Project Progress Summary:
Aim 1a: What Controls the Formation of Morphogen Gradients?
During the initial phase of embryonic development, identical cells simply divide to reproduce
more of the same. At some stage, signaling protein molecules known as morphogens (aka
ligands) are synthesized at a localized site. These morphogen molecules are transported from
their production site; some bind to their cell receptors along the way, generally resulting in
different receptor occupancies at different cell locations. The spatial concentration gradient of
morphogen-receptor complexes (aka bound morphogens) induces spatially graded differences in
cell signaling. The differential cell signaling in turn gives rise to different gene expressions from
which follows different stable cell fates and visually patterned arrangements of tissues and
organs. Although the strategy of using bound morphogen gradients [LR] to create pattern is
conceptually simple (as demonstrated in (Lander 2002) for the BMP family member Dpp in the
wing imaginal disc of Drosophilas), the need to build gradients of appropriate sizes, shapes and
rates of formation imposes some constraints. For example, the tendency of signaling receptors to
degrade their ligand (of concentration [L]) can create a need for morphogen receptors to have
slow association kinetics, and to be expressed at low levels. In fact, there was considerable
uncertainty about diffusion as a mechanism for transporting ligand away from the (localized)
production site (see (Lander 2002) and references therein). To the extent that morphogen
gradients must be biologically capable of inducing different cell signaling at different cell
locations and thereby different cell fate, limitations are imposed on the range of acceptable
system parameter values such as ligand and receptor synthesis rates, VL and VR, and binding,
dissociation, and degradation rate constants, kon, koff, and kdeg, as shown in Figure 1 (with β =
VL/(D/Xmax2) being a scaled ligand synthesis rate and ψ = konRtot/(D/Xmax2)/(1+ koff/kdeg) a scaled
effective binding rate).
100
0.8
80

0.6
too
steep
60
Fractional
Receptor
Occupancy
([LR]/Rtot)
40

0.2
20


too
shallow
0
0
0.2
0.4

0.6
0.8
0
1
20
40
60
80
100
distance (µm)
Figure 1
Some of the constraints on system parameters are caused by the simplifying approximation of the
biological processes being modeled. For the Dpp gradient in the wing disc investigated in
(Lander 2002), these include modeling the ligand synthesis by a point source while in reality it
extends over several cell widths and ignoring the flux across the edge of the ligand production
region. (One surprising result of our early effort was that the boundary value problem for
determining the steady state gradient in an extracellular model, without ligand-receptor
internalization and with or without receptor renewal, has the same mathematical form as that with
endocytosis (see (Lou 2004)). Hence, if we are only interested in steady state gradients, we can
work with the extracellular model by properly interpreting the system rate constants (see also
(Lander 2005c).
1
Model Refinements (Lander, Nie, Vargas and Wan): In the early research activities supported
by the grant being renewed, the point source idealization was removed and the consequences of a
distributed Dpp production region of a few cell width around the compartment boundary of the
wing disc were studied in (Lander 2005a). The principal effect of a distributed source is the
assured existence of a steady state signaling gradient for the entire range of morphogen synthesis
rate. To relate this spatially distributed source model to a model with a point source, we
aggregated the distributed source and showed that for a relatively narrow ligand production
region (compared to the wing disc span) the distributed source model may be adequately
approximated by a point source model (Lander 2005b). The boundary condition at the source end
so derived corresponds to the one used in (Lander 2002) (see also (Lou 2004)) except for the
neglected flux term in the earlier effort. The aggregated source model was analyzed in (Lander
2005b) with the results delimiting the range of applicability of those from the earlier efforts
without the end flux term (Lander 2002),(Lou 2004). The results reported in (Lander 2005b)
assure us that the unexpected phenomenon of stable locally intense ligand-receptor
concentration gradients observed in some recent experiments is theoretical possible and can be
described by relatively simple mathematical relations.
At high ligand synthesis rates, the signaling gradients are generally not appropriate for multifate cell developments; they are too flat over a large portion of the signaling gradient region and
hence not multi-fate gradients. At moderate ligand synthesis rate, receptors will cause gradients
to decay too rapidly with distance if receptor level is not low or rate of binding to receptors is not
slow. To expand the region of the parameter space for multi-fate gradients, more complex
models of gradient formation were then developed to include additional ligand activities (such as
the effects of non-signaling molecules that bind with the relevant ligand, feedback regulations,
and co-reception) not previously considered. We report here mainly on the progress made on the
effects of non-receptor sites (and leave other effects to preliminary results sections below).
