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Comparative Study
. 2003 Apr;119(4):333-41.
doi: 10.1007/s00418-003-0523-6. Epub 2003 Apr 15.

A simpler way of comparing the labelling densities of cellular compartments illustrated using data from VPARP and LAMP-1 immunogold labelling experiments

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Comparative Study

A simpler way of comparing the labelling densities of cellular compartments illustrated using data from VPARP and LAMP-1 immunogold labelling experiments

Terry Mayhew et al. Histochem Cell Biol. 2003 Apr.

Abstract

Quantitative immunoelectron microscopy of gold label in intracellular compartments often involves calculating labelling densities (LDs). These are related to antigen concentrations and usually refer gold particle counts to the sizes of compartments on sections (for example, golds per microm(2) of organelle profile area or per microm of membrane trace length). Here, we show how LD values can be estimated more simply (without estimating areas or lengths) and also how observed and expected LD values can be used to calculate a relative labelling index (RLI) for each compartment and then test statistically for preferential (non-random) labelling. For random labelling, RLI=1. Compartment size is estimated stereologically by superimposing random test points (which hit organelle profiles in proportion to their area) or test lines (which intersect membrane traces in proportion to their length). By this means, the observed LD of a compartment (LD(obs)) can be expressed simply as golds per test point (organelles) or per intersection (membranes). Furthermore, the LD obtained by dividing total golds (on all compartments) by total points or intersections (on all compartments) is the value to be expected (LD(exp)) when compartments label randomly. For each compartment, RLI=LD(obs)/LD(exp). Statistical analysis is undertaken by comparing observed distributions of golds with predicted random distributions (calculated from point or intersection counts). A compartment is preferentially labelled if two criteria are met: (1) its RLI>1 (i.e. LD(obs) is greater than LD(exp)) and (2) its partial chi-squared value makes a substantial contribution to total chi-squared value. This approach provides a simple and efficient way of comparing LDs in different compartments. Its utility is illustrated using data from VPARP and LAMP-1 labelling experiments.

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