Research conducted in the Haugh Laboratory
Signal Transduction Networks and Quantitative Cell Biology
Quantifying the PDGF receptor signaling network: Pathway crosstalk, feedback regulation
Spatial gradient sensing in fibroblasts: Implications for chemotaxis and wound healing
Spatiotemporal regulation of cell adhesion and migration
Structure-based kinetic models of modular signaling protein function
Signal transduction reactions/interactions at cell membranes
Dynamics of growth hormone receptor, cytokine receptors, and JAK/STAT signaling
Receptor endocytosis and compartmentalized intracellular signaling
Introduction
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. Early work by the Haugh group, largely conducted by PI Haugh as a graduate student, focused on the intracellular compartmentalization of signal transduction mediated by epidermal growth factor (EGF) receptor, which has served as the quintessential model system for quantitative studies of receptor biology and growth factor-stimulated cell signaling. Work in the Haugh Laboratory over the past 10 years has focused on signal transduction mediated by platelet-derived growth factor (PDGF) receptors, growth hormone receptor, interleukin (IL)-2 and IL-4 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.
Quantifying the PDGF receptor signaling network:
Pathway crosstalk, feedback regulationHistorically, 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, and although significant progress has been made in the mechanistic understanding of pathway crosstalk, the current state of knowledge largely rests on hand-waving conceptual models of signaling networks.
Analysis of kinetic data is a time-honored method for quantitatively assessing the mechanisms and relative rates of molecular processes, yet this approach is not routinely used in cell biological research. It requires acquisition of quantitative data and the ability to model intracellular processes in mathematical terms. Initial kinetic studies conducted by the Haugh group centered on PDGF receptor-mediated activation of PI3K signaling, which is relevant for wound healing and cancer progression. We showed that PDGF receptor phosphorylation exhibits positive cooperativity with respect to PDGF concentration and is transient at high PDGF concentrations, consistent with receptor endocytosis. By comparison, Akt activation (a readout of PI3K signaling) responds to lower PDGF concentrations and with more sustained kinetics, consistent with saturation of the pathway. Reconciling these results against live-cell microscopy data (see below) indicated that the pathway is saturated at the level of PI3K recruitment. This analysis has thus yielded quantitative insights as to the mechanisms of PDGF receptor and PI3K/Akt activation, and, more relevant to our recent work, it has afforded us the ability to quantitatively estimate the numbers of activated receptor and PI3K as a function of time and PDGF concentration.
Kinetic analysis of PDGF receptor/PI3K/Akt activation. Quantitative assays, developed in our lab, were used to measure endogenous PDGF receptor phosphorylation and Akt kinase activity as a function of time and PDGF concentration. The solid curves are from a best global fit to a kinetic model of the pathway. Adapted from J. Biol. Chem., 278: 37064 (2003). Building upon the work described above, our recent and ongoing studies in this area are helping to move the field from a pathway-centric to a network-centric paradigm. We recently published a comprehensive mechanistic analysis of the platelet-derived growth factor (PDGF) receptor signaling network, in which the PI3K and Ras/ERK pathways are prominently activated. By systematically canvassing an array of PDGF concentrations, time points, and molecular perturbations (> 3,000 measurements, including replicates), we showed that while PI3K signaling is insulated from crosstalk, PI3K enhances ERK activation both upstream and downstream of Ras. Whereas simultaneously blocking Ras and PI3K abolishes PDGF-stimulated ERK phosphorylation, each pathway makes an independent contribution to ERK activation. Some of these data are presented below, which along with the results shown above demonstrate our capability to measure biochemical readouts reproducibly and with reasonable throughput.
Ras and PI3K make independent contributions to ERK signaling, while PI3K is effectively insulated from crosstalk. Left: PDGF-stimulated ERK phosphorylation is partially inhibited when either Ras or PI3K is inhibited. Right: Corresponding analysis of Akt phosphorylation shows that PI3K is not significantly activated through crosstalk from Ras in this context. Adapted from Mol. Syst. Biol., 5: 246 (2009). Ras and PI3K account for all of the major pathways that converge on ERK. Blocking both Ras and PI3K abolishes PDGF-stimulated ERK phosphorylation. Adapted from Mol. Syst. Biol., 5: 246 (2009). Synthesizing the assembled data, a conceptual model was clear, yet the unique data set allowed for a more quantitative framework through disciplined mathematical modeling. In the context of the model, the magnitudes of the Ras- and PI3K-dependent inputs converging on MEK/ERK determine the saturability of ERK phosphorylation and the degree to which it adapts; conversely, the observed dynamics were used to estimate the magnitudes of the inputs. Adjustable parameters were specified using a Monte Carlo algorithm that directly and globally aligns the model output to the experimental data; thus, an ensemble of 10,000 or more parameter sets that fit the data almost equally well are readily assembled.
