Analysis of Key Factors for Evaluating Mucosal Adhesion Using Swine Buccal Tissue.

The assessment of the mucoadhesive properties peak mucoadhesive force (Fmax) and work of mucoadhesion (Wmuc) with texture analyzers is a common in vitro method for analyzing formulation capabilities. Challenges arise in selecting and standardizing experimental conditions due to various variables influencing mucoadhesion. This complexity hampers direct product performance comparisons. In our study, we explored factors (contact force and time, probe speed and mucin in artificial saliva) impacting a model formulation's mucoadhesive capacity. Using Omcilon-A®Orabase on porcine buccal mucosa, we systematically varied experimental conditions, employing a statistical approach (Central Composite Design - CCD). Three variables (contact force, contact time, probe speed) and their interactions were assessed for their impact on Fmax and Wmuc. Results showed that contact time and force positively affected Fmax, while only contact time influenced Wmuc. In the mucin artificial saliva test, a force of 0.5 N, time of 600 s, and speed of 1 mm/s yielded optimal Fmax (0.587 N) and Wmuc (0.468 N.s). These conditions serve as a reference for comparing mucoadhesive properties of formulations for topical oral use.

Fermentation strategies to improve propionic acid production with propionibacterium ssp.: a review.

Propionic acid (PA) is a carboxylic acid applied in a variety of processes, such as food and feed preservative, and as a chemical intermediate in the production of polymers, pesticides and drugs. PA production is predominantly performed by petrochemical routes, but environmental issues are making it necessary to use sustainable processes based on renewable materials. PA production by fermentation with the Propionibacterium genus is a promising option in this scenario, due to the ability of this genus to consume a variety of renewable carbon sources with higher productivity than other native microorganisms. However, Propionibacterium fermentation processes present important challenges that must be faced to make this route competitive, such as: a high fermentation time, product inhibition and low PA final titer, which increase the cost of product recovery. This article summarizes the state of the art regarding strategies to improve PA production by fermentation with the Propionibacterium genus. Firstly, strategies associated with environmental fermentation conditions and nutrition requirements are discussed. Subsequently, advantages and disadvantages of various strategies proposed to improve process performance (high cell concentration by immobilization or recycle, co-culture fermentation, genome shuffling, evolutive and metabolic engineering, and in situ recovery) are evaluated.

Secretome analysis as a tool to elucidate bacterial contamination influence during second-generation ethanol production in a Melle-Boinot process.

Melle-boinot fermentation process can be used to increase the ethanol productivity in second-generation ethanol process (2G). However, bacterial contamination can result in decreased ethanol production and sugars consumption. The available literature on microbial contamination in the 2G at the secretome level, microbial interactions and their impacts on ethanol production are scarce. In this context, the cultivation of Spathaspora passalidarum was studied in pure and co-culture with Lactobacillus fermentum under conditions that mimic the Melle-boinot process. Glucose consumption and ethanol production by S. passalidarum were not affected by bacterial contamination. Xylose consumption was higher in pure culture (11.54 ± 2.62, 16.23 ± 1.76 and 6.50 ± 1.68 g) than in co-culture fermentation (11.89 ± 0.38, 7.29 ± 0.49 and 5.54 ± 2.63 g) in cycle 2. The protein profile of the fermented broth was similar in pure and co-culture fermentation. The low effect of L. fermentum on fermentation and protein profile may be associated with the inhibition of the bacteria by the low nutrient fermentation broth, with centrifugation and/or with sulfuric acid washing. Thereby, considering that research on microbial contamination in the 2G fermentation process is very limited, particularly at the omics level, these findings may contribute to the lignocellulosic biomass fermentation industry.

Analysis of the proteins secreted by Trichoderma harzianum P49P11 under carbon-limited conditions.

The wild type strain Trichoderma harzianum was able to synthesize enzymes that can catalyse the hydrolysis of p-nitrophenyl-ß-D-glucopyranoside (PNPGase) in glucose-limited chemostat cultures. Fructose/glucose and sucrose conditions provided low levels of PNPGase activity. To investigate whether under these conditions other enzymes were produced, a shotgun proteomics analysis of their supernatants was performed. The analysis has indicated that the different carbon sources used influenced the amounts of proteins secreted including 1,3-beta-glucanosyltransferase, alpha-1,2-mannosidase, alpha-galactosidase and glucan 1,3-beta-glucosidase. The analysis has also suggested the presence of beta-glucosidase, which could also be represented by PNPGase activity. Intracellular metabolites were quantified during PNPGase production for the condition using 20 g/L of glucose in the feed and differences were observed, indicating that intracellular glucose could be inhibiting PNPGase production. SIGNIFICANCE: This work shows that sugars such as glucose, fructose/glucose and sucrose can be used as substrates for the continuous synthesis of different enzymes under carbon-limited conditions by Trichoderma harzianum. As far as we know, this is the first work about the continuous synthesis of enzymes under carbon-limited conditions suggesting that different easily assimilated carbon sources can be used to generate different enzymatic cocktails. Each enzyme or uncharacterized protein suggested by shotgun proteomics has the potential to become a promising product for biotechnological applications.

