100 Shworak
HS population were to function as precursor, then linearity would only be approximated
until ~30% of substrate was expended. In reality, a precursor pool may comprise only a
small fraction of total HS (6), consequently linearity may occur over only a narrow range
of enzyme activities. Fortunately, the deviation from linearity is mathematically predict-
able, which allows for an expansion of the useful range of the standard curve. Nonlinear
data are best fit by a second-order polynomial if the departure from linearity is small.
With higher enzyme activities the plateau is approached, which best fits a power func-
tion. In this latter case, assay precision deteriorates near the plateau. Consequently, one
should discard any high-activity points that lie within an obvious plateau.
20. Given the above complexities of curve fitting, extrapolation should not be performed.
Any samples that lie outside the curve should be rerun at adjusted concentrations to obtain
conversion values that lie within the reliable portion of the standard curve.
21. To determine the correction factor, pure standard is preferred. For each extract type, a
standard curve is run in the absence and presence of cell extract and raw sample activities
are calculated (see Subheading 3.3., Steps 6 and 7). The extract specific correction
factor is the slope obtained by plotting observed activity (abscissa) versus the activity
of added standard (ordinate).
References
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N. A., and Rosenberg, R. D. (1999) Multiple isoforms of heparan sulfate
D-glucosaminyl
3-O-sulfotransferase. Isolation, characterization, and expression of human cDNAs and
identification of distinct genomic loci. J. Biol. Chem. 274, 5170–5184.
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