The conserved tetrameric subunit stoichiometry of Slc26 proteins

Abstract

The Slc26 family proteins, with one possible exception, transport anions across membranes in a wide variety of tissues in vertebrates, invertebrates, and plants. Mutations in human members of the family are a significant cause of disease. Slc26 family proteins are thought to be oligomers, but their stoichiometry of association is in dispute. A recent study, using sequential bleaching of single fluorophore-coupled molecules in membrane fragments, demonstrated that mammalian Slc26a5 (prestin) is a tetramer. In this article, the stoichiometry of two nonmammalian prestins and three human SLC26 proteins has been analyzed by the same method, including the evolutionarily-distant SLC26A11. The analysis showed that tetramerization is common and likely to be ubiquitous among Slc26 proteins, at least in vertebrates. The implication of the findings is that tetramerization is present for functional reasons.

Figure 1

A) Image of a single molecule showing the mask used for analysis. The scale bar represents 750 nm. B) Representative example of the time courses of fluorescence from experiments such as Figure 1A. The scale bars represent 50 s (time, horizontal) and 200 average counts (amplitude, vertical).

Figure 2

Molecular phylogenetic analysis of Slc26 proteins by the Maximum Likelihood method. The tree with the highest log likelihood (−15058.5) is shown. The tree is drawn to scale. The scale bar represents the number of substitutions per residue.

Figure 3

Histograms of step size (A, in arbitrary units) and step counts (B) for a representative experiment in the determination of p. In A, the Gaussian fit parameters are given on the figure. The solid line and points in B shows the predicted distribution of step counts assuming n = 4.

Figure 4

Histograms of step size and step counts for single representative experiments in the determination of Slc26 stoichiometry. A) Histograms of step sizes (A1, in arbitrary units) and step counts (A2) from a single experiment on positive control ORAI1-eGFP. B) Histograms of step sizes (B1, in arbitrary units) and step counts (B2) from a single experiment on cPRES-eGFP. C) Histograms of step sizes (C1, in arbitrary units) and step counts (C2) from a single experiment on zpres-eGFP. The fit parameters for the step size distributions are given on the figures. In the step count histograms, the parameters show are the distribution mean μ_c and the number of points analyzed N. The solid lines and points show the predicted distribution of step counts assuming p = pest = 0.69 and n is the calculated integer value given in Table 2.

Figure 5

Histograms of step size and step counts for single representative experiments on SLC26 paralogs. A) Histograms of step sizes (A1, in arbitrary units) and step counts (A2) from a single experiment on SLC26A4-eGFP. B) Histograms of step sizes (B1, in arbitrary units) and step counts (B2) from a single experiment on SLC26A9-eGFP eGFP. C) Histograms of step sizes (C1, in arbitrary units) and step counts (C2) from a single experiment on SLC26A11-eGFP eGFP. The fit parameters for the step size distributions are given on the figures. In the step count histograms, the parameters show are the distribution mean μ>_c and the number of points analyzed N. The solid lines and points show the predicted distribution of step counts assuming p = pest = 0.69 and n is the calculated integer value given in Table 2.