We have since refined this approach with additional measurements that push the envelope of data-driven kinetic modeling even further (in preparation). With nearly double the number of data constraints, we have identified and parsed four distinct modes of negative regulation affecting ERK signaling and pinned down with even greater precision the magnitude of crosstalk from PI3K-dependent signaling to the Ras/ERK pathway. The goal now is to map the finer, molecular-level details (which have yet to be measured quantitatively) onto the dynamic, system-level properties that we have characterized.
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)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)
Spatial gradient sensing in fibroblasts:
Implications for chemotaxis and wound healingDuring wound healing, PDGF and other factors released by platelets (and later by macrophages) diffuse into the surrounding tissue, where they stimulate cell responses. Fibroblasts mediate wound repair and closure, and these cells proliferate in response to stimulation and migrate in a directed fashion, invading the wound site by following the gradient of PDGF that forms in the tissue (chemotaxis). Eukaryotic cells sense gradients spatially; that is, the spatial pattern of extracellular cues yields, through activation of receptors, a pattern of intracellular signaling that locally alters cell motility processes. Spatial sensing mechanisms have been actively studied in neutrophils and the slime mold Dictyostelium discoideum, but to our knowledge we are the only group doing quantitative analysis and modeling of fibroblast chemotaxis towards PDGF. The systems are similar in that chemotaxis is governed by 3' phosphoinositides (PIs), products of the aforementioned PI3Ks (although it is now appreciated that PI3K-independent signaling pathways are also involved). Our experimental system involves the real-time imaging of a fluorescent, 3' PI-specific biosensor in living cells using total internal reflection fluorescence (TIRF) microscopy. In many cases, we directly compare the spatiotemporal fluorescence patterns with reaction-diffusion models, using the actual geometry of each cell's contact area. Thus, we extract useful parameter values for each individual cell (apparent 3' PI production rate, diffusion coefficient and turnover rate constant), and more importantly we have studied how these parameters are regulated spatially in response to various cues.
Our work in this area, together with the kinetic analysis of PDGF receptor/PI 3-kinase activation described above, has culminated in an experimentally validated, mechanistic model of PDGF gradient sensing (a comprehensive version of this model is publicly available through the Virtual Cell modeling software). Compared with the chemotactic responses of Dictyostelium discoideum and neutrophils, PDGF gradient sensing in fibroblasts exhibits less sensitivity in general and a greater dependence on the midpoint concentration of the gradient. Optimal gradient sensing is observed in a relatively narrow range of PDGF concentrations that yield near maximal PI 3-kinase recruitment without saturating PDGF receptor occupancy.
Quantitative elucidation of a distinct spatial gradient-sensing mechanism in fibroblasts. Top panels: A simplified version of our PDGF gradient sensing model yields three testable predictions: 1) The PI3K signaling gradient, Δe, is sensitive to both the relative PDGF gradient, δ, and its midpoint concentration, with optimal sensitivity at intermediate concentrations; 2) Given parameter values consistent with the dose responses of PDGF receptor and PI3K activation, the effective PDGF concentration range spans roughly 20-fold; and 3) Near the optimal PDGF concentration, PI3K activation at the front of the cell exceeds the level observed at receptor saturation, and so the subsequent addition of a high PDGF dose forces the 3' PI level at the front to decrease. Bottom panels: Experiments using fluorescent AktPH-transfected mouse fibroblasts and TIRF microscopy are in qualitative and quantitative agreement with the model predictions. Adapted from J. Cell Biol., 171: 883 (2005).
More recently, these cell-level insights have been incorporated into mathematical models of PDGF-mediated fibroblast invasion; these coarse-grain, population-level models (including a hybrid, continuum/stochastic model) explain how robust fibroblast chemotaxis might be maintained over arbitrarily large length scales, across which the PDGF concentration profile might span several logs, given the relatively narrow dose responsiveness of PDGF gradient sensing.
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)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)
(NEW! 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)
Spatiotemporal regulation of cell adhesion and migration
This section is currently under construction. Our publications in this area are listed here:
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)
Structure-based kinetic models of modular signaling protein function
This section is currently under construction. Our publications in this area are listed here:
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)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)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)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, 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)
Signal transduction reactions/interactions at cell membranes
As outlined in the sections above, phosphorylated receptors serve as scaffolds for the recruitment of intracellular enzymes. Nearly all of these enzymes act upon membrane-associated molecules such as lipids or lipid-tethered proteins (as seen in each of the phospholipase C, PI3K, and Ras pathways), suggesting a general theme in intracellular signaling wherein the plasma membrane provides a physical platform for the orchestration of molecular interactions and biochemical conversions involved in the early stages of receptor-mediated signal transduction in living cells. It has long been speculated that the relatively slow diffusion of membrane constituents could give rise to rates of reaction that are limited by the frequency of intermolecular collisions, i.e., diffusion-limited kinetics. In such cases, nanometer-scale gradients of active signaling components would transiently arise in the proximity of a receptor-recruited enzyme; significantly, such gradients currently cannot be detected through direct measurements.
We and others have therefore examined this problem theoretically, following a rich tradition of reaction-diffusion problems in planar geometries. Obviously, our focus has uniquely centered on intracellular signaling (in particular the specific pathways mentioned above), with consideration of the mobility, consumption, and in some cases the regulated insertion of membrane substrates as well as the dynamics of receptor-mediated enzyme recruitment.
