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Quantitative elucidation of a distinct spatial gradient-sensing mechanism in fibroblasts.

Schneider IC, Haugh JM - J. Cell Biol. (2005)

Bottom Line: Migration of eukaryotic cells toward a chemoattractant often relies on their ability to distinguish receptor-mediated signaling at different subcellular locations, a phenomenon known as spatial sensing.A prominent example that is seen during wound healing is fibroblast migration in platelet-derived growth factor (PDGF) gradients.Robust PDGF sensing requires steeper gradients and a much narrower range of absolute chemoattractant concentration, which is consistent with a simpler system lacking the feedback loops that yield signal amplification and adaptation in amoeboid cells.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC 27695, USA.

ABSTRACT
Migration of eukaryotic cells toward a chemoattractant often relies on their ability to distinguish receptor-mediated signaling at different subcellular locations, a phenomenon known as spatial sensing. A prominent example that is seen during wound healing is fibroblast migration in platelet-derived growth factor (PDGF) gradients. As in the well-characterized chemotactic cells Dictyostelium discoideum and neutrophils, signaling to the cytoskeleton via the phosphoinositide 3-kinase pathway in fibroblasts is spatially polarized by a PDGF gradient; however, the sensitivity of this process and how it is regulated are unknown. Through a quantitative analysis of mathematical models and live cell total internal reflection fluorescence microscopy experiments, we demonstrate that PDGF detection is governed by mechanisms that are fundamentally different from those in D. discoideum and neutrophils. Robust PDGF sensing requires steeper gradients and a much narrower range of absolute chemoattractant concentration, which is consistent with a simpler system lacking the feedback loops that yield signal amplification and adaptation in amoeboid cells.

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Spatial modeling of intracellular TIRF profiles. (A) TIRF images showing the extracellular OG 514–dextran profile (PDGF) and intracellular CFP-AktPH profiles as in Fig. 3 A (the cell is the same as in Fig. 3 A, with midpoint [PDGF] = 0.61 nM and δ = 0.75). All CFP-AktPH images use the same absolute pseudocolor scale, and the OG 514–dextran image is scaled such that black is the background and white is the TIRF intensity at the pipette tip. Bar, 30 μm. (B) Virtual images obtained from finite element calculations (see supplemental Modeling details for specifics and parameter definitions, available at http://www.jcb.org/cgi/content/full/jcb.200509028/DC1). Dimensionless parameter values describing 3′ PI diffusion and the AktPH interaction are the same as those used previously (Haugh and Schneider, 2004; Schneider and Haugh, 2004; Schneider et al., 2005: Da = 3; μ = 5; κP = 2; υt = e + x0(1 − 〈e〉); and υb = x0(1 − 〈e〉). Parameters describing the PDGF dose response have the same values used in Figs. 1 and 3: αdmax = 10; κE = 0.1; and L* = 1 nM. The two remaining parameter values (σ = 15.0 and x0 = 0.016) were specified to match the overall fluorescence intensities observed before stimulation and after uniform PDGF stimulation. (C) Finite element calculations accounting for enhanced 3′ PI levels in leading edge hot spots. Hot spots were modeled as regions with locally enhanced PI 3-kinase activity (υb = υt = e + x0[1 − 〈e〉]) and slower 3′ PI diffusion coefficient (reduced by half). Other parameters are as in B except σ = 16.3 and x0 = 0.015. (D) Comparison of observed (dots) and calculated (solid lines; the model with hot spots is in red) TIRF profiles along the line scan indicated.
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fig4: Spatial modeling of intracellular TIRF profiles. (A) TIRF images showing the extracellular OG 514–dextran profile (PDGF) and intracellular CFP-AktPH profiles as in Fig. 3 A (the cell is the same as in Fig. 3 A, with midpoint [PDGF] = 0.61 nM and δ = 0.75). All CFP-AktPH images use the same absolute pseudocolor scale, and the OG 514–dextran image is scaled such that black is the background and white is the TIRF intensity at the pipette tip. Bar, 30 μm. (B) Virtual images obtained from finite element calculations (see supplemental Modeling details for specifics and parameter definitions, available at http://www.jcb.org/cgi/content/full/jcb.200509028/DC1). Dimensionless parameter values describing 3′ PI diffusion and the AktPH interaction are the same as those used previously (Haugh and Schneider, 2004; Schneider and Haugh, 2004; Schneider et al., 2005: Da = 3; μ = 5; κP = 2; υt = e + x0(1 − 〈e〉); and υb = x0(1 − 〈e〉). Parameters describing the PDGF dose response have the same values used in Figs. 1 and 3: αdmax = 10; κE = 0.1; and L* = 1 nM. The two remaining parameter values (σ = 15.0 and x0 = 0.016) were specified to match the overall fluorescence intensities observed before stimulation and after uniform PDGF stimulation. (C) Finite element calculations accounting for enhanced 3′ PI levels in leading edge hot spots. Hot spots were modeled as regions with locally enhanced PI 3-kinase activity (υb = υt = e + x0[1 − 〈e〉]) and slower 3′ PI diffusion coefficient (reduced by half). Other parameters are as in B except σ = 16.3 and x0 = 0.015. (D) Comparison of observed (dots) and calculated (solid lines; the model with hot spots is in red) TIRF profiles along the line scan indicated.

