Antimicrobial peptides and complement in neonatal hypoxia-ischemia induced brain damage

Hypoxic-ischemic encephalopathy (HIE) is a clinical condition in the neonate, resulting from oxygen deprivation around the time of birth. HIE affects 1-5/1000 live births worldwide and is associated with the development of neurological deficits, including cerebral palsy, epilepsy, and cognitive disabilities. Even though the brain is considered as an immune-privileged site, it has innate and adaptive immune response and can produce complement (C) components and antimicrobial peptides (AMPs). Dysregulation of cerebral expression of AMPs and C can exacerbate or ameliorate the inflammatory response within the brain. Brain ischemia triggers a prolonged inflammatory response affecting the progression of injury and secondary energy failure and involves both innate and adaptive immune systems, including immune-competent and non-competent cells. Following injury to the central nervous system (CNS), including neonatal hypoxia-ischemia (HI), resident microglia, and astroglia are the main cells providing immune defense to the brain in a stimulus-dependent manner. They can express and secrete pro-inflammatory cytokines and therefore trigger prolonged inflammation, resulting in neurodegeneration. Microglial cells express and release a wide range of inflammation-associated molecules including several components of the complement system. Complement activation following neonatal HI injury has been reported to contribute to neurodegeneration. Astrocytes can significantly affect the immune response of the CNS under pathological conditions through production and release of pro-inflammatory cytokines and immunomodulatory AMPs. Astrocytes express β-defensins, which can chemoattract and promote maturation of dendritic cells (DC), and can also limit inflammation by controlling the viability of these same DC. This review will focus on the balance of complement components and AMPs within the CNS following neonatal HI injury and the effect of that balance on the subsequent brain damage

A new representation in evolutionary algorithms for the optimization of bioprocesses

Evolutionary Algorithms (EAs) have been used to achieve optimal feedforward control in a number of fed-batch fermentation processes. Typically, the optimization purpose is to set the optimal feeding trajectory, being the feeding profile over time given by a piecewise linear function, in order to reduce the number of parameters to the optimization algorithm. In this work, a novel representation scheme for the encoding of the feeding trajectory over time is proposed. Each gene in the variable sized chromosome has two components: a time label and the real value of the variable. The new approach is compared with a traditional real-valued EA, with chromosomes of constant size and fixed discretization steps. Three distinct case studies are presented, taken from previous work from the authors and literature, all considering the optimization of fed-batch fermentation processes. The experimental results show that the proposed approach is capable of results better or at the same level of quality of the best traditional EAs and is able to automatically evolve the best discretization steps for each case, thus simplifying the EA's setup.Fundação para a Ciência e Tecnologia (FCT) - 59899/EIA/POSC/2004

Model-based adaptive control of acetate concentration during the production of recombinant proteins with E. coli

A model-based adaptive linearizing control law was derived for the regulation of the acetate concentration during the fed-batch fermentation of recombinant proteins with high cell density culture of Escherichia coli growing on glucose. An unstructured model for the growth was applied to the major metabolic pathways: oxidative growth on glucose, fermentative growth on glucose, oxidative growth on acetate, and maintenance. A model order reduction method was used to allow the development of the control algorithm without the knowledge of the kinetic structure being necessary. The non-linear model was subjected to transformations in order to obtain a linear behaviour for the control loop when a non-linear control is applied. The control law requires on-line acetate and carbon dioxide and oxygen transfer rates measurements. Acetate measurements are achieved with a developed Flow Injection Analysis (FIA) physical-chemical method. The gas transfer rates are calculated from gas analysis data obtained with a Mass Spectrometer (MS) connected to the exhaust gas line of the fermenter and also to the inlet aeration line. These calculations, as well as the implementation of the control law were performed through a MATLAB script embedded in a LABView program that also acquired data from the FIA system and other relevant state variables from the fermenter Digital Control Unit. Copyright 2002 IFACAgência de Inovação - PROTEXPRESS.Fundação para a Ciência e a Tecnologia (FCT) – PRAXIS XXI/BD/16961/98

