Rui Manuel Furtado Bezerra

In reactions where the enzyme is inhibited by the product, using the classical method based on initial rates to determine kinetic parameters may give rise to biased values. In fact, under certain conditions, failure to include the effect of product inhibition may generate errors of such magnitude that estimated parameters may not deserve any credit. In this work, three substrate depletion thresholds were used to obtain initial rates in reactions inhibited by the product and by a second different inhibitor. Kinetic parameters were determined by Michaelis–Menten rate equation using initial rates obtained from the slopes of theoretical curves product versus time simulated by MATLAB (in silico data). Errors in estimated parameters, including those of second inhibitor (K _ic2 and K _iu2 ), were quantified for each of the three substrate thresholds. As expected, in the absence of reaction product inhibition, i.e., when its inhibition constant tends towards infinity, minimal errors are observed in remaining estimated parameters. However, depending on the magnitude of product inhibition, percentage error in estimated parameter values can exceed 100%, being influenced by the parameter type (K _ic2 and K _iu2 are the most biased) and also by the substrate depletion threshold for determining initial rates (greater bias when substrate depletion exceeds 1%). In this work, we prove that when product inhibition occurs, the kinetic constants determined from the initial rates are generally subject to errors and, therefore, this is not a reliable method. Thus, in order to avoid determining potentially biased kinetic parameters values, we suggest an alternative methodology.

In this study, chestnut shells (CNS), a recalcitrant and low-value agro-industrial waste obtained during the peeling of Castanea sativa fruits, were subjected to solid-state fermentation by six white-rot fungal strains (Irpex lacteus, Ganoderma resinaceum, Phlebia rufa, Bjerkandera adusta and two Trametes isolates). After being fermented, CNS was subjected to hydrolysis by a commercial enzymatic mix to evaluate the effect of fermentation in saccharification yield. After 48 h hydrolysis with 10 CMCase U mL⁻¹ enzymatic mix, CNS fermented with both Trametes strains was recorded with higher saccharification yield (around 253 mg g⁻¹ fermented CNS), representing 25% w/w increase in reducing sugars as compared to non-fermented controls. To clarify the relationships and general mechanisms of fungal fermentation and its impacts on substrate saccharification, the effects of some independent or explanatory variables in the production of reducing sugars were estimated by general predictive saccharification models. The variables considered were lignocellulolytic activities in fungal fermentation, CNS hydrolysis time, and concentration of enzymatic hydrolysis mix. Multiple linear regression analysis revealed a very high significant effect (p < 0.0001) of fungal laccase and xylanase activities in the saccharification models, thus proving the key potential of these enzymes in CNS solid-state fermentation.

The Michaelis–Menten equation (MME) has been extensively used in biochemical reactions, but it is not appropriate when the reaction product inhibits the enzyme. Under these circumstances, each determined initial velocity, v₀, is one experimental point that actually belongs to a different MME because enzymatic product inhibition occurs as the reaction starts. Furthermore, the inhibition effect is not constant, since the concentration of the product inhibitor rises as time increases. To unveil the hidden enzyme inhibition and to simultaneously demonstrate the superiority of an integrated Michaelis–Menten equation (IMME), the same range of data points, assuming product inhibition and the presence of a second different inhibitor, was used for kinetic analysis with both methodologies. This study highlights the superiority of the IMME methodology for when the enzyme is inhibited by the reaction product, giving a more coherent inhibition model and more accurate kinetic constants than the classical MME methodology.