Modeling Non-Receptor Binding Sites: Morphogens can bind much more than just cell surface
receptors. For example, on vertebrate cells, BMP-2 and –4 (the orthologs of Dpp) bind to “low
affinity” sites that are at least as, if not more abundant than receptor sites. Abundant “low
affinity” sites are also seen with other morphogens, (e.g. Wnts and FGFs [56-57]). The “low”
affinity of such sites is often quite substantial. For BMPs (as well as Wnts and FGRs), many
such non-receptor sites are accounted for by cell surface heparan sulfate proteoglycans (HSPGs).
In the Drosophila wing disc, HSPGs are not only present, they affect Dpp signaling (Jackson,
Nakato et al. 1997). For the morphogen hedgehog (hh), HSPGs have been specifically implicated
in morphogen transport (although the mechanisms underlying this effect are unknown (The,
Bellaiche et al. 1999)). With the current grant support, we have examined how non-receptor
binding sites affect the establishment of morphogen gradients in several ways. Results from two
of our projects are reported under this Aim; others will appear as preliminary results in later
sections:
a) Addition of Cell Surface Bound Non-receptors to Existing Dpp Wing Disc Models (Lander,
Nie & Wan): We can modify the models B, R and C in (Lander 2002), (Lou 2004) to include
an additional set of association, dissociation, and internalization/degradation reactions associated
with a cell surface bound non-receptor (such as HSPG members). For example, modifying model
B (with a fixed receptor concentration Rtot and non-receptor concentration Ntot) yields:
A/t = D'2A/x2 –konRtotA(1 – B) + koffB – jonNtotA(1 – zC) + joffC
B/t = konRtotA(1 – B) – (koff + kdeg)B
C/t = jonNtotA(1 – zC) - (joffB + jdeg)C
(1)
with z = Rtot/Ntot and jon, joff and jdeg being association, dissociation and internalization/
degradation rate constants (respectively) associated with morphogen binding to non-receptor
sites. In Eq. (1), A=[L]/Rtot and B = [LR]/Rtot represent concentrations of free and receptor-
2
bound morphogen whereas C = [LN]/Rtot represents the concentration of morphogen bound to
non-receptor sites. Similar modifications can be made to the equations in models R and C (see
Preliminary Results section). The modified system B, designated as model NB has been analyzed
in (Lander 2005d). Among the results reported therein, we showed the effects of the addition of
non-receptor sites help to explain why overexpression of morphogen receptors can have different
(and sometimes opposite) effect in different morphogen systems. Known experimental results
show that when Dpp receptors thick veins (tkv) in wing imaginal discs are overexpressed in vivo
(Lecuit and Cohen 1998)], they produce effects significantly different from (and nearly opposite
to) those of overexpressing the Wingless (Wg) receptor Drosophila frizzled 2 (Dfz2) (Cadigan
1998). More specifically, we have from (Lecuit and Cohen 1998) that "high levels of tkv
generally sequester ligand and limit its movement across the wing disc." The corresponding
ligand-receptor gradient becomes steeper and more convex, tending to a boundary layer, while
the amplitude remains pretty much unchanged. On the other hand, we have from (Cadigan 1998)
that "high levels of a Wg receptor, Drosophila frizzled 2 (Dfz2), stabilizeWg, allowing it to reach
cells far from its site of synthesis." The theoretical results from model NB (Lander 2005d) show
that at a high concentration of non-receptor to that of receptor such as that of Wg receptor Dfz2 in
(Cadigan 1998), overexpression of signal receptor does not change the spread of the signaling
gradient, only the amplitude of concentration at the source edge But for thick veins with
konRtot/(D/Xmax2) << jonNtot/(D/Xmax2), the model predicts that overexpression of the receptor would
result in steeper and more convex [LR] gradient as observed experimentally in (Lecuit and Cohen
1998). Thus, although intuition might suggest that non-receptor binding sites, by competing with
receptors, can only inhibit the formation of gradients, the results of our investigation showed that
if the rate constants associated with binding, dissociation, internalization and degradation are very
different for non-receptor and receptor binding sites, then “a variety of behaviors is possible” as
we had anticipated in our original grant proposal. More theoretical and numerical prediction by
models incorporating effects of non-receptor (bound or unbound to a cell surface) will be reported
under other Aims below and in the Preliminary Result section.
