Quasichemical models of dynamics of cell populations after treatment with growth inhibitors and activators]

A uniform procedure is proposed, whereby growth characteristics of biological populations of various levels can be described as quantum chemistry equations. Using approaches of the kinetics of chain processes expressions have been derived, which make it possible to assess the effects of individual chemical substances and mixtures thereof on population dynamics. These expressions describe quantitatively synergistic and antagonistic effects of the substances. The models proposed describe the kinetics of growth of various populations (such as cultures of microorganisms) and can serve as a basis for targeted regulation of biotechnological processes.     

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.     

Enzyme Kinetics for Complex System Enables Accurate Determination of Specificity Constants of Numerous Substrates in a Mixture by Proteomics Platform

Many important experiments in proteomics including protein digestion, enzyme substrate screening, enzymatic labeling, etc., involve the enzymatic reactions in a complex system where numerous substrates coexists with an enzyme. However, the enzyme kinetics in such a system remains unexplored and poorly understood. Herein, we derived and validated the kinetics equations for the enzymatic reactions in complex system. We developed an iteration approach to depict the enzymatic reactions in complex system. It was validated by 630 time-course points from 24 enzymatic reaction experiments and was demonstrated to be a powerful tool to simulate the reactions in the complex system. By applying this approach, we found that the ratio of substrate depletion is independent of other coexisted substrates under specific condition. This observation was then validated by experiments. Based on this striking observation, a simplified model was developed to determine the catalytic efficiencies of numerous competing substrates presented in the complex enzyme reaction system. When coupled with high-throughput quantitative proteomics technique, this simplified model enabled the accurate determination of catalytic efficiencies for 2369 peptide substrates of a protease by using only one enzymatic reaction experiment. Thus, this study provided, in the first time, a validated model for the large scale determination of specificity constants which could enable the enzyme substrate screening approach turned from a qualitative method of identifying substrates to a quantitative method of identifying and prioritizing substrates. Data are available via ProteomeXchange with identifier PXD004665.     

Dynamics of the Ethanolamine Glycerophospholipid Remodeling Network

Acyl chain remodeling in lipids is a critical biochemical process that plays a central role in disease. However, remodeling remains poorly understood, despite massive increases in lipidomic data. In this work, we determine the dynamic network of ethanolamine glycerophospholipid (PE) remodeling, using data from pulse-chase experiments and a novel bioinformatic network inference approach. The model uses a set of ordinary differential equations based on the assumptions that (1) sn1 and sn2 acyl positions are independently remodeled; (2) remodeling reaction rates are constant over time; and (3) acyl donor concentrations are constant. We use a novel fast and accurate two-step algorithm to automatically infer model parameters and their values. This is the first such method applicable to dynamic phospholipid lipidomic data. Our inference procedure closely fits experimental measurements and shows strong cross-validation across six independent experiments with distinct deuterium-labeled PE precursors, demonstrating the validity of our assumptions. In constrast, fits of randomized data or fits using random model parameters are worse. A key outcome is that we are able to robustly distinguish deacylation and reacylation kinetics of individual acyl chain types at the sn1 and sn2 positions, explaining the established prevalence of saturated and unsaturated chains in the respective positions. The present study thus demonstrates that dynamic acyl chain remodeling processes can be reliably determined from dynamic lipidomic data.     

Transport and kinetic processes underlying biomolecular interactions in the BIACORE optical biosensor

The transport and kinetic processes describing biomolecular interactions in the BIACORE optical biosensor have been studied with the help of a mathematical model. In comparison to previous models, the model presented here couples, for the first time, transport phenomena in the flow channel with hindered diffusive transport and reactions inside the hydrogel. Simulated experiments based on this model, and two simpler models extant in the literature, are used to identify cases under which the detailed model is essential for accurate prediction of kinetic parameters. It is shown that this model can substantially improve the accuracy of kinetic parameter estimation when transport limitations in the flow channel and/or the hydrogel significantly influence the observed instrument response curves. The model can extend the range of the instrument's applicability to higher concentrations of immobilized species within the hydrogel. It can also be used for accurate design of experiments with the purpose of minimizing errors in the estimation of the kinetic parameters.     