Optimisation Methods for Improving Fed-batch Cultivation of E. Coli Producing Recombinant Proteins

Two optimisation techniques for the fed-batch cultivation of high cell density Escherichia coli producing recombinant proteins were compared. An unstructured model for the growth, based on the General State Space Dynamical Model [1] was used to represent the four major metabolic pathways: oxidative growth on glucose, fermentative growth on glucose, oxidative growth on acetate, and maintenance. The dilution rate (dependent on the substrate feed rate) was chosen as the input variable. Recombinant protein production is known to be proportional, in our system, to the biomass concentration. Thus, biomass productivity was chosen as the criterion to be maximized. The two methods compared were a first order gradient method based on Pontryagin’s minimum principle and a stochastic method based on the biological principle of natural evolution, using a genetic algorithm. The former method revealed less efficient concerning to the computed maximum, and dependence on good initial values

On-line calculation of CTR and OTR during high-cell density recombinant E. coli fed-batch fermentation: MS calibration, on-line data acquisition, analysis and integration

During a high-cell density fed-batch fermentation of recombinant E. coli, both oxygen and carbon dioxide transfer rates (OTR and CTR) were calculated on-line from inlet and exhaust gas composition measurements obtained with Mass Spectrometry (MS) and from the culture weight. These rates, together with on-line measurements of acetate concentration by Flow Injection Analysis, were used to implement an adaptive control law in a real fermentation. For MS calibration, a new method was adapted, where several gas mixtures were used, their composition being chosen from the analysis of the expected experimental space. A calibration factor was then calculated by linear regression that correlated the pressure values obtained in the MS for a given mass to charge ratio with the mixture composition in oxygen, carbon dioxide and nitrogen. During the fermentation, 12 MS and weight data points (corresponding to approximately 3 minutes) were acquired in a developed LabVIEW subroutine where a C embedded window performed data analysis by statistical significance assessment to exclude potential outliers. Afterwards, the noise was partially eliminated by applying a moving average filter and MS raw data was converted to molar fractions, according to the calculated calibration factors. CTR and OTR values are then computed from inlet and exhaust gas composition and reactor weight. This LabVIEW subroutine was then integrated in a supervisory programme, together with the measurements of other equipments, acquired by serial ports or analog input and using string interpretation or the standard Windows Dynamic Data Exchange (DDE) protocol

On-line monitoring of glucose and acetate during high-cell density fermentations of Escherichia coli with a flow injection analysis system

A system based on Flow Injection Analysis (FIA) for the on-line monitoring and data acquisition of acetate and glucose concentrations in the liquid phase during high cell density fed-batch fermentations of recombinant E. coli was developed. Retrieval of liquid medium samples free of biomass and suspended particles is obtained by on-line filtration of the fermentation culture using an external unit, composed of a peristaltic pump and a tangential filtration device. The measurement of acetate is based on the diffusion of that volatile compound through a gas-diffusion chamber into a stream ontaining an acid-base indicator. The subsequent decrease in the absorbance is detected with an incorporated photometer. After method optimization, it was possible to achieve linearity until 10 g/L without needing a dilution step and with a sensibility of 0.05 g/L. No significant interferences were detected when compared with other methods. Commercially packed Glucose Oxidase is used in the amperometric measurement of glucose. The method is linear until 5 g/L and it is possible to detect concentrations of less than 0.1 g/L. The FIA system is coupled with a computer equipped with appropriate software that continuously writes data in a file. These data are then accessed via network by the supervisor computer running a programme developed in Labview environment. This software allows the development of control actions based on the concentration of the two compounds, together with on-line information from exit gas measurements using mass spectrometry, on-line weight readings from two balances (one for the fermenter and the other for the feeding substrate), and other state variables acquired from the digital control unit coupled to the fermenter. Several fed-batch fermentations with recombinant E. coli were conducted with success using the system described. The measurement ranges revealed adequate without needing a dilution step and the filtration system was stable even at high cell densities (more than 55 g/L of biomass)

