Butyrylcholinesterase from chicken brain is smaller than that from serum: its purification, glycosylation, and membrane association.

Applying a new four-step isolation procedure, we have purified butyrylcholinesterase (BChE) from chicken serum to homogeneity with more than 250 U/mg specific activity. The serum enzyme was used for producing monoclonal antibodies. These BChE-specific also recognize BChE from brain, and thus enabled us to isolate the enzymes from embryonic and adult brain that occur only in minute amounts. More than 50% of the brain BChE is membrane-bound. The catalytic and inhibition properties of brain BChE are similar to those of serum BChE. However on sodium dodecyl sulfate-polyacrylamide gel electrophoresis, the serum enzyme is represented by a double-band of 79/82 kDa, whereas the brain enzyme has a size of 74 kDa. Limited digestion of the serum and brain preparations by V8-protease leads to similar peptide patterns. Enzymatic deglycosylation shows that their core proteins consist of 59-kDa subunits and that the different molecular weights are due to different glycosylation patterns. The differently sized glycosylation parts of brain and serum BChE may indicate that they subserve different functions. Furthermore, the membrane-bound brain BChE can be solubilized by Pronase or protease K, but not by phosphatidylinositol-specific phospholipase C

Application of the wavelet image analysis technique to monitor cell concentration in bioprocesses

The growth of cells of great practical interest, such as, the filamentous cells of bacterium Streptomyces clavuligerus, the yeast Saccharomyces cerevisiae and the insect Spodoptera frugiperda (Sf9) cell, cultivated in shaking flasks with complex media at appropriate temperatures and pHs, was quantified by the new wavelet transform technique. This image analysis tool was implemented using Matlab 5.2 software to process digital images acquired of samples taken of these three types of cells throughoot their cultivation. The values of the average wavelet coefficients (AWCs) of simplified images were compared with experimental measurements of cell concentration and with computer-based densitometric measurements. AWCs were shown to be directly proportional to measurements of cell concentration and to densitometric measurements, making evident the great potential of the wavelet transform technique to quantitatively estimate the growth of several types of cells