Research conducted in the Haugh Laboratory

Signal Transduction Networks and Quantitative Cell Biology


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Quantifying signaling networks: pathway crosstalk and feedback regulation

Directed cell migration: Integration of signaling, adhesion, and cytoskeletal dynamics

Biophysical modeling and simulation

Receptor endocytosis and compartmentalized intracellular signaling

 

In mammalian cell biology, the ongoing challenge is to bridge the gaps in our understanding of processes at the molecular, cellular, and tissue levels. Central to this hierarchy of biological complexity is the field of signal transduction, which deals with the biochemical mechanisms by which cells respond to external stimuli. Intracellular signaling processes control the growth, survival, differentiation and migration of cells in normal physiological contexts, and defects in signaling form the molecular basis for cancer, immune system disorders, and other diseases. Since 2000, the Haugh Laboratory has implemented a quantitative approach that combines biochemical measurements, live-cell fluorescence microscopy, and computational modeling to study signal transduction through analysis of its kinetics and spatial patterns in cells.

A cell's ability to sense, respond, and adapt to external signals is largely mediated by receptor proteins expressed on the cell surface. Receptors are bifunctional in that they are responsible for both molecular recognition of extracellular ligands and signal transduction through interactions with intracellular enzymes and adaptor proteins. Each cell's repertoire of cell surface receptors determines which ligands it responds to, and once activated, most receptors plug into a common set of signal transduction pathways.

Common signaling pathways accessed by cell surface receptors. The arrow diagram is organized both horizontally and vertically as follows. From left to right, the diagram depicts the Ras/MAPK pathway, lipid modification pathways (PI3K and PLC), and activation of Rho-family GTPases. From top to bottom, the diagram depicts receptors, adaptors, receptor-proximal enzymes, membrane-anchored lipids and proteins, and downstream effector kinases. Black arrows indicate recruitment, activation, or production; red arrows indicate negative regulation.

Research in the Haugh Laboratory has focused on signal transduction mediated by platelet-derived growth factor (PDGF) and fibroblast growth factor (FGF) receptors, growth hormone receptor, interleukin (IL)-2 and IL-4 receptors, CXCR chemokine receptors, and integrins. In terms of signaling pathways, a major effort in the lab has been devoted to studying signal transduction through phosphoinositide 3-kinases (PI3Ks), lipid kinases that are centrally involved in cell migration and chemotaxis, cell survival, and cell proliferation. As outlined in more detail below, we have studied the kinetics of PI3K action, its subcellular localization, and its crosstalk with other canonical signaling pathways. Other signaling proteins and pathways studied by the Haugh group include Ras and its activation of mitogen-activated protein kinase (MAPK) cascades, phospholipase C (PLC), protein-tyrosine phosphatases, Rho-family GTPases, and JAK-STAT signaling. In the context of cell migration, we are keenly interested in integrating signaling dynamics with those of adhesion and the actin cytoskeleton.

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Quantifying signaling networks: pathway crosstalk and feedback regulation

Historically, intracellular signal transduction has been characterized in terms of linear pathways, exemplified by the canonical MAPK cascades; e.g., the Ras → Raf → MEK → extracellular signal-regulated kinase (ERK) pathway in mammals. Yet it has been appreciated for some time that so-called signaling "pathways" are seldom activated or regulated in isolation. Indeed, it is well understood that they are simply dominant routes of regulation embedded in larger networks of interactions, including those between classically defined pathways (crosstalk) and those responsible for feedback regulation/reinforcement. But simply identifying the topology of the network is not enough; the magnitudes and dynamics of the interactions must be characterized, and this analysis must be performed for a spectrum of cell types and contexts. To do this, it is clear that a more quantitative approach is sorely needed.

Our approach in this area typically combines quantitative measurements and kinetic modeling, with the goal of elucidating the important crosstalk and feedback interactions in signaling networks mediated by growth factor and cytokine receptors. Publications selected from this line of research are listed below.