Determination of elasticities, concentration and flux control coefficients from transient metabolite data using linlog kinetics

This paper presents a practical approach to estimate the kinetic parameters of a metabolic network from in vivo kinetics experiments. This method is based on the linlog kinetics format (Visser and Heijnen, 2003, Metab. Eng. 5(3), 164-176; Wu et al., 2004, Eur. J. Biochem. 271, 3348-3359), of which the kinetic parameters, called elasticities, are estimated by an iterative linear optimization followed by non-linear optimization, from transient metabolite concentration data which are directly obtainable from rapid pulse experiments. In this way, not only the parameters are estimated but also a full kinetic model, based on linlog kinetics, is developed. The obtained elasticities also allow immediate calculation of all control coefficients. As an in silico case study, the estimation of elasticities of a linear pathway is presented. The method is shown to be able to estimate the elasticities quite accurately and to be robust toward errors in the metabolite data originating from sampling and measurement inaccuracy. The method allows experimental redesign to get more accurate estimated parameters and accommodates various types of experimentally applied disturbances in the pathway: changes in independent metabolites, dependent metabolites or enzyme levels/activities.     

Aggregation and disaggregation kinetics of human blood platelets: Part I. Development and validation of a population balance method.

Hydrodynamic shear stress of sufficient intensity is known to cause platelet activation and aggregation and to alter the effects of biochemical platelet agonists and antagonists. In this work, a population balance equation (PBE) model is developed for analysis of platelet aggregation and disaggregation kinetics under the influence of a shear field. The model incorporates both aggregation and disaggregation by splitting and/or erosion mechanisms. This paper, the first of a series of three, deals with the formulation, simplification, and validation of the PBE and with the estimation of parameters involved in the PBE. These population parameters include collision efficiency, void fraction (related to the particle collision diameter), and the breakage rate coefficient. The platelet particle size distribution is determined experimentally, both initially and at some later times. The PBE can then be used to match satisfactorily the observed particle histograms, by appropriate choice of parameters of the model as functions of time, platelet size, and magnitude of physical or chemical stimuli. Besides providing information on adhesive forces and on the rates of aggregation and disaggregation, these parameters infer the physical properties of platelets and platelet aggregates. These properties are of potential value in increasing our understanding of the processes involved in thrombotic disease and/or therapy. A numerical procedure for solving the PBE is validated by application to simple cases for which analytical solutions are available. The model is applied to analysis of experiments, and parameter sensitivity studies are used to order the importance of the parameters and to reduce the complexity of the model. The simplified model is shown to give good agreement with experimental observations.     

On-line optimization of biotechnological processes: I. Application to open algal pond

A new on-line optimization and control procedure applicable to biotechnological systems for which a precise mathematical model is unavailable has been developed and tested. The proposed approach is based on an online search for optimum operating conditions by an automatic system using a modified simplex algorithm to which several features have been added to permit real time operation. The simplex algorithm is the upper level of a hierarchical software package in which the other levels are cost evaluation, control, data acquisition, and signal processing. The optimization method was tested in a laboratory minipond for the cultivation of Spirulina platensis. The controlled parameters were light intensity, optical density, pH, and temperature. The proposed optimization method can be applied to other biological processes provided that the pertinent variables can be measured and controlled and the cost function can be defined mathematically.     

Development of a novel membrane aerated hollow-fiber microbioreactor

A new challenge in biotechnological processes is the development of flexible bioprocessing platforms, allowing strain selection, facilitating scale-up and integrating separation steps. Miniaturization of such a cultivation system allows parallel use and the saving of resources but makes the supply of oxygen to the cells difficult. In this work we present a membrane aerated hollow-fiber microbioreactor (HFMBR) which consists of an acrylic glass module equipped with two different types of membrane fibers. Fibers of polyethersulfone and polyvinyldifluoride were used for substrate and oxygen supply, respectively. Cultivation of E. coli as model organism and production of His-tagged GFP were carried out in the extracapillary space of the membrane aerated HFMBR and compared with cultivations in shaking flask which are commonly used for screening experiments. The measurement of the oxygen transfer capacity and the online monitoring of the dissolved oxygen during the cultivation were performed using a fiber optic oxygen sensor. Online measurement of the optical density was also integrated to the bioreactor. Due to efficient oxygen transfer, a better cell growth than in the shaking flask experiments was achieved, while no negative influence on the GFP productivity was observed in the membrane aerated bioreactor. Thus the feasibility of a future integrated downstreaming could also be demonstrated.     

Microbial production of enzymes: Nonlinear state and kinetic reaction rates estimation

The nonlinearity of the biotechnological processes and the absence of cheap and reliable instrumentation require an enhanced modelling effort and estimation strategies for the state and the kinetic parameters. This work approaches nonlinear estimation strategies for microbial production of enzymes, exemplified by using a process of lipase production from olive oil by Candida rugosa. First, by using a dynamical mathematical model of this process, an asymptotic observer which reconstructs the unavailable state variables is proposed. The design of this kind of observers is based on mass and energy balances without the knowledge of kinetics being necessary; only minimal information concerning the measured concentrations is used. Second, a nonlinear high-gain observer is designed for the estimation of imprecisely known kinetics of the bioprocess. An important advantage of this high-gain estimator is that the tuning is reduced to the calibration of a single parameter. Numerical simulations in various scenarios are provided in order to test the behaviour and performances of the proposed nonlinear estimation strategies.     

