Orchestration of ErbB3 signaling through heterointeractions and homointeractions

Multiscale imaging and quantitative analysis of plasma membrane protein-cortical actin interplay

The spatiotemporal organization of cell surface receptors is important for cell signaling. Cortical actin (CA), the subset of the actin cytoskeleton subjacent to the plasma membrane (PM), plays a large role in cell surface receptor organization. However, this has been shown largely through actin perturbation experiments, which raise concerns of nonspecific effects and preclude quantification of actin architecture and dynamics under unperturbed conditions. These limitations make it challenging to predict how changes in CA properties can affect receptor organization. To derive direct relationships between the architecture and dynamics of CA and the spatiotemporal organization of PM proteins, including cell surface receptors, we developed a multiscale imaging and computational analysis framework based on the integration of single-molecule imaging (SMI) of PM proteins and fluorescent speckle microscopy (FSM) of CA (combined: SMI-FSM) in the same live cell. SMI-FSM revealed differential relationships between PM proteins and CA based on the PM proteins' actin binding ability, diffusion type, and local CA density. Combining SMI-FSM with subcellular region analysis revealed differences in CA dynamics that were predictive of differences in PM protein mobility near ruffly cell edges versus closer to the cell center. SMI-FSM also highlighted the complexity of cell-wide actin perturbation, where we found that global changes in actin properties caused by perturbation were not necessarily reflected in the CA properties near PM proteins, and that the changes in PM protein properties upon perturbation varied based on the local CA environment. Given the widespread use of SMI as a method to study the spatiotemporal organization of PM proteins and the versatility of SMI-FSM, we expect it to be widely applicable to enable future investigation of the influence of CA architecture and dynamics on different PM proteins, especially in the context of actin-dependent cellular processes.

Multiscale imaging and quantitative analysis of plasma membrane protein-cortical actin interplay

The spatiotemporal organization of cell surface receptors is important for cell signaling. Cortical actin (CA), the subset of the actin cytoskeleton subjacent to the plasma membrane (PM), plays a large role in cell surface receptor organization. This was however shown largely through actin perturbation experiments, which raise concerns of nonspecific effects and preclude quantification of actin architecture and dynamics under unperturbed conditions. These limitations make it challenging to predict how changes in CA properties can affect receptor organization. To derive direct relationships between the architecture and dynamics of CA and the spatiotemporal organization of PM proteins, including cell surface receptors, we developed a multiscale imaging and computational analysis framework based on the integration of single-molecule imaging (SMI) of PM proteins and fluorescent speckle microscopy (FSM) of CA (combined: SMI-FSM) in the same live cell. SMI-FSM revealed differential relationships between PM proteins and CA based on the PM proteins’ actin binding ability, diffusion type and local CA density. It also highlighted the complexity of cell wide actin perturbation, where we found that global changes in actin properties caused by perturbation were not necessarily reflected in the CA properties near PM proteins, and the changes in PM protein properties upon perturbation varied based on the local CA environment. Given the widespread use of SMI as a method to study the spatiotemporal organization of PM proteins and the versatility of SMI-FSM, we expect it to be widely applicable to enable future investigation of the influence of CA architecture and dynamics on different PM proteins, especially in the context of actin-dependent cellular processes, such as cell migration.

Significance

Plasma membrane protein organization, an important factor for shaping cellular behaviors, is influenced by cortical actin, the subset of the actin cytoskeleton near the plasma membrane. Yet it is challenging to directly and quantitatively probe this influence. Here, we developed an imaging and analysis approach that combines single-molecule imaging, fluorescent speckle microscopy and computational statistical analysis to characterize and correlate the spatiotemporal organization of plasma membrane proteins and cortical actin. Our approach revealed different relationships between different proteins and cortical actin, and highlighted the complexity of interpreting cell wide actin perturbation experiments. We expect this approach to be widely used to study the influence of cortical actin on different plasma membrane components, especially in actin-dependent processes.