Grape stalks, an inedible lignocellulosic residue from winemaking and agro-industrial grape juice production, can be valorized as a source of bioactive compounds and as feedstock for the saccharification and bioconversion of soluble sugars. Solid-state fermentation (SSF) by six white-rot fungi was applied as pretreatment. Fiber composition, free radical scavenging activity, four ligninolytic, and three hydrolytic enzyme activities were determined. Saccharification kinetics, yield, and productivity were evaluated and complemented with scanning electron microscopy (SEM), high performance liquid chromatography (HPLC) quantification of monosaccharides, and principal component analysis (PCA). After SSF, the biomass exhibited a drastic free radical scavenging activity decrease and the main enzymes produced were manganese-dependent peroxidase and xylanase. Scanning electron microscopy revealed the erosion of cell walls, and PCA exhibited a negative correlation between saccharification, and neutral detergent fiber and acid detergent lignin. Phlebia rufa pretreated biomass gave the highest sugars yield and productivity, representing a nearly three-fold increase compared to untreated samples. Also, monosaccharides quantification revealed that the 1:1 ratio of glucose to the sum of xylose plus galactose changes to the value of 2:1 after pretreatment. In this work, and for the first time, P. rufa proved to be an effective pretreatment of grape stalks for the saccharification and further bioconversion into value-added chemicals. In addition, lignocellulolytic enzymes were also produced through SSF.

This study describes the development of a new methodology based on a new integrated equation which allows the determination of the kinetic parameters for two mutually non-exclusive inhibitors when one of which is produced during the time-course reaction. Alkaline phosphatase simultaneously inhibited by phosphate and urea is used to illustrate this methodology, including the evaluation of interaction effects between them. Data analyses were carried out using two integrated velocity equations: exclusive linear mixed inhibition (EMI) and non-exclusive linear mixed inhibition (NEMI). Kinetic parameters are estimated using non-linear regression and results show that (i) the interaction between enzyme and the inhibitors urea and phosphate exhibit a mutually non-exclusive behavior; (ii) more specifically, these inhibitors are non-exclusive only in free enzyme (E) species; (iii) the inhibitors also show an interaction with enzyme classified as facilitation; (iv) phosphate is a competitive inhibitor and urea a mixed inhibitor; (v) the inhibition constant for phosphate is much lower than that determined for urea. In addition, a functional Excel Spreadsheet which can be adapted to any kinetic study is also included as a supplement.

Forested wetlands are interfaces between terrestrial and aquatic environments. These ecosystems play an important role in the hydrology, chemistry and biodiversity maintenance. Despite their high microbial diversity, there has been a lack of attention to the potential of their yeast communities. The purpose of this study is to evaluate the potential of yeasts isolated from a Mediterranean forested wetlands in decolorizing azo dyes. Azo dyes are synthetic, and highly recalcitrant to degradation. Ninety-two out of 560 isolates were randomly chosen to assess their ability to decolorize five azo dyes. Hierarchical clustering based on medium color changes during incubations was used to evaluate the isolates’ decolorization performance. All of the isolates that best degraded the 5 dyes tested were identified as Basidiomycota (Filobasidiales, Tremellales and Sporidiobolales). This work identifies new azo dye-degrading yeast species, and supports the hypothesis that forested wetlands are a niche for yeasts with bioremediation potential - namely azo dyes removal.

Laccase from the white-rot fungus Fomes fomentarius was used for the biodegradation of ferulic acid (FA) in the presence of chloride anions. The initial reaction rates of substrate depletion were obtained by reverse-phase HPLC determination of remaining FA since substrate and reaction products have absorption peaks at similar wavelengths. Modelling of time-course data was accomplished by discrimination of the best enzyme inhibition equation from an initial set of seven different models based on Michaelis–Menten kinetics: competitive; uncompetitive; non-competitive; mixed; mixed hyperbolic; mixed parabolic; mixed hyperbolic and parabolic. Corrected Akaike information criterion was used to evaluate the relative merit of each kinetic model in order to rank them and find the more likely one. The discrimination results showed that the models with higher probabilities were the competitive and mixed inhibition types, but Akaike weights supported the selection of competitive inhibition (CI). After optimization by nonlinear regression, laccase kinetic parameters of FA biodegradation in the presence of chloride anions were: V_max = 0.11 μmol min⁻¹ mg⁻¹, K_m = 44 μmol L⁻¹ and a CI constant K_ic = 14 mmol L⁻¹.