b) Effects of heparan sulfate proteoglycan Syndecan on Wingless Signaling (Marcu, Marsh,
Nguyen, Nie & Wan) We turn next to our theoretical and experimental investigation of how the
non-receptor Syndecan promotes internalization of Wingless and inhibits wingless signaling by
overexpressing Syndecan. To mimic mathematically the overexpression of syndecan, we varied
the rate and region of syndecan production within the time limit of 30 hours chosen to see an
effect on the wingless gradient. When Vs was increased 3 times (5x10-5 to 5x10-2) the formation
of WR2 (Wingless-Frizzled2) signaling complexes decreased 6.25 times (0.25 to 0.04). This is
consistent with the biological observation that overproduction of syndecan, in an area covering
the production region of wingless, leads to loss of signaling. To determine the time evolution of
gradients, we note that the experimental overproduction of syndecan (high Vs) has the observed
effect of transiently expanding the dorso-ventral gradient of wg. This is explained by the increase
in wg production (increased Vw) following the relief of negative feedback of wg on its own
production. Mathematically however, the evolution of the relevant gradients from time 0-30
hours following the increase in Vs shows that the gradient narrows rather than expanding. This
would be expected from the overproduction of a proteoglycan which does not have an
intracellular component, like the glypicans dally and dally-like. If such a proteoglycan is to be
produced in the region of wingless expression, the surface sugar chains would trap wingless
outside the cell and prevent diffusion, thus sharpening the gradient. In fact we do observe this
effect of sharpening the gradient when we overexpress a truncated form of syndecan which lacks
the cytoplasmic tail (Figure (2)). Since our model for the full-length syndecan does not yet
include the internalization of wg through the syndecan cytoplasmic domain, the result fits our
prediction. With internalization followed by degradation we expect a longer time to reach steadystate and a transient expansion of the gradient followed by reduction of the signal. To show
mathematically and biologically the effect of loss of syndecan (with no genetic mutant which
3
allows studying the wingless gradient), we proposed 2 approaches: (i) using the mathematical
model with Vs = 0 and thus mimic a null mutant, and (ii) look at the loss of syndecan in flies
which express siRNA for syndecan. The second had been done for the different isoforms of
syndecan. The result confirmed the prediction that in the absence of syndecan there will be a gain
of wingless signaling, as shown (in Figure (3)) by the 85-100% rescue of wing margin notches in
the animals in which siRNA knocks off syndecan function (B, female expressing syndecan
siRNA) vs. controls (A, male lacking the transgene). To uncover the molecular mechanism of
syndecan activity We proposed that the antagonistic function of Syndecan is due to its function as
either a nonreceptor for Wingless or as a co-receptor with R3, and suggested that this function is
possibly mediated by PDZ proteins which act as linkers between Syndecan and the Frizzled
receptors. To date we have produced and purified bacterial extracts containing the individual and
tandem PDZ domains of these proteins and monitored their interaction with the Syndecan and
Frizzled cytoplasmic tails. The data obtained so far shows that at least one protein binds Fz2
through one of its PDZ domains (Figure 4).
So far, we have considered only the non-receptor model mathematically as suggested by the
interaction with R2. We are currently testing the co-receptor model with a set of equations that
includes internalization. Experimentally we will do competition assays in the presence of Sdc
and Frizzled to determine whether the interaction is cooperative or exclusive.
Figure (2) The wg gradient sharpens in the presence of syndecan lacking the cytoplasmic tail
intensity
normal levels of syndecan (1)
syndecan overproduction (2)
1
2
0
distance across the dorso-ventral axis
Figure (3) Loss of syndecan produces gain of wingless signaling
A
B
4
Figure (4) GM6509 PDZ2 binds Fz2 (R2)
Dilutions of the purified protein are shown next to the curve. Binding is measured in
Response Units (RU) over time after washing out the extract run over the flow cell.
250
GM6509 PDZ2
GM6509 PDZ2
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GM6509 PDZ1+PDZ2
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Re s p. Diff.