Mentions: To refine our quasi–steady-state model of PDGF gradient sensing, finite element calculations were performed that allowed us to directly compare the predicted fluorescence profile, f (equation 4), with the acquired TIRF images at each point in the contact area (Fig. 4). The actual PDGF concentration field and irregular cell geometry are inputs to the model, which accounts for pseudo-steady receptor and PI 3-kinase activation as well as lateral diffusion of 3′ PI lipids and recruitment of the CFP-AktPH probe from the cytosol. Order of magnitude estimates of the model parameter values were assigned based on our previous experimental and modeling studies of fibroblast responses to uniform PDGF stimulation (Haugh et al., 2000; Park et al., 2003; Haugh and Schneider, 2004; Schneider and Haugh, 2004; Schneider et al., 2005) and to approximately match the overall fluorescence intensities observed before stimulation and after uniform saturation. No parameters were fitted to the gradient response.


Quantitative elucidation of a distinct spatial gradient-sensing mechanism in fibroblasts.

Schneider IC, Haugh JM - J. Cell Biol. (2005)

Spatial modeling of intracellular TIRF profiles. (A) TIRF images showing the extracellular OG 514–dextran profile (PDGF) and intracellular CFP-AktPH profiles as in Fig. 3 A (the cell is the same as in Fig. 3 A, with midpoint [PDGF] = 0.61 nM and δ = 0.75). All CFP-AktPH images use the same absolute pseudocolor scale, and the OG 514–dextran image is scaled such that black is the background and white is the TIRF intensity at the pipette tip. Bar, 30 μm. (B) Virtual images obtained from finite element calculations (see supplemental Modeling details for specifics and parameter definitions, available at http://www.jcb.org/cgi/content/full/jcb.200509028/DC1). Dimensionless parameter values describing 3′ PI diffusion and the AktPH interaction are the same as those used previously (Haugh and Schneider, 2004; Schneider and Haugh, 2004; Schneider et al., 2005: Da = 3; μ = 5; κP = 2; υt = e + x0(1 − 〈e〉); and υb = x0(1 − 〈e〉). Parameters describing the PDGF dose response have the same values used in Figs. 1 and 3: αdmax = 10; κE = 0.1; and L* = 1 nM. The two remaining parameter values (σ = 15.0 and x0 = 0.016) were specified to match the overall fluorescence intensities observed before stimulation and after uniform PDGF stimulation. (C) Finite element calculations accounting for enhanced 3′ PI levels in leading edge hot spots. Hot spots were modeled as regions with locally enhanced PI 3-kinase activity (υb = υt = e + x0[1 − 〈e〉]) and slower 3′ PI diffusion coefficient (reduced by half). Other parameters are as in B except σ = 16.3 and x0 = 0.015. (D) Comparison of observed (dots) and calculated (solid lines; the model with hot spots is in red) TIRF profiles along the line scan indicated.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC2171296&req=5