Kinetics and Yields of Pesticide Biodegradation at Low Substrate Concentrations and under Conditions Restricting Assimilable Organic Carbon

The fundamentals of growth-linked biodegradation occurring at low substrate concentrations are poorly understood. Substrate utilization kinetics and microbial growth yields are two critically important process parameters that can be influenced by low substrate concentrations. Standard biodegradation tests aimed at measuring these parameters generally ignore the ubiquitous occurrence of assimilable organic carbon (AOC) in experimental systems which can be present at concentrations exceeding the concentration of the target substrate. The occurrence of AOC effectively makes biodegradation assays conducted at low substrate concentrations mixed-substrate assays, which can have profound effects on observed substrate utilization kinetics and microbial growth yields. In this work, we introduce a novel methodology for investigating biodegradation at low concentrations by restricting AOC in our experiments. We modified an existing method designed to measure trace concentrations of AOC in water samples and applied it to systems in which pure bacterial strains were growing on pesticide substrates between 0.01 and 50 mg liter⁻¹. We simultaneously measured substrate concentrations by means of high-performance liquid chromatography with UV detection (HPLC-UV) or mass spectrometry (MS) and cell densities by means of flow cytometry. Our data demonstrate that substrate utilization kinetic parameters estimated from high-concentration experiments can be used to predict substrate utilization at low concentrations under AOC-restricted conditions. Further, restricting AOC in our experiments enabled accurate and direct measurement of microbial growth yields at environmentally relevant concentrations for the first time. These are critical measurements for evaluating the degradation potential of natural or engineered remediation systems. Our work provides novel insights into the kinetics of biodegradation processes and growth yields at low substrate concentrations.     

Enhancing the feasibility of many biotechnological processes through enzyme deactivation studies

Enzymes are deactivated by different ways to an inactive state, which is a major constraint in the development of biotechnological processes. Understanding the complex process of enzyme deactivation will be helpful in enhancing the feasibility of many biological processes. This paper mainly deals with the different ways by which enzymes are inactivated, which includes the role of thermodynamics in deactivation. Different models namely, unified deactivation theory, single exponential model, rapid equilibrium model, isozyme model and bacterial contamination model used to describe the complex deactivation processes are also discussed in this communication. The complete understanding of deactivation process is very essential in commercialization because enzyme activity and stability of the enzyme play a critical role in economics of biotechnological processes. Activity and stability of the enzyme are conflicting properties and trade-off between these factors must be considered in the selection and design of enzymes.     

Chip devices for miniaturized biotechnology

Chip devices were introduced in chemistry and molecular biology to improve the read-out of information from molecular systems by efficient analytical procedures and to organize automated experiments. Biochips and chip reactor systems are of interest for cellular processes, too, and can be regarded as components in interfaces for the information exchange between living nature and digital electronic systems. In this minireview, different types of chip reactors for biotechnological applications like nanotiterplates, chip thermocyclers and devices for segmented flow operations are discussed. Finally, an outlook is given on the application of chip reactor systems, which are promising tools for automated experiments with highly parallelized screening procedures, for artificial microcompartmentation, cell analogue systems, micro-ecological studies, investigations on modulated morphogenesis, and for a bioanalogue molecular nanotechnology.     

Biodegradation kinetics of volatile hydrophobic organic compounds in cultures with variable fractional volumes

An extension of the models developed by Guha and Jaffé (Biotechnol Bioeng [1996] 50:693-699) to describe the phenanthrene biodegradation kinetics for the cultures with variable fractional volumes is presented. Batch experiments were conducted with a culture capable of degrading the phenanthrene using a single culture vessel from which samples were withdrawn over time to monitor the disappearance of phenanthrene. For accurate measurement of phenanthrene concentrations, a sampling procedure designed for quantifying the sorption of phenanthrene onto glassware was also introduced. The Monod parameters were estimated by nonlinear regression analyses of simultaneous solutions to the substrate utilization/volatilization and Monod equations for growth of the cell mass. The results demonstrate that the models were able to be extended to phenanthrene-degrading cultures with variable fractional volumes. When the ratio between sampling volume and volume of the culture medium was relatively small, the parameters obtained were similar to those which would be obtained using constant fractional volumes of culture medium. It was also found that the model's fit to the phenanthrene disappearance data in this study were better than those obtained by Guha and Jaffé, implying that the sorption process of phenanthrene during the sampling period could significantly affect the measurement of phenanthrene concentrations. Failing to account for these losses led to less accurate measurements of substrate concentrations, which in turn resulted in a poor estimation of the parameters. The findings of this study reduce considerably the experimental work necessary in the estimation of Monod kinetic parameters for the purpose of modeling.     

