Changes in chymotrypsin hydrolysis of beta-lactoglobulin A induced by high hydrostatic pressure

Beta-lactoglobulin (beta-Lg) was subjected to high pressures up to 400 MPa and proteolysis with chymotrypsin. The hydrolysates were analyzed by SDS-PAGE and RP-HPLC, and the fragments obtained were identified by ESI-MS/MS. The results obtained showed that beta-Lg was hydrolyzed by chymotrypsin in a "progressive proteolysis" manner at either atmospheric or high pressure. Proteolysis during or after high-pressure treatment showed longer and more hydrophobic peptides than proteolysis at atmospheric pressure. Chymotrypsin showed a behavior similar to that of trypsin, with some differences, probably related to the orientation of the target residues specific for each enzyme. The similarities between proteolytic fragments produced by the two enzymes support that proteolysis enhancement under high pressure depends on the substrate changes rather than the enzyme. High pressure seemed to accelerate the first steps of proteolysis, probably through dimer dissociation, while leaving portions of the molecule more resistant to the enzyme.     

Unfolding and refolding of beta-lactoglobulin subjected to high hydrostatic pressure at different pH values and temperatures and its influence on proteolysis

The unfolding of beta-lactoglobulin during high-pressure treatment and its refolding after decompression were studied by 1H NMR and 2H/1H exchange at pH 6.8 and 2.5 and at 37 and 25 degrees C. The extent of unfolding increased with the pressure level. The structure of beta-lactoglobulin required higher pressures to unfold at pH 2.5 than at pH 6.8. More flexibility was achieved at 37 degrees C than at 25 degrees C. Results indicated that the structural region formed by strands F, G, and H was more resistant to unfold under acidic and neutral conditions. The exposure of Trp19 at an earlier time, as compared to other protein regions, supports the formation of a swollen structural state at pH 2.5. Refolding was achieved faster when beta-lactoglobulin was subjected to 200 MPa than to 400 MPa, to 37 degrees C than to 25 degrees C, and to acidic than to neutral pH. After treatment at 400 MPa for 20 min at neutral pH, the protein native structure was not recovered. All samples at acidic pH showed that the protein quickly regained its structure. Hydrolysis of beta-lactoglobulin by pepsin and chymotrypsin could be related to pressure-induced changes in the structure of the protein. Compared to the behavior of the protein at atmospheric pressure, no increased proteolysis was found in samples with no increased flexibility (100 MPa, 37 degrees C, pH 2.5). Slightly flexible structures were associated with significantly increased proteolysis (100 MPa, 37 degrees C, pH 6.8; 200 MPa, 37 degrees C, pH 2.5). Highly flexible structures were associated with very fast proteolysis (>or=200 MPa, 37 degrees C, pH 6.8; >or=300 MPa, 37 degrees C, pH 2.5). Proteolysis of prepressurized samples improved only when the protein was significantly changed after the pressure treatment (400 MPa, 25 degrees C, 20 min, pH 6.8).     

Analysis of fine-scale spatial pattern of a grassland from remotely-sensed imagery and field collected data

An important practical problem in the analysis of spatial pattern in ecological systems is that requires spatially-intensive data, with both fine resolution and large extent. Such information is often difficult to obtain from field-measured variables. Digital imagery can offer a valuable, alternative source of information in the analysis of ecological pattern. In the present paper, we use remotely-sensed imagery to provide a link between field-based information and spatially-explicit modeling of ecological processes. We analyzed one digitized color infrared aerial photograph of a serpentine grassland to develop a detailed digital map of land cover categories (31.24 m × 50.04 m of extent and 135 mm of resolution), and an image of vegetation index (proportional to the amount of green biomass cover in the field). We conducted a variogram analysis of the spatial pattern of both field-measured (microtopography, soil depth) and image-derived (land cover map, vegetation index, gopher disturbance) landscape variables, and used a statistical simulation method to produce random realizations of the image of vegetation index based upon our characterization of its spatial structure. The analysis revealed strong relationships in the spatial distribution of the ecological variables (e.g., gopher mounds and perennial grasses are found primarily on deeper soils) and a non-fractal nested spatial pattern in the distribution of green biomass as measured by the vegetation index. The spatial pattern of the vegetation index was composed of three basic components: an exponential trend from 0 m to 4 m, which is related to local ecological processes, a linear trend at broader scales, which is related to a general change in topography across the study site, and a superimposed periodic structure, which is related to the regular spacing of deeper soils within the study site. Simulations of the image of vegetation index confirmed our interpretation of the variograms. The simulations also illustrated the limits of statistical analysis and interpolations based solely on the semivariogram, because they cannot adequately characterize spatial discontinuities.