Effect of contamination with Lactobacillus fermentum I2 on ethanol production by Spathaspora passalidarum.

Second-generation bioethanol is a promising source of renewable energy. In Brazilian mills, the production of ethanol from sugarcane (first generation, 1G) is a consolidated process performed by Saccharomyces cerevisiae and characterized by high substrate concentrations, high cell density, and cell recycle. The main bacterial contaminants in 1G fermentation tanks are lactic acid bacteria, especially bacteria from the Lactobacillus genus, which is associated with a decrease in ethanol yield and yeast cell viability, among other negative effects. Second-generation (2G) bioethanol production is characterized by the conversion of glucose and xylose into ethanol by genetically modified or non-Saccharomyces yeasts. Spathaspora passalidarum is a promising non-Saccharomyces yeast for 2G ethanol production due to its ability to effectively convert xylose into ethanol. The effect of bacterial contamination on the fermentation of this yeast is unknown; therefore, L. fermentum, a common bacterium found in Brazilian 1G processes, was studied in coculture with S. passalidarum in a fed-batch fermentation process similar to that used in 1G mills. Individually, L. fermentum I2 was able to simultaneously consume glucose and xylose in nutrient-rich broth (Man, Rogosa, and Sharpe (MRS + xylose) but failed to grow in a glucose- and xylose-based synthetic broth. In coculture with S. passalidarum, the bacteria remained at a concentration of 108 UFC/mL throughout cell recycling, but no flocculation was observed, and it did not affect the fermentative parameters or the cellular viability of the yeast. Under both conditions, the maximum ethanol production was 21 g L-1 with volumetric productivity ranging from 0.65 to 0.70 g L-1 h-1. S. passalidarum was thus shown to be resistant to L. fermentum I2 under the conditions studied.

A robotic platform to screen aqueous two-phase systems for overcoming inhibition in enzymatic reactions.

Aqueous two-phase systems (ATPS) can be applied to enzymatic reactions that are affected by product inhibition. In the biorefinery context, sugars inhibit the cellulolytic enzymes in charge of converting the biomass. Here, we present a strategy to select an ATPS (formed by polymer and salt) that can separate sugar and enzymes. This automated and miniaturized method is able to determine phase diagrams and partition coefficients of solutes in these. Tailored approaches to quantify the solutes are presented, taking into account the limitations of techniques that can be applied with ATPS due to the interference of phase forming components with the analytics. The developed high-throughput (HT) platform identifies suitable phase forming components and the tie line of operation. This fast methodology proposes to screen up to six different polymer-salt systems in eight days and supplies the results to understand the influence of sugar and protein concentrations on their partition coefficients.

Bioethanol production by recycled Scheffersomyces stipitis in sequential batch fermentations with high cell density using xylose and glucose mixture.

Here, it is shown three-step investigative procedures aiming to improve pentose-rich fermentations performance, involving a simple system for elevated mass production by Scheffersomyces stipitis (I), cellular recycle batch fermentations (CRBFs) at high cell density using two temperature strategies (fixed at 30°C; decreasing from 30 to 26°C) (II), and a short-term adaptation action seeking to acclimatize the microorganism in xylose rich-media (III). Cellular propagation provided 0.52gdrycellweightgRS(-1), resulting in an expressive value of 45.9gdrycellweightL(-1). The yeast robustness in CRBF was proven by effective ethanol production, reaching high xylose consumption (81%) and EtOH productivity (1.53gL(-1)h(-1)). Regarding the short-term adaptation, S. stipitis strengthened its robustness, as shown by a 6-fold increase in xylose reductase (XR) activity. The short fermentation time (20h for each batch) and the fermentation kinetics for ethanol production from xylose are quite promising.

Mathematical modeling of enzyme production using Trichoderma harzianum P49P11 and sugarcane bagasse as carbon source.

A mathematical model to describe the kinetics of enzyme production by the filamentous fungus Trichoderma harzianum P49P11 was developed using a low cost substrate as main carbon source (pretreated sugarcane bagasse). The model describes the cell growth, variation of substrate concentration and production of three kinds of enzymes (cellulases, beta-glucosidase and xylanase) in different sugarcane bagasse concentrations (5; 10; 20; 30; 40 gL(-1)). The 10 gL(-1) concentration was used to validate the model and the other to parameter estimation. The model for enzyme production has terms implicitly representing induction and repression. Substrate variation was represented by a simple degradation rate. The models seem to represent well the kinetics with a good fit for the majority of the assays. Validation results indicate that the models are adequate to represent the kinetics for a biotechnological process.

Effects of the pretreatment method on high solids enzymatic hydrolysis and ethanol fermentation of the cellulosic fraction of sugarcane bagasse.