Comparison of screening methods for high-throughput determination of oil yields in micro-algal biofuel strains

The phenotypic and phylogenetic diversity of micro-algae capable of accumulating triacylglycerols provides a challenge for the accurate determination of biotechnological potential. High-yielding strains are needed to improve economic viability and their compositional information is required for optimizing biodiesel properties. To facilitate a high-throughput screening programme, a very rapid direct-derivatization procedure capable of extracting lyophilized material for GC analysis was compared with a scaled-down Folch-based method. This was carried out on ten micro-algal strains from 6 phyla where the more rapid direct-derivatization approach was found to provide a more reliable measure of yield. The modified Folch-based procedure was found to substantially underestimate oil yield in one Chlorella species (P?<?0.01). In terms of fatty acid composition however, the Folch procedure proved to be slightly better in recovering polyunsaturated fatty acids, in six out of the ten strains. Therefore, direct-derivatization is recommended for rapid determination of yields in screening approaches but can provide slightly less compositional accuracy than solvent-based extraction methods.     

Kinetic and thermodynamic properties of wild-type and engineered mutants of tyrosyl-tRNA synthetase analyzed by pyrophosphate-exchange kinetics.

The first step of the reaction catalyzed by the aminoacyl-tRNA synthetases is the formation of enzyme-bound aminoacyl adenylate. The steady-state kinetics of this step has conventionally been studied by measuring the rate of isotopic exchange between pyrophosphate and ATP. A simple kinetic analysis of the pyrophosphate-exchange reaction catalyzed by the tyrosyl-tRNA synthetase from Bacillus stearothermophilus is given in which all the observed rate and binding constants can be assigned to identifiable physical processes under a variety of limiting conditions. The free energies of binding to the enzyme of tyrosine, ATP, and the transition state for tyrosyl adenylate formation can be measured in relatively straightforward experiments. The excellent agreement between parameters measured in these experiments and those from earlier pre-steady-state kinetics confirms that the intermediates isolated in the presteady state are kinetically competent. The dissociation constant of ATP from the unligated enzyme, a constant that has previously been experimentally inaccessible, has been measured for wild-type and several mutant enzymes. The changes in enthalpy and entropy of activation on mutation have been measured by a rapid procedure for mutants that have altered contacts with tyrosine and ATP. Those mutants that have large changes of enthalpy and entropy of binding are likely to have structural changes and so warrant further examination by protein crystallography.     

Simulation of detachment of specifically bound particles from surfaces by shear flow.

The receptor-mediated adhesion of cells to ligand-coated surfaces is important in many physiological and biotechnological processes. Previously, we measured the detachment of antibody-coated spheres from counter-antibody- and protein A-coated substrates using a radial-flow detachment assay and were able to relate mechanical adhesion strength to chemical binding affinity (Kuo and Lauffenburger, Biophys. J. 65:2191-2200 (1993)). In this paper, we use "adhesive dynamics" to simulate the detachment of antibody-coated hard spheres from a ligand-coated substrate. We modeled the antibody-ligand (either counter-antibody or protein A) bonds as adhesive springs. In the simulation as in the experiments, beads attach to the substrate under static conditions. Flow is then initiated, and detachment is measured by the significant displacement of previously bound particles. The model can simulate the effects of many parameters on cell detachment, including hydrodynamic stresses, receptor number, ligand density, reaction rates between receptor and ligand, and stiffness and reactive compliance of the adhesive springs. The simulations are compared with experimental detachment data, thus relating measured bead adhesion strength to molecular properties of the adhesion molecules. The simulations accurately recreated the logarithmic dependence of adhesion strength on affinity of receptor-ligand recognition, which was seen in experiments and predicted by analytic theory. In addition, we find the value of the reactive compliance, the parameter which relates the strain of a bond to its rate of breakage, that gives the best match between theory and experiment to be 0.01. Finally, we analyzed the effect of varying either the forward or reverse rate constants as different ways to achieve the same affinity, and showed that adhesion strength depends uniquely on the equilibrium affinity, not on the kinetics of binding. Given that attachment is independent of affinity, detachment and attachment are distinct adhesive phenomena.     

Computersimulation der Trocknung biologischer Produkte

The extend of non-enzymatic browning and ascorbic acid loss during air drying of a slab are predicted by computer, utilizing moisture and temperature dependencies of reaction kinetics together with simulated data for either averaged moisture contents. Results show that the extend of quality loss is a function of the drying parameters. The computer model is useful for the optimization of quality retention during dehydration of biotechnological products and foods.