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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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Sensitivity of the PDGF gradient–sensing mechanism: experimental validation. (A) Representative cell responses to steep PDGF gradients with different midpoint concentrations. The montages shows TIRF images acquired prestimulus (initial), at the peak of the gradient response, after bolus addition of 10 nM PDGF (uniform), and after PI 3-kinase inhibition with wortmannin (wort). The arrows indicate PDGF gradient orientation from high to low, and the relative gradients δ across these four cells were 0.75, 0.63, 0.75, and 0.59 (from top to bottom). Bars, 30 μm. The normalized TIRF intensities at the front (closed circles) and back (open circles) of each cell with respect to the gradient are shown as a function of time, with dotted lines indicating the additions of uniform PDGF and wortmannin. (B–D) The local normalized response to the gradient stimulation is defined as Γ (equation 5). (B) Whole cell average responses, 〈Γ〉, of individual cells to various gradients tend to increase with midpoint PDGF concentration and are not affected by gradient steepness. Values of 〈Γ〉 were classified as low (<0.3; blue triangles), intermediate (0.3–0.7; green squares), or high (>0.7; red circles). PDGF concentration cut-offs of 0.05 and 1 nM (vertical dotted lines) demarcate cell populations that tend to exhibit low or high average responses. (C) The difference in response between the front and back is optimized at intermediate PDGF concentrations and depends on the gradient steepness. Values of ΔΓ were classified as low (<0.1; blue triangles), intermediate (0.1–0.3; green squares), or high (>0.3; red circles). The quasi–steady-state model results from Fig. 1 C, with L* = 1 nM, are overlaid for comparison. (D) Fractional responses at the front and back are plotted for the cells depicted in B and C and are grouped according to the midpoint concentration and steepness of the PDGF gradient: black diamonds, <0.1 nM PDGF; blue triangles, 0.1–2 nM PDGF and δ < 0.3; red circles, 0.1–2 nM PDGF and δ > 0.3; green squares, >2 nM PDGF.
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fig3: Sensitivity of the PDGF gradient–sensing mechanism: experimental validation. (A) Representative cell responses to steep PDGF gradients with different midpoint concentrations. The montages shows TIRF images acquired prestimulus (initial), at the peak of the gradient response, after bolus addition of 10 nM PDGF (uniform), and after PI 3-kinase inhibition with wortmannin (wort). The arrows indicate PDGF gradient orientation from high to low, and the relative gradients δ across these four cells were 0.75, 0.63, 0.75, and 0.59 (from top to bottom). Bars, 30 μm. The normalized TIRF intensities at the front (closed circles) and back (open circles) of each cell with respect to the gradient are shown as a function of time, with dotted lines indicating the additions of uniform PDGF and wortmannin. (B–D) The local normalized response to the gradient stimulation is defined as Γ (equation 5). (B) Whole cell average responses, 〈Γ〉, of individual cells to various gradients tend to increase with midpoint PDGF concentration and are not affected by gradient steepness. Values of 〈Γ〉 were classified as low (<0.3; blue triangles), intermediate (0.3–0.7; green squares), or high (>0.7; red circles). PDGF concentration cut-offs of 0.05 and 1 nM (vertical dotted lines) demarcate cell populations that tend to exhibit low or high average responses. (C) The difference in response between the front and back is optimized at intermediate PDGF concentrations and depends on the gradient steepness. Values of ΔΓ were classified as low (<0.1; blue triangles), intermediate (0.1–0.3; green squares), or high (>0.3; red circles). The quasi–steady-state model results from Fig. 1 C, with L* = 1 nM, are overlaid for comparison. (D) Fractional responses at the front and back are plotted for the cells depicted in B and C and are grouped according to the midpoint concentration and steepness of the PDGF gradient: black diamonds, <0.1 nM PDGF; blue triangles, 0.1–2 nM PDGF and δ < 0.3; red circles, 0.1–2 nM PDGF and δ > 0.3; green squares, >2 nM PDGF.

Mentions: PI 3-kinase signaling responses to PDGF gradients of varying midpoint concentration and steepness were consistent with model predictions (Fig. 3). Proper gradient sensing was apparent within a relatively narrow range of PDGF concentration, as PDGF gradients with low midpoint concentrations elicited little change in the TIRF profile, whereas cells exposed to gradients with very high midpoint concentrations showed little change after the uniform stimulus; optimal gradient sensing was often accompanied by a decrease in fluorescence at the front and a corresponding increase at the back after the uniformly saturating dose (Fig. 3 A). In all cases, the observed kinetics were consistent with those calculated in Fig. 1 D. It should be noted that these experiments were performed at room temperature to inhibit cell motility (Haugh et al., 2000) so that the regions would remain stationary during the experiment. The qualitative predictions of the model were also validated in experiments conducted at 37°C, in which spatially biased membrane-spreading events were also observed (Fig. S1, available at http://www.jcb.org/cgi/content/full/jcb.200509028/DC1).


