asymptomatic throughout their lives, non-genetic factors must also be involved in transthyretin amyloidosis. We discovered, using a differential proteomics approach, that extracellular chaperones such as fibrinogen, clusterin, haptoglobin, alpha-1-anti-trypsin and 2-macroglobulin are overrepresented in transthyretin amyloidosis. Our data shows that a complex network of extracellular chaperones are over represented in human plasma and we speculate that they act synergistically to cope with amyloid prone proteins. Proteostasis may thus be as important as point mutations in transthyretin amyloidosis.</p></div

Proteome analysis of plasma from ATTR individuals.

<p>A– 2D-PAGE analysis of plasma proteins. Labeled spots show a statistically significant variation (p<0.05) and a minimal fold variation of 1.5. These spots were excised, tryptic digested and proteins identified by MS/MS analysis. Average normalized volumes and protein identifications are presented in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125392#pone.0125392.t001" target="_blank">Table 1</a>. B–Principle component analysis (PCA) of the 2D results. Each data point in the PCA represents the global expression values for all spots with a significant ANOVA value (p<0.05). A separation between the control and the ATTR individuals is clearly observed. C- 2D image analysis of four protein spots and normalized volumes, shown as examples. D-Over expression of western blot analysis of plasma from four control and four FAP individuals to detect TTR. E—Western blot analysis of a 2DE of serum from four control and four FAP individuals to detect TTR with super imposition of spots identified as TTR in 2DE.</p

Extracellular Chaperones are overrepresented in DLT individuals—SDS-PAGE analysis of plasma proteins from four individuals after orthotic liver transplantation (OLT) and four individuals after domino transplantation (DLT) and Western blot to detect TTR, Fibrinogen, Alpha 1 anti-trypsin (ITI), Vitamin D binding protein (VBP), alpha 2 microglobolin and C-reactive protein (CRP).

<p>Molecular weight markers are represented on the left hand of the figure and included in the western blots as blue markers.</p

Functional annotation enrichment analysis of the identified proteins using the Database for Annotation, Visualization and Integrated Discovery (DAVID ) v6.7.

<p>Annotation terms are representative of a particular cluster. FDR – False discovery rate.</p

Detailed expression profiles for all the identified differentially expressed proteins, according to its functional categories: (A) cell metabolism; (B) unknown function; (C) Cell redox homeostasis; (D) protein folding and degradation; (E) translation.

<p>Grey bars represent fold change in protein expression in BTTR-wt versus the control while black bars represent fold change in protein expression in BTTR-L55P versus the control. The vertical axis indicates the identified protein while the horizontal axis represents the fold variation in protein expression. Additional information for each protein, including full name, can be found in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0050123#pone-0050123-t001" target="_blank">Table 1</a>. For proteins identified in different spots (with slightly different fold variations) the average is represented in the graph.</p