Modeling of enzyme production kinetics

Engineering interventions in enzyme production: Lab to industrial scale

Commercial enzyme production has gained popularity due to its extensive applications in traditional and modern industrial sectors. Rigorous research activities are being conducted worldwide to make the enzyme production system more efficient, cost-effective and hence, sustainable. To overcome the lacunae in earlier enzyme production methods, new engineering interventions are being introduced to meet the growing demand for industrial enzymes. This review focuses initially on the current global scenario of the enzyme market followed by a discussion on different bioreactor design approaches. The use of novel membrane based, airlift and reciprocating plate bioreactors along with the emergence of micro-reactors have also been discussed. Further, the review covers different modelling and optimization strategies for the enzyme production process including advanced techniques like neural networks, adaptive neuro-fuzzy inference systems and genetic algorithms. Finally, the required thrust areas in the enzyme production sector have been highlighted with directions for future research.

Bioconversion of Fish Discards through the Production of Lactic Acid Bacteria and Metabolites: Sustainable Application of Fish Peptones in Nutritive Fermentation Media

In the current work, we study the capacity of 30 peptones obtained by enzyme proteolysis of ten discarded fish species (hake, megrim, red scorpionfish, pouting, mackerel, gurnard, blue whiting, Atlantic horse mackerel, grenadier, and boarfish) to support the growth and metabolite production of four lactic acid bacteria (LAB) of probiotic and technological importance. Batch fermentations of Lactobacillus plantarum, L. brevis, L. casei, and Leuconostoc mesenteroides in most of the media formulated with fish peptones (87% of the cases) led to similar growths (quantified as dry-weight biomass and viable cells) and metabolites (mainly lactic acid) than in commercial control broth (MRS). Comparisons among cultures were performed by means of the parameters obtained from the mathematical fittings of experimental kinetics to the logistic equation. Modelling among experimental and predicted data from each bioproduction was generally accurate. A simple economic assessment demonstrated the profitability achieved when MRS is substituted by media formulated with fish discards: a 3-4-fold reduction of costs for LAB biomass, viable cells formation, and lactic and acetic acid production. Thus, these fish peptones are promising alternatives to the expensive commercial peptones as well as a possible solution to valorize discarded fish biomasses and by-products.

Developing a new approach for (biological) optimal control problems: Application to optimization of laccase production with a comparison between response surface methodology and novel geometric procedure

Laccase production by indigenous fungus, Phanerochaete chrysosporium, requires solving optimal problems to determine the maximum production of the enzyme within a definite time period and conditions specified in the solid-state fermentation process. For this purpose, parallel to response surface methodology, an analytical approach has been proposed based on the advanced concepts of Poisson geometry and Lie groups, which lead to a system of the Hamiltonian equations. Despite the dating of the Hamiltonian approach to solving biological problems, the novelty of this paper is based on the expression of a Hamiltonian system in notions of Poisson geometry, Lie algebras and symmetry groups and first integrals. In this way, all collected data and the variables are taken into account in their actual role in the Hamiltonian system without any limitation on their number and dimensions. Also, the Hamiltonian system obtained can be reduced by symmetry concepts of Lie algebras, which result in the exact solution of the initial optimal problem. In addition, it can be converted to Lagrangian and vice versa. The proposed approach applies to the mathematical models describing the production of biomass and lignocellulolytic enzymes, consumption of the lignocellulosic matrix, fermentation model of the Tequila production process, and the laccase production. Ultimately, a comparison between the approximate method for producing laccase using the response surface methodology and the proposed analytical method has been made.

Modeling of exo-inulinase biosynthesis by Kluyveromyces marxianus in fed-batch mode: correlating production kinetics and metabolic heat fluxes

A metabolic heat-based model was used for estimating the growth of Kluyveromyces marxianus, and the modified Luedeking-Piret kinetic model was used for describing the inulinase production kinetics. For the first time, a relationship was developed to relate inulinase production kinetics directly to metabolic heat generated, which corroborated well with the experimental data (with R ² values of above 0.9). It also demonstrated the predominantly growth-associated nature of the inulinase production with Luedeking-Piret parameters α and β, having values of 0.75 and 0.033, respectively, in the exponential feeding experiment. MATLAB was used for simulating the inulinase production kinetics which demonstrated the model's utility in performing real-time prediction of inulinase concentration with metabolic heat data as input. To validate the model predictions, a biocalorimetric (Bio RC1e) experiment for inulinase production by K. marxianus was performed. The inulinase concentration (IU/mL) values acquired from the model in were validated with the experimental values and the metabolic heat data. This modeling approach enabled the optimization, monitoring, and control of inulinase production process using the real-time biocalorimetric (Bio RC1e) data. Gas chromatography and mass spectrometry analysis were carried out to study the overflow metabolism taking place in K. marxianus inulinase production.

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.

Optimal control analysis of the dynamic growth behavior of microorganisms

Understanding the growth behavior of microorganisms using modeling and optimization techniques is an active area of research in the fields of biochemical engineering and systems biology. In this paper, we propose a general modeling framework, based on Monod model, to model the growth of microorganisms. Utilizing the general framework, we formulate an optimal control problem with the objective of maximizing a long-term cellular goal and solve it analytically under various constraints for the growth of microorganisms in a two substrate batch environment. We investigate the relation between long term and short term cellular goals and show that the objective of maximizing cellular concentration at a fixed final time is equivalent to maximization of instantaneous growth rate. We then establish the mathematical connection between the generalized framework and optimal and cybernetic modeling frameworks and derive generalized governing dynamic equations for optimal and cybernetic models. We finally illustrate the influence of various constraints in the cybernetic modeling framework on the optimal growth behavior of microorganisms by solving several dynamic optimization problems using genetic algorithms.