Herring LE, Grant KG, Blackburn K, Haugh JM, Goshe MB (2015).
Development of a tandem affinity phosphoproteomic method with motif
selectivity and its application in analysis of signal transduction networks.
Journal of Chromatography B, 988: 166-174. (doi:10.1016/j.jchromb.2015.02.017)

Rahman A, Haugh JM (2014).
Deactivation of a negative regulator: a distinct signal transduction mechanism,
pronounced in Akt signaling.
Biophysical Journal, 107: L29-L32. (doi:10.1016/j.bpj.2014.10.003)

Ahmed S, Grant KG, Edwards LE, Rahman A, Cirit M, Goshe MB, Haugh JM (2014).
Data-driven modeling reconciles kinetics of ERK phosphorylation, localization,
and activity states.
Molecular Systems Biology, 10: 718 (14 pages). (doi:10.1002/msb.134708)

Cirit M, Grant KG, Haugh JM (2012).
Systemic perturbation of the ERK signaling pathway by the
proteasome inhibitor, MG132.
PLOS ONE, 7: e50975. (doi:10.1371/journal.pone.0050975)

Haugh JM (2012).
Cell regulation: a time to signal, a time to respond.
BioEssays, 34: 528-529 (Comment). (doi:10.1002/bies.201200077)

Cirit M, Haugh JM (2012).
Data-driven modelling of receptor tyrosine kinase signalling networks quantifies
receptor-specific potencies of PI3K- and Ras-dependent ERK activation.
Biochemical Journal, 441: 77-85. (doi:10.1042/BJ20110833)

Cirit M, Haugh JM (2011).
Quantitative models of signal transduction networks: How detailed should they be?
Communicative & Integrative Biology, 4: 353-356 (Addendum Article). (doi:10.4161/cib.4.3.15149)

Buhrman G, Kumar VSS, Cirit M, Haugh JM, Mattos C (2011).
Allosteric modulation of Ras-GTP is linked to signal transduction through Raf kinase.
Journal of Biological Chemistry, 286: 3323-3331. (doi:10.1074/jbc.M110.193854)

Cirit M, Wang C-C, Haugh JM (2010).
Systematic quantification of negative feedback mechanisms in the
extracellular signal-regulated kinase (ERK) signaling network.
Journal of Biological Chemistry, 285: 36736-36744. (doi:10.1074/jbc.M110.148759)

Wang C-C, Cirit M, Haugh JM (2009).
PI3K-dependent crosstalk interactions converge with Ras as quantifiable inputs
integrated by Erk.
Molecular Systems Biology, 5: art. 246 (11 pages). (doi:10.1038/msb.2009.4)

Comfort KK, Haugh JM (2008).
Combinatorial signal transduction responses mediated by interleukin-2 and -4 receptors
in a helper TH2 cell line.
Cellular and Molecular Bioengineering, 1: 163-172. (doi:10.1007/s12195-008-0015-9)

Monine MI, Haugh JM (2008).
Signal transduction at point-blank range: analysis of a spatial coupling mechanism
for pathway crosstalk.
Biophysical Journal, 95: 2172-2182. (doi:10.1529/biophysj.108.128892)

Kaur H, Park CS, Lewis JM, Haugh JM (2006).
Quantitative model of Ras/phosphoinositide 3-kinase signalling cross-talk
based on co-operative molecular assembly.
Biochemical Journal, 393: 235-243. (doi:10.1042/BJ20051022)

Park CS, Schneider IC, Haugh JM (2003).
Kinetic analysis of platelet-derived growth factor receptor/phosphoinositide 3-kinase/Akt
signaling in fibroblasts.
Journal of Biological Chemistry, 278: 37064-37072. (link)

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Directed cell migration: Integration of signaling, adhesion,
and cytoskeletal dynamics

We and other multicellular organisms are evolved with the amazing ability to heal. Similar to the way our bodies respond to infection, wound healing involves the recruitment of specific cells between tissues, i.e., directed cell migration. Another, more insidious example of the same basic process is the exodus of cancer cells from primary tumors. The migration of a select subpopulation of invasive cancer cells results in the colonization of secondary tumors (metastasis), leading many to characterize cancer as a 'cell migration disease'.

Research in the Haugh laboratory has focused primarily on migration of fibroblasts, which is directed by both chemical and physical cues during wound healing. Especially recently, we have also studied cancer cell and lymphocyte (T and B cell) migration. Our approach in this area of research centers on live-cell microscopy, interrogating dynamics of signaling, adhesion, and cytoskeletal processes; when warranted, the analysis of these measurements is integrated with computational methods and biophysical models. Publications selected from this line of research are listed below.
 