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-20
-500
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Tim e
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2500
s
A manuscript on the experimental aspects of the problem has been written but is awaiting for the
completion the theoretical study before submission for publication (see (Marcu 2005),
http://www.math.uci.edu/~fwan/sdc-wg.doc/html)
Extension to Higher Dimension: Morphogen transport in fields such as fly wing discs occurs in
an essentially two-dimensional space. Because the Dpp source in the disc is a linear array of cells
in the center of the disc, and we are primarily interested in the formation of gradients
perpendicular to this line (e.g., in the case of Dpp, along the antero-posterior axis), we have been
treating morphogen gradient formation as a one-dimensional problem in our initial modeling
efforts, e.g., System NB in Eq. (1). It was proposed as a part of Aim 1 that we would extend our
analysis to explicitly include the second dimension to see how the additional geometrical feature
would affect the theoretical conclusions and predictions of the 1-D models. As expected, results
from our two-dimensional treatment (e.g., (Lander 2003)) show that the 1-D models are found to
capture the essential features of the system, including the approach to steady state (see Figure (5))
away from the edge of the wing disc (or its idealized boundaries). We have also results for other
geometries, including morphogen movement on the surface of a spherical shell, modeling the frog
5
or fly embryo, being prepared for publication.
Figure (5)
Aim 1b: How do inhibitors of Dpp signaling such as Sog and Tsg increase Dpp activity at the
embryonic dorsal midline?(Lander, Marsh, Nie, Wan and Zhang) The phenotypes of Twisted
gastrulation (Tsg) and Short gastrulation (Sog) mutants indicate that they are required to maintain
a high level of Dpp signaling at the dorsal midline of the embryo (Figure (6)). Reconciling this
fact with observations that Tsg and Sog together act as potent inhibitors of Dpp signaling is not
straightforward. Recent reviews offer intuitive explanations invoking effects of Tsg and Sog on
Dpp transport (Harland 2001; Ray and Wharton 2001; Ross, Shimmi et al. 2001), Our modeling
and simulation studies (Mizutani 2005) have yet to provide support for such a mechanism.
It has been proposed that Tsg+Sog bind and carry Dpp to a dorsal location where it is
released--potentially by the action of the secreted protease Tolloid (Tld)--thereby concentrating
Dpp in the dorsal midline (and lowering its level laterally (Harland 2001; Ray and Wharton 2001;
Ross, Shimmi et al. 2001)). We undertook a research project to test this hypothesis and examine
the conditions need to be met for a concentrating effect by modeling the diffusion, binding and
turnover of Dpp, Sog, Tolloid (Tld) and Tsg in the fly embryo by Eq. (2) (Figure (7)), designated
as System STT, in much that same way as we did for Dpp in the wing disc. With this description
we have obtained both analytical results and numerical simulations (see (Lou 2005),(Mizutani
2005)) on how various system parameters affect distribution of the Dpp ligand and its occupied
receptors. With gradient formation and action occurring over a very short time period in the
Drosophila embryo, the biologically important solutions to this system will be at times well
before the establishment of any steady state. Hence, an understanding on how the gradients
evolve is significant to our quest for insight to mechanism underlying the observed phenomena.
A
D
B
C
amniosersa
D
D
asm
LR
asm
de
dorsal ectoderm
dpp
de
ventral ectoderm
ve
mesoderm
ve
me
V
V
me
sog
6
Figure 6: The cell fates along the D/V axis of a fly embryo are shown. A: a
micrograph of a fly embryo showing the dorsal-most amnioserosa (dark blue arrow),
the dorsal-lateral ectoderm (light blue arrow) and the ventral ectoderm (red arrow).
B: These domains are shown diagramatically and C in cross section. Dorsal is up and
ventral down. D: shows the same cell fates with the approximate distribution of
several key proteins shown. Sog (deep purple) is distributed in a gradient from
ventral to dorsal. Dpp (pink) is graded from dorsal to ventral. The peak of Dpp
signaling that forms is shown in green.
