John Hubble

Estimation of parameters for cell-surface interactions : Maximum binding force and detachment constant

A convenient model is presented which can be used to quantify the relationship between applied shear and attached cell fraction in cell/surface interaction studies. The model uses two parameters (the shear stress required to detach the total attached cell population and a detachment constant) based on the estimated strength of the cell/bead interaction force. Use of these parameters allows results obtained on different systems to be compared. The model has been applied to data from three systems. 1) The effects of shear on the interaction between anti-goat IgG-coated beads and surface immobilized goat IgG;1 2) The effect of applying fluid shear stress to a stable fraction of attached 3T3 fibroblast cells on glass;2 and 3) The interaction of suspended yeast cells with surface-immobilized concanavalin A which is reported here. In the yeast system, the model provided a convenient aid for quantifying the effect of competing glucose on the interaction strength where it was found that the detachment constant for yeast interaction with surface-bound conA increases with the glucose concentration while the maximum shear stress and the binding force between the yeast cells and conA decreases.

Affinity cell separations: problems and prospects

The use of biospecific interactions for the separation and recovery of biomolecules is widely established, but developments in affinity-based separations for cell fractionation have been slow. Many of the problems encountered result from applying techniques developed for molecular systems to cell separation with only minor modification to the conditions. This approach tends to ignore, or at least trivialize, the problems that arise from the heterogeneous nature of a cell suspension and the implications of cooperativity that can occur with multivalent interactions. This article considers how alternative protocols might be used to develop more attractive cell-separation processes.

Thermal monitoring of phenoxyacid herbicide adsoprtion on granular activated carbon

Abstract A thermal detection technique, which is based on monitoring the effects of a partial desorption of adsorbed material resulting from an applied heat pulse, has been used to follow the adsorption of phenoxyacid herbicides (MCPA, MCPP, and MCPB) on a carbon packed column. Results obtained show that this approach allows effective prediction of single component breakthrough using a single-sensor configuration and an artificial neural network for signal interpretation. However, the integration of a multiple-sensor array using a modified neural network was found to give improved performance. Although this work has focused mainly on single-solute systems, preliminary results are presented which demonstrate the potential for monitoring binary-solute loadings.

A neural network for breakthrough prediction in packed bed adsorption

A single hidden layer back propagation neural network has been used to predict the occurrence of breakthrough in an ion-exchange adsorption column using signals derived from a thermal monitoring system. After training the neural network was capable of a complete prediction of breakthrough. This is in contrast with the mechanistic models used to date, which all show significant deviations in one or more regions of the breakthrough response.

Bubble‐induced detachment of affinity‐adsorbed erythrocytes

It is desirable that cells adsorbed in affinity‐separation processes be easily recovered from the adsorption surface, without excessive dilution, once contaminants have been removed. The present study investigates the use of gas‐bubble‐induced shear stress for the recovery of affinity‐adsorbed human erythrocytes. This method has previously been demonstrated to be effective with yeast cells, where it allows cells to be attached, washed and detached under isocratic conditions. Concanavalin A (Con A), used as the binding agent, was attached to the inside of nylon tubes. Whole blood solution, diluted to an erythrocyte concentration of 1×108·ml−1 with PBS, was incubated with the Con A–nylon surface and then washed with PBS prior to elution. To effect elution, air bubbles of known volume were introduced to the buffer feed to the tubes and the effects of bubble size, bubble volume and bubble velocity on detachment being determined. The results obtained showed that the most significant parameter was bubble number, with up to 90% of attached cells being recovered using a five‐bubble sequence. Microscopic examination showed no evidence of mechanical damage to the detached cells.

The kinetics of affinity-mediated cell-surface attachment

Data and a semi-empirical model are presented that describe the affinity interaction of yeast cells with a Concanavalin A derivatised surface. The model uses 3 parameters to describe the time course of cell attachment from a flowing suspension of yeast cells, over a range of flow rates, and gives an effective global fit to the data obtained. Further modifications allow the effects of a soluble competitor (glucose) on binding to be quantified in terms of a saturation effect, and an effective global fit is obtained. A comparison was made between the relationship between steady-state attached fraction and applied shear with similar data reported earlier (Ming, F. et al, 1998) for the detachment of pre-adsorbed cells. This shows that there is an order of magnitude difference between the forces required to effect complete detachment in the two systems, and that the nature of the relationship between shear and attached fraction is profoundly different. The magnitude of this time-dependent stabilization might be explained in terms of a progressive reorientation of cell relative to the surface such that the number of bonds is maximized.

A model of multivalent ligand-receptor equilibriawhich explains the effect of multivalent binding inhibitors

Quantitative relationships based on multivalent ligand receptor binding equilibria are developed which can describe the enhanced binding observed when polyvalent ligands are used as inhibitors of cell/cell interactions. This theory is able to explain the many orders of magnitude difference reported between the apparent dissociation constants determined for the interaction of Entamoeba histolytica membrane receptors with mono and multivalent N-Acetylgalactosaminide inhibitors. Given two experimentally accessible constants the theory provides a framework for the quantitative evaluation of custom designed polyvalent inhibitors of lectin and antibody mediated interactions.

A Neural Network Model for Prediction of Binary Adsorption Using Single Solute and Limited Binary Solute Adsorption Data

Abstract A simple neural network model was used to predict binary solute adsorption onto granular activated carbon (GAC). While some data on binary adsorption were required, the neural network could be effectively trained using predominately single solute adsorption data, and only a limited number of data sets (<10) were necessary for effective performance. Once trained, the network was capable of predicting binary solute adsorptions even for systems showing nonideality.

Optimisation of frontal chromatography by partial loading

Abstract Quantitative assessment of adsorbate losses during washing is used to provide the basis for a new approach to optimising the performance of packed-bed adsorption chromatography. This paper presents this new approach, and shows, through simulating the performance of the adsorption and washing processes how it can be used with a variety of performance criteria. These include: maximum use of column capacity, minimum product loss and maximum process throughput. The results show that for product loss to be minimised, it is advantageous to stop adsorption before column breakthrough is detected, in order to leave unused capacity capable of scavenging unadsorbed material and product eluted during the washing process. The effect of changes in axial dispersion, length of column loading, inherent adsorbent capacity and adsorption rate or mass transfer are analysed and discussed with respect to optimising the point at which washing is started. It is shown that the application of the new approach can improve column performance significantly and minimise waste without any serious consequence on column capacity utilisation and process throughput.

A simple model for predicting the performance of affinity chromatography columns

This paper presents a simple model for affinity chromatography, the approach used is based on the equilibrium stage model introduced by Martin and Synge (1941). The current development eliminates the need for an equilibrium assumption by using a simplified rate equation to describe the adsorption process. Although it is not mathematically rigorous this method has proved useful for the design of column experiments in our laboratory.