Bioprocess systems engineering: transferring traditional process engineering principles to industrial biotechnology

The complexity of the regulatory network and the interactions that occur in the intracellular environment of microorganisms highlight the importance in developing tractable mechanistic models of cellular functions and systematic approaches for modelling biological systems. To this end, the existing process systems engineering approaches can serve as a vehicle for understanding, integrating and designing biological systems and processes. Here, we review the application of a holistic approach for the development of mathematical models of biological systems, from the initial conception of the model to its final application in model-based control and optimisation. We also discuss the use of mechanistic models that account for gene regulation, in an attempt to advance the empirical expressions traditionally used to describe micro-organism growth kinetics, and we highlight current and future challenges in mathematical biology. The modelling research framework discussed herein could prove beneficial for the design of optimal bioprocesses, employing rational and feasible approaches towards the efficient production of chemicals and pharmaceuticals.

Use of fruit residues for pectinase production by Aspergillus flavipes FP-500 and Aspergillus terreus FP-370

AIMS

Utilization of fruit residues for pectinase production by two Aspergillus strains for recognizing the effects of some factors during fermentation and describing enzyme production kinetics.

METHODS AND RESULTS

Pectinase production on several fruit residues was compared. The effects of three factors on the production of several pectinases were evaluated by a full factorial 2(k) experimental design. Higher activities were obtained on lemon peel. In both strains, acidic pH values and high carbon source concentration favoured exopectinase and endopectinase production, while higher pH values and low carbon source concentration promoted pectin lyase and rhamnogalacturonase production. Unstructured mathematical modelling provided a good description of pectinase production in a submerged batch culture.

CONCLUSIONS

Fruit residues were very good substrates for pectinase production, and Aspergillus strains used showed a promising performance in submerged fermentation. Mathematical modelling was useful to describe growth and pectinase production.

SIGNIFICANCE AND IMPACT OF THE STUDY

Lemon peel can be used as a substrate to obtain high pectinase titres by Aspergillus flavipes FP-500 and Aspergillus terreus FP-370. The factors that contributed to improve the yield were identified, which supports the possibility of using this substrate in the industrial production of these enzymes.

Crystal ball - 2011

In this feature, leading researchers in the field of microbial biotechnology speculate on the technical and conceptual developments that will drive innovative research and open new vistas over the next few years.

Good modeling practice for PAT applications: propagation of input uncertainty and sensitivity analysis

The uncertainty and sensitivity analysis are evaluated for their usefulness as part of the model-building within Process Analytical Technology applications. A mechanistic model describing a batch cultivation of Streptomyces coelicolor for antibiotic production was used as case study. The input uncertainty resulting from assumptions of the model was propagated using the Monte Carlo procedure to estimate the output uncertainty. The results showed that significant uncertainty exists in the model outputs. Moreover the uncertainty in the biomass, glucose, ammonium and base-consumption were found low compared to the large uncertainty observed in the antibiotic and off-gas CO(2) predictions. The output uncertainty was observed to be lower during the exponential growth phase, while higher in the stationary and death phases - meaning the model describes some periods better than others. To understand which input parameters are responsible for the output uncertainty, three sensitivity methods (Standardized Regression Coefficients, Morris and differential analysis) were evaluated and compared. The results from these methods were mostly in agreement with each other and revealed that only few parameters (about 10) out of a total 56 were mainly responsible for the output uncertainty. Among these significant parameters, one finds parameters related to fermentation characteristics such as biomass metabolism, chemical equilibria and mass-transfer. Overall the uncertainty and sensitivity analysis are found promising for helping to build reliable mechanistic models and to interpret the model outputs properly. These tools make part of good modeling practice, which can contribute to successful PAT applications for increased process understanding, operation and control purposes.

Matrix notation for efficient development of first-principles models within PAT applications: integrated modeling of antibiotic production with Streptomyces coelicolor

A matrix notation coupled to macroscopic principles is introduced as a means to develop first- principles models in an efficient and structured way within PAT applications. The notation was evaluated for developing an integrated biological, chemical (pH modeling) and physical (gas-liquid exchange) model for describing antibiotic production with Streptomyces coelicolor in batch fermentations. The model provided statistically adequate fits to all the monitored macroscopic biological, chemical and physical data of the process, except the phosphate uptake dynamics. This phosphate discrepancy is hypothesized to result from the internal storage of phosphate as polyphosphate prior to the exponential growth phase. The antibiotic production was associated with the stationary phase and its kinetics was adequately described using a modified Luedeking-Piret equation. Further, the maintenance was best described by employing a combination of Pirt and Herbert models, a result that was supported by a model-based hypothesis testing. Overall the process knowledge currently incorporated in the model is believed to be useful both for process optimization purposes and for further testing of hypotheses aiming at improving the mechanistic understanding of antibiotic production with S. coelicolor. Last but not least, the matrix notation is believed to be a promising supporting tool for efficient development and communication of complex dynamic models within a PAT framework.