Johnson HE, Haugh JM (2016).
Are filopodia privileged signaling structures in migrating cells?
Biophysical Journal, 111: 1827-1830. (doi:10.1016/j.bpj.2016.09.022)

Liu X, Asokan SB, Bear JE, Haugh JM (2016).
Quantitative analysis of B-lymphocyte migration directed by CXCL13.
Integrative Biology, 8: 894-903. (doi:10.1039/c6ib00128a)

King SJ, Asokan SB, Haynes EM, Zimmerman SP, Rotty JD, Alb JG Jr, Tagliatela A, Blake DR, Lebedeva IP, Marston D, Johnson HE, Parsons M, Sharpless NE, Kuhlman B,
Haugh JM, Bear JE (2016).
Lamellipodia are crucial for haptotactic sensing and response.
Journal of Cell Science, 129: 2329-2342. (doi:10.1242/jcs.184507)

Haynes EM, Asokan SB, King SJ, Johnson HE, Haugh JM, Bear JE (2015).
GMFβ controls branched actin content and lamellipodial retraction in fibroblasts.
Journal of Cell Biology, 209: 803-812. (doi:10.1083/jcb.201501094)

Liu X, Welf ES, Haugh JM (2015).
Linking morphodynamics and directional persistence of T lymphocyte migration.
Journal of the Royal Society Interface, 12: pii:20141412. (doi:10.1098/rsif.2014.1412)

Johnson HE, King SJ, Asokan SB, Rotty JD, Bear JE, Haugh JM (2015).
F-actin bundles direct the initiation and orientation of lamellipodia
through adhesion-based signaling.
Journal of Cell Biology, 208: 443-455. (doi:10.1083/jcb.201406102)
Featured in the biosights podcast series and JCB journal club

Rotty JD, Wu C, Haynes EM, Winkelman JD, Suarez C, Johnson HE, Haugh JM,
Kovar DR, Bear JE (2015).
Profilin-1 serves as a gatekeeper for actin assembly by Arp2/3-dependent
and -independent pathways.
Developmental Cell, 32: 54-67. (doi:10.1016/j.devcel.2014.10.026)

Asokan SB, Johnson HE, Rahman A, King SJ, Rotty JD, Lebedeva I, Haugh JM,
Bear JE (2014).
Mesenchymal chemotaxis requires selective inactivation of Myosin II
at the leading edge via a non-canonical PLCγ/PKCα pathway.
Developmental Cell, 31: 747-760. (doi:10.1016/j.devcel.2014.10.024)

Vernekar VN, Wallace CS, Wu M, Chao JT, O'Connor S, Raleigh A, Liu X,
Haugh JM, Reichert WM (2014).
Bi-ligand surfaces with oriented and patterned protein for real-time tracking
of cell migration.
Colloids and Surfaces B: Biointerfaces, 123: 225-235. (doi:10.1016/j.colsurfb.2014.09.020)

Bear JE, Haugh JM (2014).
Directed migration of mesenchymal cells: where signaling and
the cytoskeleton meet.
Current Opinion in Cell Biology, 30C: 74-82. (doi:10.1016/j.ceb.2014.06.005)

Johnson HE, Haugh JM (2013).
Quantitative analysis of phosphoinositide 3-kinase (PI3K) signaling using live-cell
total internal reflection fluorescence (TIRF) microscopy.
Current Protocols in Cell Biology, 61: 14.14.1-24 (Methods Article). (doi:10.1002/0471143030.cb1414s61)

Welf ES, Johnson HE, Haugh JM (2013).
Bidirectional coupling between integrin-mediated signaling and actomyosin mechanics explains matrix-dependent intermittency of leading-edge motility.
Molecular Biology of the Cell, 24: 3945-3955. (doi:10.1091/mbc.E13-06-0311)

Ott LE, Sung EJ, Melvin AT, Sheats MK, Haugh JM, Adler KB, Jones SL (2013).
Fibroblast migration is regulated by Myristoylated Alanine-Rich C-Kinase Substrate
(MARCKS) protein.
PLOS ONE, 8: e66512. (doi:10.1371/journal.pone.0066512)

Haugh JM (2012).
Live-cell fluorescence microscopy with molecular biosensors:
What are we really measuring?
Biophysical Journal, 102: 2003-2011 (featured article). (doi:10.1016/j.bpj.2012.03.055)
Featured in the Biophysical Journal best of 2012 issue

