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SAM domain-based protein oligomerization observed by live-cell fluorescence fluctuation spectroscopy.

Slaughter BD, Huff JM, Wiegraebe W, Schwartz JW, Li R - PLoS ONE (2008)

Bottom Line: Fluorescence cross-correlation spectroscopy (FCCS) and 1-dimensional photon counting histogram (1dPCH) confirm the SAM-mediated interaction and oligomerization of Ste11 and Ste50.In addition, Ste50 also exists as a high order oligomer that does not interact with Ste11, and the size of this oligomer decreases in response to signals that activate the MAP kinase cascade.Surprisingly, a SAM domain mutant of Ste50 disrupted not only the Ste50 oligomers but also Ste11 dimerization.

View Article: PubMed Central - PubMed

Affiliation: The Stowers Institute for Medical Research, Kansas City, Missouri, United States of America.

ABSTRACT
Sterile-alpha-motif (SAM) domains are common protein interaction motifs observed in organisms as diverse as yeast and human. They play a role in protein homo- and hetero-interactions in processes ranging from signal transduction to RNA binding. In addition, mutations in SAM domain and SAM-mediated oligomers have been linked to several diseases. To date, the observation of heterogeneous SAM-mediated oligomers in vivo has been elusive, which represents a common challenge in dissecting cellular biochemistry in live-cell systems. In this study, we report the oligomerization and binding stoichiometry of high-order, multi-component complexes of (SAM) domain proteins Ste11 and Ste50 in live yeast cells using fluorescence fluctuation methods. Fluorescence cross-correlation spectroscopy (FCCS) and 1-dimensional photon counting histogram (1dPCH) confirm the SAM-mediated interaction and oligomerization of Ste11 and Ste50. Two-dimensional PCH (2dPCH), with endogenously expressed proteins tagged with GFP or mCherry, uniquely indicates that Ste11 and Ste50 form a heterogeneous complex in the yeast cytosol comprised of a dimer of Ste11 and a monomer of Ste50. In addition, Ste50 also exists as a high order oligomer that does not interact with Ste11, and the size of this oligomer decreases in response to signals that activate the MAP kinase cascade. Surprisingly, a SAM domain mutant of Ste50 disrupted not only the Ste50 oligomers but also Ste11 dimerization. These results establish an in vivo model of Ste50 and Ste11 homo- and hetero-oligomerization and highlight the usefulness of 2dPCH for quantitative dissection of complex molecular interactions in genetic model organisms such as yeast.

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Fluctuation data can probe protein-protein interactions.A. Example traces of fluctuation data for dual-color experiments. B. Data can be analyzed by correlation analysis to examine concentration, diffusion, and co-diffusion of red and green particles. C. 1dPCH examines the distribution of photon events per time interval, and reports concentration and ‘brightness’, or oligomeric status. D. 2dPCH reports simultaneously concentration, interaction, oligomerization, and binding stoichiometry of heterogeneous complexes. An example two-dimensional PCH histogram is shown, with frequency versus number of green photons and number of red photons per time bin. E. Example, two-dimensional plot of a fit of modeled 2dPCH data. If a monomer red or green probe has a brightness of 3000 CPSM, for example, the plot demonstrates points one would expect to find values for with non-interacting monomeric species, or interacting monomeric species, or interacting dimeric species, as labeled.
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pone-0001931-g001: Fluctuation data can probe protein-protein interactions.A. Example traces of fluctuation data for dual-color experiments. B. Data can be analyzed by correlation analysis to examine concentration, diffusion, and co-diffusion of red and green particles. C. 1dPCH examines the distribution of photon events per time interval, and reports concentration and ‘brightness’, or oligomeric status. D. 2dPCH reports simultaneously concentration, interaction, oligomerization, and binding stoichiometry of heterogeneous complexes. An example two-dimensional PCH histogram is shown, with frequency versus number of green photons and number of red photons per time bin. E. Example, two-dimensional plot of a fit of modeled 2dPCH data. If a monomer red or green probe has a brightness of 3000 CPSM, for example, the plot demonstrates points one would expect to find values for with non-interacting monomeric species, or interacting monomeric species, or interacting dimeric species, as labeled.

Mentions: Emerging fluorescence-based technologies probe in vivo binding equilibrium and stoichiometry of protein complexes. Fluorescence correlation spectroscopy (FCS) and fluorescence cross-correlation spectroscopy (FCCS) [22]–[26] are fluctuation techniques that analyze protein mobility, concentration, and protein-protein association (Figure 1A, 1B), and have recently been applied to live yeast cells expressing autofluorescent proteins (AFP) at the endogenous levels [27], [28]. While FCCS measures co-diffusion of two particles with different fluorescent tags, extraction of binding stoichiometry is not easily accomplished with this technique. The photon counting histogram (PCH) and similar techniques, such as fluorescence intensity distribution analysis (FIDA), are fluctuation techniques designed to analyze the oligomeric status of fluorescent species and have been applied to both in vitro and in vivo systems. These techniques determine the state of molecular homo-oligomerization [29]–[34] (Figure 1C); however, PCH does not resolve stoichiometry of heterogeneous complexes that result from dynamic protein interactions between different molecular species.