fig4: Spatial modeling of intracellular TIRF profiles. (A) TIRF images showing the extracellular OG 514–dextran profile (PDGF) and intracellular CFP-AktPH profiles as in Fig. 3 A (the cell is the same as in Fig. 3 A, with midpoint [PDGF] = 0.61 nM and δ = 0.75). All CFP-AktPH images use the same absolute pseudocolor scale, and the OG 514–dextran image is scaled such that black is the background and white is the TIRF intensity at the pipette tip. Bar, 30 μm. (B) Virtual images obtained from finite element calculations (see supplemental Modeling details for specifics and parameter definitions, available at http://www.jcb.org/cgi/content/full/jcb.200509028/DC1). Dimensionless parameter values describing 3′ PI diffusion and the AktPH interaction are the same as those used previously (Haugh and Schneider, 2004; Schneider and Haugh, 2004; Schneider et al., 2005: Da = 3; μ = 5; κP = 2; υt = e + x0(1 − 〈e〉); and υb = x0(1 − 〈e〉). Parameters describing the PDGF dose response have the same values used in Figs. 1 and 3: αdmax = 10; κE = 0.1; and L* = 1 nM. The two remaining parameter values (σ = 15.0 and x0 = 0.016) were specified to match the overall fluorescence intensities observed before stimulation and after uniform PDGF stimulation. (C) Finite element calculations accounting for enhanced 3′ PI levels in leading edge hot spots. Hot spots were modeled as regions with locally enhanced PI 3-kinase activity (υb = υt = e + x0[1 − 〈e〉]) and slower 3′ PI diffusion coefficient (reduced by half). Other parameters are as in B except σ = 16.3 and x0 = 0.015. (D) Comparison of observed (dots) and calculated (solid lines; the model with hot spots is in red) TIRF profiles along the line scan indicated.
Mentions: To refine our quasi–steady-state model of PDGF gradient sensing, finite element calculations were performed that allowed us to directly compare the predicted fluorescence profile, f (equation 4), with the acquired TIRF images at each point in the contact area (Fig. 4). The actual PDGF concentration field and irregular cell geometry are inputs to the model, which accounts for pseudo-steady receptor and PI 3-kinase activation as well as lateral diffusion of 3′ PI lipids and recruitment of the CFP-AktPH probe from the cytosol. Order of magnitude estimates of the model parameter values were assigned based on our previous experimental and modeling studies of fibroblast responses to uniform PDGF stimulation (Haugh et al., 2000; Park et al., 2003; Haugh and Schneider, 2004; Schneider and Haugh, 2004; Schneider et al., 2005) and to approximately match the overall fluorescence intensities observed before stimulation and after uniform saturation. No parameters were fitted to the gradient response.

Bottom Line: Migration of eukaryotic cells toward a chemoattractant often relies on their ability to distinguish receptor-mediated signaling at different subcellular locations, a phenomenon known as spatial sensing.A prominent example that is seen during wound healing is fibroblast migration in platelet-derived growth factor (PDGF) gradients.Robust PDGF sensing requires steeper gradients and a much narrower range of absolute chemoattractant concentration, which is consistent with a simpler system lacking the feedback loops that yield signal amplification and adaptation in amoeboid cells.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC 27695, USA.

ABSTRACT
Migration of eukaryotic cells toward a chemoattractant often relies on their ability to distinguish receptor-mediated signaling at different subcellular locations, a phenomenon known as spatial sensing. A prominent example that is seen during wound healing is fibroblast migration in platelet-derived growth factor (PDGF) gradients. As in the well-characterized chemotactic cells Dictyostelium discoideum and neutrophils, signaling to the cytoskeleton via the phosphoinositide 3-kinase pathway in fibroblasts is spatially polarized by a PDGF gradient; however, the sensitivity of this process and how it is regulated are unknown. Through a quantitative analysis of mathematical models and live cell total internal reflection fluorescence microscopy experiments, we demonstrate that PDGF detection is governed by mechanisms that are fundamentally different from those in D. discoideum and neutrophils. Robust PDGF sensing requires steeper gradients and a much narrower range of absolute chemoattractant concentration, which is consistent with a simpler system lacking the feedback loops that yield signal amplification and adaptation in amoeboid cells.

Show MeSH
Related in: MedlinePlus