Welf ES, Ahmed S, Johnson, HE, Melvin AT, Haugh JM (2012).
Migrating fibroblasts reorient directionality by a metastable,
PI3K-dependent mechanism.
Journal of Cell Biology, 197: 105-114. (doi:10.1083/jcb.201108152)
Featured in the biosights podcast series and JCB journal club

Welf ES, Haugh JM (2012).
Stochastic models of cell protrusion arising from spatiotemporal signaling
and adhesion dynamics.
Methods in Cell Biology, 110: 223-241 (Methods Article). (doi:10.1016/B978-0-12-388403-9.00009-6)

Melvin AT, Welf ES, Wang Y, Irvine DJ, Haugh JM (2011).
In chemotaxing fibroblasts, both high-fidelity and weakly biased cell movements
track the localization of PI3K signaling.
Biophysical Journal, 100: 1893-1901 (featured article). (doi:10.1016/j.bpj.2011.02.047)

Ahmed S, Yang H, Ozcam AE, Efimenko K, Weiger MC, Genzer J, Haugh JM (2011).
Poly(vinylmethylsiloxane) elastomer networks as functional materials for
cell adhesion and migration studies.
Biomacromolecules, 12: 1265-1271. (doi:10.1021/bm101549y)

Welf ES, Haugh JM (2011).
Signaling pathways that control cell migration: models and analysis.
Wiley Interdisciplinary Reviews Systems Biology & Medicine, 3: 231-240
(Focused Review). (doi:10.1002/wsbm.110)

Cirit M, Krajcovic M, Choi CK, Welf ES, Horwitz AF, Haugh JM (2010).
Stochastic model of integrin-mediated signaling and adhesion dynamics
at the leading edges of migrating cells.
PLOS Computational Biology, 6: e1000688. (doi:10.1371/journal.pcbi.1000688)

Welf ES, Haugh JM (2010).
Stochastic dynamics of membrane protrusion mediated by the DOCK180/Rac
pathway in migrating cells.
Cellular and Molecular Bioengineering, 3: 30-39. (doi:10.1007/s12195-010-0100-8)

Weiger MC, Ahmed S, Welf ES, Haugh JM (2010).
Directional persistence of cell migration coincides with stability of
asymmetric intracellular signaling.
Biophysical Journal, 98: 67-75 (featured article). (doi:10.1016/j.bpj.2009.09.051)

Weiger MC, Wang C-C, Krajcovic M, Melvin AT, Rhoden JJ, Haugh JM (2009).
Spontaneous phosphoinositide 3-kinase signaling dynamics drive spreading
and random migration of fibroblasts.
Journal of Cell Science, 122: 313-323. (doi:10.1242/jcs.037564)

Monine MI, Haugh JM (2008).
Cell population-based model of dermal wound invasion with heterogeneous
intracellular signaling properties.
Cell Adhesion & Migration, 2: 137-145. (link)
(Simulation codes and instructions)

Schneider IC, Haugh JM (2006).
Mechanisms of gradient sensing and chemotaxis: conserved pathways, diverse regulation.
Cell Cycle, 5: 1130-1134 (Extra View). (link)

Haugh JM, Schneider IC (2006).
Effectiveness factor for spatial gradient sensing in living cells.
Chemical Engineering Science, 61: 5603-5611. (doi:10.1016/j.ces.2006.04.041)

Haugh JM (2006).
Deterministic model of dermal wound invasion incorporating receptor-mediated
signal transduction and spatial gradient sensing.
Biophysical Journal, 90: 2297-2308. (doi:10.1529/biophysj.105.077610)

Schneider IC, Haugh JM (2005).
Quantitative elucidation of a distinct spatial gradient-sensing mechanism in fibroblasts.
Journal of Cell Biology, 171: 883-892. (doi:10.1083/jcb.200509028)

Schneider IC, Parrish EM, Haugh JM (2005).
Spatial analysis of 3' phosphoinositide signaling in living fibroblasts, III:
Influence of cell morphology and morphological polarity.
Biophysical Journal, 89: 1420-1430. (doi:10.1529/biophysj.105.061218)

Schneider IC, Haugh JM (2004).
Spatial analysis of 3' phosphoinositide signaling in living fibroblasts: II.
Parameter estimates for individual cells from experiments.
Biophysical Journal, 86: 599-608. (link)

Haugh JM, Schneider IC (2004).
Spatial analysis of 3' phosphoinositide signaling in living fibroblasts: I.
Uniform stimulation model and bounds on dimensionless groups.
Biophysical Journal, 86: 589-598. (link)