L
2L
 DL 2  K on LR  K off [ LR]  I on LSTsg  I off [ SLTsg ]Tol  v L ( x)
t
x
S
2S
 DS 2  I on LSTsg  J on RS  J off [ SR]  v S ( x)
t
x
[ SLTsg ]
 2 [ SLTsg ]
 D[ SLTsg ]
 I on SLTsg  I off [ SLTsg ]Tol
t
x 2
Tol
 2Tol
 DTol
 vTol ( x)
t
x 2
Tsg
 vT sg ( x)  I on SLTsg  I off [ SLTsg ]Tol
t
R
  K on LR  K off [ LR]  J on SR  J off [ SR]  v R ( x)
t
[ LR ]
 K on LR  K off [ LR]  K int [ LR ]
t
[ SR]
 J on SR  J off [ SR]
t
(2)
Figure 7. Equations describing the distribution and binding interactions of proteins in the
Dpp pathway. The general form of the equations follows those outlined in 1a. Symbols
are Ligand (Dpp); Tsg, (Tsg); Sog; Receptor; Tld. Tolloid. (Tld) is a secreted protease the
can cleave Sog when in a complex with other factors.
In (Mizutani 2005), we used experimental and computational approaches to investigate how the
interactions of a multi-protein network create the unusual shape and dynamics of formation of
this gradient. Starting with the observation suggesting that receptor-mediated BMP degradation
is an important driving force in gradient dynamics, we developed a general model that is capable
of capturing both subtle aspects of gradient behavior and a level of robustness that agrees with in
vivo results. The results reported in (Lou 2005),(Mizutani 2005) assure us that the unexpected
phenomenon of stable locally intense ligand-receptor concentration gradients observed in recent
experiments is theoretical possible and can be described by relatively simple mathematical
relations.
Aim 2: To investigate the effects of the role of inhibition/activation and feedback on cell
signaling (Lander, Nie and Wan) With the current grant support, we investigated, both
theoretically (by mathematical modeling, analysis and numerical simulations) and
7
experimentally, how do feedback interactions enable morphogen gradients to specify complex,
stable and robust patterns. The considerable amount of results obtained will be reported under
Preliminary Results of Aim 1 of the new proposal. We mention here only that a large part of
these results have been reported in a manuscript submitted for publication (Lander 2005e).
Others, such as the possibility of a positive feedback destabilizing the normally steady gradients
by lengthening the decaying time of transients, will be reported in manuscripts under preparation
(including one cited under Aim 1a (Marcu 2005)).
Aim 3: To test the predictions emerging from aims 1-2 abov. In addition to experimental work
reported under the previous Aims, a team headed by Co-PI Marsh performed experiments on
diffusive rate for Dpp in Drosophila wing discs to establish Fluorescence Correlation
Spectroscopy measurements in tissues. The results are published (Wang 2004).
Fluorescence correlation spectroscopy (FCS) is a powerful tool for studying the dynamic
properties of diffusion and chemical reactions, as well as molecular concentrations.1 Recent
developments in FCS technology have opened the possibility to observe the in vivo properties of
protein molecules2-6. To date, in vivo FCS studies are mainly performed on single living cells.
To the best of our knowledge, there is no reported in vivo FCS study on intact biological tissues.
At the same time, it was found in the course of the current grant supported research that there is
no existing data for determining the diffusion coefficient for Dpp in wing imaginal disc. In
principle, FCS measurements should be capable of determining rates of diffusion and
concentration in biological tissues. In (Wang 2004), we demonstrate that FCS is in fact feasible
for studying the properties of molecules in intact Drosophila wing imaginal disc tissues. We do
this by conducting FCS measurements of morphogen Dpp-EGFP fusion protein in intact
Drosophila imaginal discs with two-photon excitation at 850 nm. We observed Brownian motion
of Dpp morphogen within the gradient band. In addition, the analysis of the measured
autocorrelation functions with a two-species model indicates that a fraction of the Dpp-EGFP is
involved in a larger complex or a possible anomalous diffusion along the cell membranes. Our
studies demonstrate for the first time that FCS is capable of investigating the molecular dynamics
in intact tissues.
Publications Supported by NIH Grant R01GM067247 (for competitive renewal):
[1] Kao, J.C., Nie, Q., Teng, A., Wan, F.Y.M., Lander, A.D. and Marsh, J.L., Can Morphogen
Activity Be Enhanced by Its Inhibitors? Proc. 2nd MIT Conference on Computational Mechanics
(Cambridge, June), 2003, Pgs 1729-1734.
[2] Lou, Y., Nie, Q. and Wan, F.Y.M., Nonlinear eigenvalue problems in the stability analysis
of morphogen gradients, Studies in Appl. Math. Vol. 113, 2004, 183-215.