This work evaluated ethanol production from sugarcane bagasse at high solids loadings in the pretreatment (20-40% w/v) and hydrolysis (10-20% w/v) stages. The best conditions for diluted sulfuric acid, AHP and Ox-B pretreatments were determined and mass balances including pretreatment, hydrolysis and fermentation were calculated. From a technical point of view, the best pretreatment was AHP, which enabled the production of glucose concentrations near 8% with high productivity (3.27 g/Lh), as well as ethanol production from 100.9 to 135.4 kg ethanol/ton raw bagasse. However, reagent consumption for acid pretreatment was much lower. Furthermore, for processes that use pentoses and hexoses separately, this pretreatment produces the most desirable pentoses liquor, with higher xylose concentration in the monomeric form.

Adsorption characteristics of cellulase and ß-glucosidase on Avicel, pretreated sugarcane bagasse, and lignin.

Although adsorption is an essential step in the enzymatic hydrolysis of lignocellulosic materials, literature reports controversial results in relation to the adsorption of the cellulolitic enzymes on different biomasses/pretreatments, which makes difficult the description of this phenomenon in hydrolysis mathematical models. In this work, the adsorption of these enzymes on Avicel and sugarcane bagasse pretreated by the hydrothermal bagasse (HB) and organosolv bagasse (OB) methods was evaluated. The results have shown no significant adsorption of ß-glucosidase on Avicel or HB. Increasing solids concentration from 5% (w/v) to 10% (w/v) had no impact on the adsorption of cellulase on the different biomasses if stirring rates were high enough (>100 rpm for Avicel and >150 rpm for HB and OB). Adsorption equilibrium time was low for Avicel (10 Min) when compared with the lignocellulosic materials (120 Min). Adsorption isotherms determined at 4 and 50 °C have shown that for Avicel there was a decrease in the maximum adsorption capacity (Emax) with the temperature increase, whereas for HB increasing temperature increased Emax . Also, Emax increased with the content of lignin in the material. Adsorption studies of cellulase on lignin left after enzymatic digestion of HB show lower but significant adsorption capacity (Emax = 11.92 ± 0.76 mg/g).

Study of kinetic parameters in a mechanistic model for enzymatic hydrolysis of sugarcane bagasse subjected to different pretreatments.

The goal of this work is to evaluate the influence of different pretreatments in the kinetics of enzymatic hydrolysis of sugarcane bagasse and to propose a reliable methodology to easily perform sensitivity analysis and updating kinetic parameters whenever necessary. A kinetic model was modified to represent the experimental data of the batch enzymatic hydrolysis of sugarcane bagasse pretreated with alkaline hydrogen peroxide. The simultaneous estimation of kinetic parameters of the mathematical model was performed using the Pikaia genetic algorithm using batch hydrolysis experimental data obtained with different enzymatic loads. Subsequently, Plackett-Burman designs were used to identify the kinetic parameters with the higher influence on the dynamic behavior of the process variables, which were re-estimated to describe experimental data of the hydrolysis of bagasse pretreated with phosphoric acid + sodium hydroxide. The methodology was accurate and straightforward and can be used whenever there are changes in pretreatment conditions and/or fluctuations in biomass composition in different harvests.

Kinetics of ethanol production from sugarcane bagasse enzymatic hydrolysate concentrated with molasses under cell recycle.

In this work, a kinetic model for ethanol fermentation from sugarcane bagasse enzymatic hydrolysate concentrated with molasses was developed. A model previously developed for fermentation of pure molasses was modified by the inclusion of a new term for acetic acid inhibition on microorganism growth rate and the kinetic parameters were estimated as functions of temperature. The influence of the hydrolysate on the kinetic parameters is analyzed by comparing with the parameters from fermentation of pure molasses. The impact of cells recycling in the kinetic parameters is also evaluated, as well as on the ethanol yield and productivity. The model developed described accurately most of the fermentations performed in several successive batches for temperatures from 30 to 38°C.

Kinetic modeling and parameter estimation in a tower bioreactor for bioethanol production.

In this work, a systematic method to support the building of bioprocess models through the use of different optimization techniques is presented. The method was applied to a tower bioreactor for bioethanol production with immobilized cells of Saccharomyces cerevisiae. Specifically, a step-by-step procedure to the estimation problem is proposed. As the first step, the potential of global searching of real-coded genetic algorithm (RGA) was applied for simultaneous estimation of the parameters. Subsequently, the most significant parameters were identified using the Placket-Burman (PB) design. Finally, the quasi-Newton algorithm (QN) was used for optimization of the most significant parameters, near the global optimum region, as the initial values were already determined by the RGA global-searching algorithm. The results have shown that the performance of the estimation procedure applied in a deterministic detailed model to describe the experimental data is improved using the proposed method (RGA-PB-QN) in comparison with a model whose parameters were only optimized by RGA.