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

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

Sensitivity of the PDGF gradient–sensing mechanism: experimental validation. (A) Representative cell responses to steep PDGF gradients with different midpoint concentrations. The montages shows TIRF images acquired prestimulus (initial), at the peak of the gradient response, after bolus addition of 10 nM PDGF (uniform), and after PI 3-kinase inhibition with wortmannin (wort). The arrows indicate PDGF gradient orientation from high to low, and the relative gradients δ across these four cells were 0.75, 0.63, 0.75, and 0.59 (from top to bottom). Bars, 30 μm. The normalized TIRF intensities at the front (closed circles) and back (open circles) of each cell with respect to the gradient are shown as a function of time, with dotted lines indicating the additions of uniform PDGF and wortmannin. (B–D) The local normalized response to the gradient stimulation is defined as Γ (equation 5). (B) Whole cell average responses, 〈Γ〉, of individual cells to various gradients tend to increase with midpoint PDGF concentration and are not affected by gradient steepness. Values of 〈Γ〉 were classified as low (<0.3; blue triangles), intermediate (0.3–0.7; green squares), or high (>0.7; red circles). PDGF concentration cut-offs of 0.05 and 1 nM (vertical dotted lines) demarcate cell populations that tend to exhibit low or high average responses. (C) The difference in response between the front and back is optimized at intermediate PDGF concentrations and depends on the gradient steepness. Values of ΔΓ were classified as low (<0.1; blue triangles), intermediate (0.1–0.3; green squares), or high (>0.3; red circles). The quasi–steady-state model results from Fig. 1 C, with L* = 1 nM, are overlaid for comparison. (D) Fractional responses at the front and back are plotted for the cells depicted in B and C and are grouped according to the midpoint concentration and steepness of the PDGF gradient: black diamonds, <0.1 nM PDGF; blue triangles, 0.1–2 nM PDGF and δ < 0.3; red circles, 0.1–2 nM PDGF and δ > 0.3; green squares, >2 nM PDGF.
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fig3: Sensitivity of the PDGF gradient–sensing mechanism: experimental validation. (A) Representative cell responses to steep PDGF gradients with different midpoint concentrations. The montages shows TIRF images acquired prestimulus (initial), at the peak of the gradient response, after bolus addition of 10 nM PDGF (uniform), and after PI 3-kinase inhibition with wortmannin (wort). The arrows indicate PDGF gradient orientation from high to low, and the relative gradients δ across these four cells were 0.75, 0.63, 0.75, and 0.59 (from top to bottom). Bars, 30 μm. The normalized TIRF intensities at the front (closed circles) and back (open circles) of each cell with respect to the gradient are shown as a function of time, with dotted lines indicating the additions of uniform PDGF and wortmannin. (B–D) The local normalized response to the gradient stimulation is defined as Γ (equation 5). (B) Whole cell average responses, 〈Γ〉, of individual cells to various gradients tend to increase with midpoint PDGF concentration and are not affected by gradient steepness. Values of 〈Γ〉 were classified as low (<0.3; blue triangles), intermediate (0.3–0.7; green squares), or high (>0.7; red circles). PDGF concentration cut-offs of 0.05 and 1 nM (vertical dotted lines) demarcate cell populations that tend to exhibit low or high average responses. (C) The difference in response between the front and back is optimized at intermediate PDGF concentrations and depends on the gradient steepness. Values of ΔΓ were classified as low (<0.1; blue triangles), intermediate (0.1–0.3; green squares), or high (>0.3; red circles). The quasi–steady-state model results from Fig. 1 C, with L* = 1 nM, are overlaid for comparison. (D) Fractional responses at the front and back are plotted for the cells depicted in B and C and are grouped according to the midpoint concentration and steepness of the PDGF gradient: black diamonds, <0.1 nM PDGF; blue triangles, 0.1–2 nM PDGF and δ < 0.3; red circles, 0.1–2 nM PDGF and δ > 0.3; green squares, >2 nM PDGF.
Mentions: PI 3-kinase signaling responses to PDGF gradients of varying midpoint concentration and steepness were consistent with model predictions (Fig. 3). Proper gradient sensing was apparent within a relatively narrow range of PDGF concentration, as PDGF gradients with low midpoint concentrations elicited little change in the TIRF profile, whereas cells exposed to gradients with very high midpoint concentrations showed little change after the uniform stimulus; optimal gradient sensing was often accompanied by a decrease in fluorescence at the front and a corresponding increase at the back after the uniformly saturating dose (Fig. 3 A). In all cases, the observed kinetics were consistent with those calculated in Fig. 1 D. It should be noted that these experiments were performed at room temperature to inhibit cell motility (Haugh et al., 2000) so that the regions would remain stationary during the experiment. The qualitative predictions of the model were also validated in experiments conducted at 37°C, in which spatially biased membrane-spreading events were also observed (Fig. S1, available at http://www.jcb.org/cgi/content/full/jcb.200509028/DC1).

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