Measurement of acetate during the production of recombinant proteins with E. coli

Acetate is known to be the major by-product during fermentation of recombinant E. coli. Among the consequences of that production, the more important are the decrease of the biomass yield for a given carbon source, the inhibition of the growth when acetate is present at high concentrations (typically 10 g/L) and the decrease of the production of recombinant proteins. For these reasons, its accurate and fast measurement is a very important issue when trying to achieve high productivities in this kind of processes. A method based on Flow Injection Analysis (FIA) was then adapted and optimized for the on-line monitoring of fermentations of recombinant E. coli. The method is based on the pre-acidification of the sample with sulfuric acid followed by the diffusion of the acetate into a stream containing an acid-base indicator through a hydrophobic membrane. The decrease in the absorbance of the acid-base indicator at 560 nm is proportional to the concentration of acetate and is measured with a photometer for that wavelength. The composition of the indicator was studied in order to achieve a compromise between stability and sensitivity of the method. Several solutions are proposed, depending on the concentration range of acetate to be measured. It was possible to achieve linearity until 10 g/L of acetate with a sensibility of less than 0.1 g/L. The correlation between acetate measured with FIA and with other methods (HPLC and enzymatic kit from R-Biopharm) is also acceptable, the differences never exceeding 20%. The method is very reproducible, being the averaged relative standard deviations around 2% for 20 replicates of the same sample. The method is also very fast, being the sampling rate of 30 hˉ¹.Fundação para a Ciência e a Tecnologia (FCT) - PRAXIS XXI/BD/16961/98

Yield and kinetic parameters estimation and model reduction in a recombinant E. coli fermentation

A genetic algorithm was used to estimate both yield and kinetic coefficients of an unstructured model representing a high-cell density fermentation of E. coli. The model is composed of mass balance equations with 3 states: Biomass, Glucose, and Acetate. Kinetic equations are based on the 3 main metabolic pathways of the microorganism: glucose oxidation, fermentation of glucose and acetate oxidation. Genetic Algorithms were used to minimize the normalized quadratic differences between simulated and real values of the state variables, by manipulating both yield and kinetic coefficients. Data from real fed-batch fermentation runs were analyzed with this optimization routine, the new parameter set obtained allowing a much better description of the process behaviour when compared to simulations conducted with non-optimized parameters obtained from literature. After parameter estimation, a sensitivity function analysis was applied to evaluate the influence of the various parameters on the state variables biomass, acetate, and glucose. Thus, essential parameters were selected and the model was re-written in a more simplified form that could also describe accurately experimental data

On-line simultaneous monitoring of glucose and acetate with FIA during high cell density fermentation of recombinant E. coli

A two-channel flow injection analysis (FIA) system was developed for the simultaneous on-line monitoring of acetate and glucose during high cell density fed-batch fermentations of recombinant Escherichia coli. Acetate measurement was performed with a modified and optimised version of an existing method, based on acetate diffusion through a gas-diffusion chamber into a stream containing an acid–base indicator. The subsequent decrease in the absorbance was detected with an incorporated photometer. After method optimisation, it was possible to achieve linearity until 10 g/kg with no dilution step and with a detection level of 0.05 g/kg. Although some interferences were found, the performance of the method proved to be sufficiently reliable for on-line control purposes Commercially packed glucose oxidase (GOD) was used for the amperometric measurement of glucose. The method was linear up to 5 g/kg and it was possible to detect concentrations lower than 0.06 g/kg. For these measurements, no significant interferences were detected when the results were compared with other reference methods. The application of a simultaneous parallel configuration of the methods to a high cell density fed-batch E. coli fermentation was tested and reliable results were obtained within a 3 min delay. This information was made available to a supervisory computer running a developed LabVIEWTM programme via an Ethernet network, allowing the immediate implementation of control actions, improving the process performance