[3] Lander, A.D., Nie, Q. and Wan, F.Y.M., Spatially Distributed Morphogen Production and
Morphogen Gradient Formation, Math. Biosci. & Eng. (MBE) 2, 2005, 239 – 262.
[4]. Lander, A.D., Nie, Q., Vargas, B. and Wan, F.Y.M., Aggregation of a distributed ligand
source and morphogen gradients, Studies in Appl. Math. 114, 2005, 343 – 374.
[5] Mizutani, C.M., Nie, Q., Wan, F.Y.M., Zhang, Y.T., Vilmos, P., Bier, E., Marsh, J.L. and
Lander, A.D., Formation of MP activity gradient in the Drosophila embryo, Dev. Cell 8 (No.6),
2005, 915 – 924.
[6] Lou, Y., Nie, Q. and Wan, F.Y.M., Effects of Sog on Dpp-receptor binding, SIAM J. Appl.
Math., 65, 1748 – 1771.
[7] Lander, A.D., Nie, Q. and Wan, F.Y.M., Internalization and end flux in morphogen gradient
formation, J. of Comp. and Appl. Math. (CAM), to appear.
[8] Lander, A.D., Nie, Q. and Wan, F.Y.M., Membrane associated non-receptors and
morphogen gradients, Bulletin of Math. Bio., to appear.
8
[9] Wang, Z., Marcu, O., Berns, M. W., and Marsh, J. L. (2004b). In vivo FCS measurements of
ligand diffusion in intact tissues. Multiphoton Microscopy in the Biomedical Sciences IV,
Proceedings of SPIE 5323, 177-183. (Also, Journal Biomedical Optics 9. In Press.)
[10] Lander, A.D., Wan, F.Y.M., Elledge, H.M., Claudia Mieko Mizutani, C.M., Bier, E. and Nie,
Q., Diverse Paths to Morphogen Gradient Robustness, submitted to PLoS Biology.
References
Cadigan, K. M., Fish, M.P., Rulifson, E.J., and Nusse, R. (1998). "Wingless repression of
Drosoplila frizzled 2 expression shapes the Wingless morphogen gradient in the wing."
Cell 93: 767-777.
Harland, R. M. (2001). "Developmental biology A twist on embryonic signalling."
Nature 410(6827): 423-4.
Jackson, S. M., H. Nakato, et al. (1997). "division abnormally delayed, a Drosophila
glypican, controls cellular responses to the TGF-ß-related morphogen, Dpp."
Development 124: 4113-4120.
Lander, A., Nie, Q. , Wan, F. (2005c). "Internalization and End Flux in Morphogen
Gradient Formation." Accepted, J. of Computational and Applied Math.
Lander, A., Nie, Q. , Vargas, B. Wan, F. (2005b). "Aggregation of Distributed Sources
in Morphogen Gradients Formation." Studies in Applied Mathematics 114(4): 343-374.
Lander, A., Nie,Q. , Wan, F. (2002). "Do morphogen gradients arise by diffusion."
Development Cell 2(6): 785-796.
Lander, A. D., Nie, Q. , Wan, F.Y.M. (2005a). "Spatially Distributed Morphogen
Production and Morphogen Gradient Formation." Mathematical Biosciences and
Engineering 2: 239-262.
Lander, A. D., Nie, Q. and Wan, F.Y.M. (2005d). "Membrane associated non-recptors
and morphogen gradients, Bulletin of Math." Bulletin of Mathematical Biology Accepted
for Publication (http://www.math.uci.edu/~fwan/pdf/BulletinMB.pdf).
Lander, A. D., Wan, F.Y.M., Heather M. Elledge, H.M., Claudia Mieko Mizutani, C.M.,
Bier, E. and Nie, Q. (2005e). "Diverse Paths to Morphogen Gradient Robustness."
Submitted for publication (http://www.math.uci.edu/~fwan/pdf/DivPaths.pdf).
Lander, A. N., Q. , Wan, F., Xu, J. (2003). Diffusion and Morphogen Gradient
Formation. Submitted (http://math.uci.edu/~fwan/pdf/all.pdf): 66 pages.
Lecuit, T. and S. M. Cohen (1998). "Dpp receptor levels contribute to shaping the Dpp
morphogen gradient in the Drosophila wing imaginal disc." Development 125(24): 49017.