Recently, we introduced a conceptual mechanism called spatial coupling, wherein simultaneous recruitment of different enzymes to the same receptor scaffold facilitates crosstalk between different signaling pathways through the local release and capture of activated signaling molecules. To study its spatiotemporal dynamics, we developed a Brownian dynamics-based stochastic modeling approach, benchmarked its performance against continuum theory (for relatively simple systems), and applied it to a specific signaling system: receptor-mediated activation of Ras and the cooperative recruitment of PI3K by activated receptors and Ras. Various analyses of the model simulations show that cooperative assembly of multi-molecular complexes nucleated by activated receptors is facilitated by the local release and capture of membrane-anchored signaling molecules (such as active Ras) from/by receptor-bound signaling proteins. In the case of Ras/PI3K crosstalk, the model predicts that PI3K is more likely to be recruited by activated receptors bound or recently visited by the enzyme that activates Ras. By this mechanism, receptor-bound PI3K is stabilized through short-range, diffusion-controlled capture of active Ras and Ras/PI3K complexes released from the receptor complex. We contend that this mechanism is a means by which signaling pathways are propagated and spatially coordinated for efficient crosstalk between them.
Theoretical models of signaling processes nucleated at cell membranes. Left: Spatial coupling in the context of receptor-mediated recruitment of PI3K, studied through Brownian dynamics simulations. PI3K (P) is more likely to be recruited by receptors bound or recently visited by the enzyme (E) that generates active Ras (black). Adapted from Biophys. J., 95: 2172 (2008).
Below: Subcompartmentalization of the plasma membrane can affect the nature of the activation gradient in the vicinity of a signaling complex. Adapted from Biochem. J., 393: 235 (2006).Most recently, we have begun to explore how membrane "corrals" and other microstructural/microdomain features might influence molecular mobility and thus reaction-diffusion problems that are relevant to signaling processes at cell membranes.
Haugh JM (2009).
Analysis of reaction-diffusion systems with anomalous subdiffusion.
Biophysical Journal, 97: 435-442. (doi:10.1016/j.bpj.2009.05.014)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)
(NEW! Simulation codes and instructions)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)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)
(NEW! Simulation codes and instructions)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 (1997).
Physical modulation of intracellular signaling processes by locational regulation.
Biophysical Journal, 72: 2014-2031. (link)
Dynamics of growth hormone receptor, cytokine receptors,
and JAK/STAT signalingHuman growth hormone (hGH) is a classical pituitary hormone that controls numerous physiological processes, most notably skeletal growth. Structurally and functionally, the interactions of hGH with its receptor have been resolved in fine detail, such that hGH and hGH receptor variants can be practically engineered by either random or rational approaches to achieve significant changes in the free energies of binding. A somewhat unique feature of hGH action is its homodimerization of two hGH receptors, which is required for intracellular signaling and stimulation of cell proliferation. It is well known that such an activation mechanism naturally gives rise to a bell-shaped dose response curve, as higher ligand concentrations progressively decrease the number of unoccupied receptors available for dimerization.
Given the extensive experimental work on this system, it has been used as a model example of receptor dynamics in Prof. Haugh's specialty course, Molecular Cell Engineering. As a direct outcome of in-class discussions, it became clear that certain observations - namely the efficacies of hGH receptor agonists and antagonists in cell-based assays - could not be adequately explained by kinetic models that only considered receptor-ligand interactions. It was subsequently found that a model considering hGH receptor internalization, which imposes a limit on the lifetime of an active receptor complex at the cell surface, is uniformly consistent with the numerous published observations regarding hGH receptor agonism and antagonism.
As described in more detail above, we have more recently used rule-based modeling to study the complexity of JAK2 activation mediated by dimerized growth hormone receptor and the adaptor protein SH2-B.
We have also studied molecular aspects of signaling in T lymphocytes, agents of the immune system that orchestrate the defense against infectious disease. Aside from their obvious importance in human health, the highly specialized and tightly controlled activities of T cells offer a unique test case for the fundamental understanding of cell regulation. We quantified the transient kinetics of the Ras/ERK, PI3K/Akt and JAK/STAT signaling pathways stimulated by the receptor for interleukin (IL)-2, a soluble cytokine that explicitly stimulates proliferation of T cells as the immune system mounts its defense against a specific pathogen, and we analyzed the effects of a second cytokine, IL-4, on IL-2-stimulated signaling and T-cell proliferation.
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)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)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)
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. The Lauffenburger lab had previously analyzed, along with Steven Wiley's group (then at Univ. of Utah), the dyamics of EGF receptor trafficking and the resulting effects on cell proliferation, assuming a phenomenological relationship between receptor occupancy and response. The subsequent analyses of the underlying signaling pathways were undertaken in collaboration with Alan Wells and his group (then at UAB), who had previously elucidated the role of the phospholipase C pathway in EGF-stimulated cell motility. 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.