Haugh JM, Codazzi F, Teruel M, Meyer T (2000).
Spatial sensing in fibroblasts mediated by 3' phosphoinositides.
Journal of Cell Biology, 151: 1269-1279. (link)

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Biophysical modeling and simulation

Most often, our research tightly integrates experiments and mathematical modeling; however, just as there are cases where a system is accessible experimentally, but knowledge is lacking to build a proper model, there are other instances where modeling and simulation stand alone. For example, a number of our studies have tackled questions concerning the assembly of multi-molecular complexes both in the cytosol and at membranes, and the nanoscale concentration gradients associated with those processes. In that context, experimental measurements are simply not yet informative enough. In other cases, experimental results are already reported in the literature, but a simple model provides an explanation, insight, or alternative interpretation. Publications that embody this style of research are listed below.
 

Rahman A, Haugh JM (2014).
Deactivation of a negative regulator: a distinct signal transduction mechanism,
pronounced in Akt signaling.
Biophysical Journal, 107: L29-L32. (doi:10.1016/j.bpj.2014.10.003)

Welf ES, Johnson HE, Haugh JM (2013).
Bidirectional coupling between integrin-mediated signaling and actomyosin mechanics explains matrix-dependent intermittency of leading-edge motility.
Molecular Biology of the Cell, 24: 3945-3955. (doi:10.1091/mbc.E13-06-0311)

Haugh JM (2012).
Live-cell fluorescence microscopy with molecular biosensors:
What are we really measuring?
Biophysical Journal, 102: 2003-2011 (featured article). (doi:10.1016/j.bpj.2012.03.055)
Featured in the Biophysical Journal best of 2012 issue

Welf ES, Haugh JM (2012).
Stochastic models of cell protrusion arising from spatiotemporal signaling
and adhesion dynamics.
Methods in Cell Biology, 110: 223-241 (Methods Article). (doi:10.1016/B978-0-12-388403-9.00009-6)

Chylek LA, Hu B, Blinov ML, Emonet T, Faeder JR, Goldstein B, Gutenkunst RN,
Haugh JM, Lipniacki T, Posner RG, Yang J, Hlavacek WS (2011).
Guidelines for visualizing and annotating rule-based models.
Molecular BioSystems, 7: 2779-2795. (doi:10.1039/C1MB05077J)

Cirit M, Krajcovic M, Choi CK, Welf ES, Horwitz AF, Haugh JM (2010).
Stochastic model of integrin-mediated signaling and adhesion dynamics
at the leading edges of migrating cells.
PLOS Computational Biology, 6: e1000688. (doi:10.1371/journal.pcbi.1000688)

Welf ES, Haugh JM (2010).
Stochastic dynamics of membrane protrusion mediated by the DOCK180/Rac
pathway in migrating cells.
Cellular and Molecular Bioengineering, 3: 30-39. (doi:10.1007/s12195-010-0100-8)

Haugh JM (2009).
Analysis of reaction-diffusion systems with anomalous subdiffusion.
Biophysical Journal, 97: 435-442. (doi:10.1016/j.bpj.2009.05.014)

Barua D, Faeder JR, Haugh JM (2009).
A bipolar clamp mechanism for activation of Jak-family protein tyrosine kinases.
PLOS Computational Biology, 5: e1000364 (9 pages). (doi:10.1371/journal.pcbi.1000364)

Monine MI, Haugh JM (2008).
Cell population-based model of dermal wound invasion with heterogeneous
intracellular signaling properties.
Cell Adhesion & Migration, 2: 137-145. (link)
(Simulation codes and instructions)

Barua D, Faeder JR, Haugh JM (2008).
Computational models of tandem Src homology 2 domain interactions and application to phosphoinositide 3-kinase.
Journal of Biological Chemistry, 283: 7338-7345. (doi:10.1074/jbc.M708359200)

Monine MI, Haugh JM (2008).
Signal transduction at point-blank range: analysis of a spatial coupling mechanism
for pathway crosstalk.
Biophysical Journal, 95: 2172-2182. (doi:10.1529/biophysj.108.128892)
(Simulation codes and instructions)

Barua D, Faeder JR, Haugh JM (2007).
Structure-based kinetic models of modular signaling protein function: focus on Shp2.
Biophysical Journal, 92: 2290-2300. (doi:10.1529/biophysj.106.093484)

Haugh JM, Schneider IC (2006).
Effectiveness factor for spatial gradient sensing in living cells.
Chemical Engineering Science, 61: 5603-5611. (doi:10.1016/j.ces.2006.04.041)

Haugh JM (2006).
Deterministic model of dermal wound invasion incorporating receptor-mediated
signal transduction and spatial gradient sensing.