9
Axis formation in the Drosophila wing depends on the localized expression of the
secreted signaling molecule Decapentaplegic (Dpp). Dpp acts directly at a
distance to specify discrete spatial domains, suggesting that it functions as a
morphogen. Expression levels of the Dpp receptor thick veins (tkv) are not
uniform along the anterior- posterior axis of the wing imaginal disc. Receptor
levels are low where Dpp induces its targets Spalt and Omb in the wing pouch.
Receptor levels increase in cells farther from the source of Dpp in the lateral
regions of the disc. We present evidence that Dpp signaling negatively regulates
tkv expression and that the level of receptor influences the effective range of the
Dpp gradient. High levels of tkv sensitize cells to low levels of Dpp and also
appear to limit the movement of Dpp outside the wing pouch. Thus receptor levels
help to shape the Dpp gradient.
Lou, Y., Nie, Q., Wan, F. (2004). "Nonlinear Eigenvalue Problems in the Stability
Analysis of Morphogen Gradients." Studies in Applied Mathematics 113: 183-215.
Lou, Y., Nie, Q., Wan, F. (2005). "Effects of Sog on Dpp-Receptor Binding." SIAM J.
Appl. Math. (http://math.uci.edu/~fwan/download/LNW-SIAM.pdf) 65(5): 1748 - 1771.
Marcu, O., Agrawal, N. , Heslip, T. and Marsh, J.L. (2005). "
Syndecan modulates the distribution and signaling of Wingless morphogen
in the Drosophila wing margin." Preprint (http://www.math.uci.edu/~fwan/sdcwg.doc/html).
Mizutani, C., Nie,Q.,Wan, F.,Zhang, Y. ,Vilmos, P. ,Bier, E., Marsh,L., and Lander, A.
(2005). "Formation of the BMP activity gradient in the Drosophila embryo."
Developmental Cell 8(June-6): 1 - 10.
Ray, R. P. and K. A. Wharton (2001). "Twisted Perspective. New Insights into
Extracellular Modulation of BMP Signaling during Development." Cell 104(6): 801-804.
Ross, J. J., O. Shimmi, et al. (2001). "Twisted gastrulation is a conserved extracellular
BMP antagonist." Nature 410(6827): 479-83.
Bone morphogenetic protein (BMP) signalling regulates embryonic dorsalventral cell fate decisions in flies, frogs and fish. BMP activity is controlled by
several secreted factors including the antagonists chordin and short gastrulation
(SOG). Here we show that a second secreted protein, Twisted gastrulation (Tsg),
enhances the antagonistic activity of Sog/chordin. In Drosophila, visualization of
BMP signalling using anti-phospho-Smad staining shows that the tsg and sog
loss-of- function phenotypes are very similar. In S2 cells and imaginal discs, TSG
and SOG together make a more effective inhibitor of BMP signalling than either
of them alone. Blocking Tsg function in zebrafish with morpholino
oligonucleotides causes ventralization similar to that produced by chordin
mutants. Co-injection of sub-inhibitory levels of morpholines directed against
both Tsg and chordin synergistically enhances the penetrance of the ventralized
phenotype. We show that Tsgs from different species are functionally equivalent,
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and conclude that Tsg is a conserved protein that functions with SOG/chordin to
antagonize BMP signalling.
The, I., Y. Bellaiche, et al. (1999). "Hedgehog movement is regulated through tout veludependent synthesis of a heparan sulfate proteoglycan." Mol Cell 4(4): 633-9.
Hedgehog (Hh) molecules play critical roles during development as a morphogen,
and therefore their distribution must be regulated. Hh proteins undergo several
modifications that tether them to the membrane. We have previously identified
tout velu (ttv), a homolog of the mammalian EXT tumor suppressor gene family,
as a gene required for movement of Hh. In this paper, we present in vivo evidence
that ttv is involved in heparan sulfate proteoglycan (HSPG) biosynthesis,
suggesting that HSPGs control Hh distribution. In contrast to mutants in other
HSPG biosynthesis genes, the activity of the HSPG-dependent FGF and Wingless
signaling pathways are not affected in ttv mutants. This demonstrates an
unexpected level of specificity in the regulation of the distribution of extracellular
signals by HSPGs.
Wang, Z., Marcu, O., Berns, M.W. and Marsh, J. L. (2004). "In vivo FCS measurements
of ligand diffusion in intact tissue." J. of Biomedical Optics 9(2).
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