SAM domain-based protein oligomerization observed by live-cell fluorescence fluctuation spectroscopy.

Slaughter BD, Huff JM, Wiegraebe W, Schwartz JW, Li R - PLoS ONE (2008)

Fluctuation data can probe protein-protein interactions.A. Example traces of fluctuation data for dual-color experiments. B. Data can be analyzed by correlation analysis to examine concentration, diffusion, and co-diffusion of red and green particles. C. 1dPCH examines the distribution of photon events per time interval, and reports concentration and ‘brightness’, or oligomeric status. D. 2dPCH reports simultaneously concentration, interaction, oligomerization, and binding stoichiometry of heterogeneous complexes. An example two-dimensional PCH histogram is shown, with frequency versus number of green photons and number of red photons per time bin. E. Example, two-dimensional plot of a fit of modeled 2dPCH data. If a monomer red or green probe has a brightness of 3000 CPSM, for example, the plot demonstrates points one would expect to find values for with non-interacting monomeric species, or interacting monomeric species, or interacting dimeric species, as labeled.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2291563&req=5

pone-0001931-g001: Fluctuation data can probe protein-protein interactions.A. Example traces of fluctuation data for dual-color experiments. B. Data can be analyzed by correlation analysis to examine concentration, diffusion, and co-diffusion of red and green particles. C. 1dPCH examines the distribution of photon events per time interval, and reports concentration and ‘brightness’, or oligomeric status. D. 2dPCH reports simultaneously concentration, interaction, oligomerization, and binding stoichiometry of heterogeneous complexes. An example two-dimensional PCH histogram is shown, with frequency versus number of green photons and number of red photons per time bin. E. Example, two-dimensional plot of a fit of modeled 2dPCH data. If a monomer red or green probe has a brightness of 3000 CPSM, for example, the plot demonstrates points one would expect to find values for with non-interacting monomeric species, or interacting monomeric species, or interacting dimeric species, as labeled.
Mentions: Emerging fluorescence-based technologies probe in vivo binding equilibrium and stoichiometry of protein complexes. Fluorescence correlation spectroscopy (FCS) and fluorescence cross-correlation spectroscopy (FCCS) [22]–[26] are fluctuation techniques that analyze protein mobility, concentration, and protein-protein association (Figure 1A, 1B), and have recently been applied to live yeast cells expressing autofluorescent proteins (AFP) at the endogenous levels [27], [28]. While FCCS measures co-diffusion of two particles with different fluorescent tags, extraction of binding stoichiometry is not easily accomplished with this technique. The photon counting histogram (PCH) and similar techniques, such as fluorescence intensity distribution analysis (FIDA), are fluctuation techniques designed to analyze the oligomeric status of fluorescent species and have been applied to both in vitro and in vivo systems. These techniques determine the state of molecular homo-oligomerization [29]–[34] (Figure 1C); however, PCH does not resolve stoichiometry of heterogeneous complexes that result from dynamic protein interactions between different molecular species.

Bottom Line: Fluorescence cross-correlation spectroscopy (FCCS) and 1-dimensional photon counting histogram (1dPCH) confirm the SAM-mediated interaction and oligomerization of Ste11 and Ste50.In addition, Ste50 also exists as a high order oligomer that does not interact with Ste11, and the size of this oligomer decreases in response to signals that activate the MAP kinase cascade.Surprisingly, a SAM domain mutant of Ste50 disrupted not only the Ste50 oligomers but also Ste11 dimerization.

View Article: PubMed Central - PubMed

Affiliation: The Stowers Institute for Medical Research, Kansas City, Missouri, United States of America.

ABSTRACT
Sterile-alpha-motif (SAM) domains are common protein interaction motifs observed in organisms as diverse as yeast and human. They play a role in protein homo- and hetero-interactions in processes ranging from signal transduction to RNA binding. In addition, mutations in SAM domain and SAM-mediated oligomers have been linked to several diseases. To date, the observation of heterogeneous SAM-mediated oligomers in vivo has been elusive, which represents a common challenge in dissecting cellular biochemistry in live-cell systems. In this study, we report the oligomerization and binding stoichiometry of high-order, multi-component complexes of (SAM) domain proteins Ste11 and Ste50 in live yeast cells using fluorescence fluctuation methods. Fluorescence cross-correlation spectroscopy (FCCS) and 1-dimensional photon counting histogram (1dPCH) confirm the SAM-mediated interaction and oligomerization of Ste11 and Ste50. Two-dimensional PCH (2dPCH), with endogenously expressed proteins tagged with GFP or mCherry, uniquely indicates that Ste11 and Ste50 form a heterogeneous complex in the yeast cytosol comprised of a dimer of Ste11 and a monomer of Ste50. In addition, Ste50 also exists as a high order oligomer that does not interact with Ste11, and the size of this oligomer decreases in response to signals that activate the MAP kinase cascade. Surprisingly, a SAM domain mutant of Ste50 disrupted not only the Ste50 oligomers but also Ste11 dimerization. These results establish an in vivo model of Ste50 and Ste11 homo- and hetero-oligomerization and highlight the usefulness of 2dPCH for quantitative dissection of complex molecular interactions in genetic model organisms such as yeast.

Show MeSH
Related in: MedlinePlus