Monine MI, Haugh JM (2005).
Reactions on cell membranes: Comparison of continuum theory and
Brownian dynamics simulations.
Journal of Chemical Physics, 123: art. 074908 (6 pages). (doi:10.1063/1.2000236)
(Simulation codes and instructions)

Haugh JM (2004).
A mathematical model of human growth hormone (hGH)-stimulated cell proliferation explains
the efficacy of hGH variants as receptor agonists or antagonists.
Biotechnology Progress, 20: 1337-1344. (doi:10.1021/bp0499101)

Haugh JM, Schneider IC, Lewis JM (2004).
On the cross-regulation of protein tyrosine phosphatases and receptor tyrosine kinases
in intracellular signaling.
Journal of Theoretical Biology, 230: 119-132. (doi:10.1016/j.jtbi.2004.04.023)

Haugh JM (2002).
A unified model for signal transduction reactions in cellular membranes.
Biophysical Journal, 82: 591-604. (link)

Haugh JM, Wells A, Lauffenburger DA (2000).
Mathematical modeling of epidermal growth factor receptor signaling through the phospholipase C pathway: mechanistic insights and predictions for molecular interventions.
Biotechnology & Bioengineering, 70: 225-238. (link)

Haugh JM, Lauffenburger DA (1998).
Analysis of receptor internalization as a mechanism for modulating signal transduction.
Journal of Theoretical Biology, 195: 187-218. (doi:10.1006/jtbi.1998.0791)

Haugh JM, Lauffenburger DA (1997).
Physical modulation of intracellular signaling processes by locational regulation.
Biophysical Journal, 72: 2014-2031. (link)

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Receptor endocytosis and compartmentalized intracellular signaling

For his graduate thesis, Prof. Haugh studied the effects of epidermal growth factor (EGF) receptor internalization on the magnitude and specificity of intracellular signaling. This topic is currently not a major focus of our laboratory, but the interested reader is referred to the following publications.
 

Haugh JM (2002).
Localization of receptor-mediated signal transduction pathways: the inside story.
Molecular Interventions, 2: 292-307 (Review). (link)

Haugh JM, Meyer T (2002).
Active EGF receptors have limited access to PI(4,5)P2 in endosomes:
implications for phospholipase C and PI 3-kinase signaling.
Journal of Cell Science, 115: 303-310. (link)

Haugh JM, Huang AC, Wiley HS, Wells A, Lauffenburger DA (1999).
Internalized epidermal growth factor receptors participate in the activation of p21(ras) in fibroblasts.
Journal of Biological Chemistry, 274: 34350-34360. (link)

Haugh JM, Schooler K, Wells A, Wiley HS, Lauffenburger DA (1999).
Effect of epidermal growth factor receptor internalization on regulation of the
phospholipase C-γ1 signaling pathway.
Journal of Biological Chemistry, 274: 8958-8965. (link)

Haugh JM, Lauffenburger DA (1998).
Analysis of receptor internalization as a mechanism for modulating signal transduction.
Journal of Theoretical Biology, 195: 187-218. (doi:10.1006/jtbi.1998.0791)

Lauffenburger, D.A., Fallon, E.F. and Haugh, J.M. (1998).
Scratching the (cell) surface: cytokine engineering for improved ligand/receptor trafficking dynamics.
Chemistry & Biology, 5: R257-R263 (Review). (doi:10.1016/S1074-5521(98)90110-7)

 


Cartoon of compartmentalized receptor signaling, most resembling the epidermal growth factor (EGF) receptor system. Hydrolysis and phosphorylation of phosphatidylinositol (4,5)-bisphosphate (PIP2) by phospholipase C (PLC) and phosphoinositide 3-kinase (PI3K), respectively, are restricted to the plasma membrane. Internalized receptors, insofar as they remain ligated, retain the ability to recruit those enzymes, but PIP2 is not accessible to them in endosomal membranes. On the other hand, surface and internalized receptor-ligand complexes contribute equally to the production of Ras-GTP. Adapted from the Molecular Interventions review.

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