Molecular weight estimation using sodium dodecyl sulfate-pore gradient electrophoresis

Abstract

Pore gradient electrophoresis (PGE) in the presence of sodium dodecyl sulfate (SDS) provides a means for high resolution fractionation of multicomponent protein systems and permits estimation of molecular weights for macromolecules ranging from 10 3 to 10 6. We have evaluated the performance of several methods used to construct calibration curves for estimation of molecular weights using SDS-PGE. A linear relationship between the logarithm of molecular weight, log ( M r), and the logarithm of the relative mobility, log ( R l ), can be obtained for a 30-fold range of molecular weights. However, this range of linearity depends on the choice of the concentration gradient, the degree of crosslinking of the gel, and on the nature of the underlying relationship between the retardation coefficient, K R , and the molecular weight. An empirical relationship, first introduced by Lambin et al. (1976, Anal. Biochem. 74, 567) between log ( M r) and the logarithm of the gel concentration at the position reached by the protein, log (% T), provides better linearity over a wider molecular weight range than does the use of log ( R l ). We have compared these relatienships by experimental analysis of 10 standard proteins and by a theoretical analysis of an idealized model system. A computer program has been developed which provides appropriate statistical estimation of the molecular weight for an unknown protein, together with its standard error and 95% confidence limits. A new method has also been developed for analysis of nonlinear calibration curves in terms of molecular weight versus distance migrated, based on a theoretically justifiable, physical-chemical model. This model implies that either the relationship between log ( M r) and log ( R l ) or the one between log ( M r) and log (% T) will become nonlinear as the range of molecular weight is extended. We suggest that the use of a nonlinear least-squares curve-fitting procedure provides an optimal method for molecular weight estimation when sufficient data are available. Based on these findings, a general strategy is presented for estimation of molecular weights by polyacrylamide gel electrophoresis.