Spatial Stochastic Model of the Pre-B Cell Receptor

Survival and proliferation of immature B lymphocytes requires expression and tonic signaling of the pre-B cell receptor (pre-BCR). This low level, ligand-independent signaling is likely achieved through frequent, but short-lived, homo interactions. Tonic signaling is also central in the pathology of precursor B acute lymphoblastic leukemia (B-ALL). In order to understand how repeated, transient events can lead to sustained signaling and to assess the impact of receptor accumulation induced by the membrane landscape, we developed a spatial stochastic model of receptor aggregation and downstream signaling events. Our rule- and agent-based model builds on previous mature BCR signaling models and incorporates novel parameters derived from single particle tracking of pre-BCR on surfaces of two different B-ALL cell lines, 697 and Nalm6. Live cell tracking of receptors on the two cell lines revealed characteristic differences in their dimer dissociation rates and diffusion coefficients. We report here that these differences affect pre-BCR aggregation and consequent signal initiation events. Receptors on Nalm6 cells, which have a lower off-rate and lower diffusion coefficient, more frequently form higher order oligomers than pre-BCR on 697 cells, resulting in higher levels of downstream phosphorylation in the Nalm6 cell line.

Signalling dynamics, cell decisions, and homeostatic control in health and disease

Cell signalling engenders cells with the capability to receive and process information from the intracellular and extracellular environments, trigger and execute biological responses, and communicate with each other. Ultimately, cell signalling is responsible for maintaining homeostasis at the cellular, tissue and systemic level. For this reason, cell signalling is a topic of intense research efforts aimed to elucidate how cells coordinate transitions between states in developing and adult organisms in physiological and pathological conditions. Here, we review current knowledge of how cell signalling operates at multiple spatial and temporal scales, focusing on how single-cell analytical techniques reveal mechanisms underpinning cell-to-cell variability, signalling plasticity, and collective cellular responses.

Modeling the Cluster Size Distribution of Vascular Endothelial Growth Factor (VEGF) Receptors

We previously developed a method of defining receptor clusters in the membrane based on mutual distance and applied it to a set of transmission microscopy images of vascular endothelial growth factor receptors. An optimal length parameter was identified, resulting in cluster identification and a procedure that assigned a geometric shape to each cluster. We showed that the observed particle distribution results were consistent with the random placement of receptors within the clusters and, to a lesser extent, the random placement of the clusters on the cell membrane. Here, we develop and validate a stochastic model of clustering, based on a hypothesis of preexisting domains that have a high affinity for receptors. The proximate objective is to clarify the mechanism behind cluster formation and to estimate the effect on signaling. Receptor-enriched domains may significantly impact signaling pathways that rely on ligand-induced dimerization of receptors. We define a simple statistical model, based on the preexisting domain hypothesis, to predict the probability distribution of cluster sizes. The process yielded sets of parameter values that can readily be used in dynamical calculations as the estimates of the quantitative characteristics of the clustering domains.

It Takes More than Two to Tango: Complex, Hierarchal, and Membrane-Modulated Interactions in the Regulation of Receptor Tyrosine Kinases

The search for an understanding of how cell fate and motility are regulated is not a purely scientific undertaking, but it can also lead to rationally designed therapies against cancer. The discovery of tyrosine kinases about half a century ago, the subsequent characterization of certain transmembrane receptors harboring tyrosine kinase activity, and their connection to the development of human cancer ushered in a new age with the hope of finding a treatment for malignant diseases in the foreseeable future. However, painstaking efforts were required to uncover the principles of how these receptors with intrinsic tyrosine kinase activity are regulated. Developments in molecular and structural biology and biophysical approaches paved the way towards better understanding of these pathways. Discoveries in the past twenty years first resulted in the formulation of textbook dogmas, such as dimerization-driven receptor association, which were followed by fine-tuning the model. In this review, the role of molecular interactions taking place during the activation of receptor tyrosine kinases, with special attention to the epidermal growth factor receptor family, will be discussed. The fact that these receptors are anchored in the membrane provides ample opportunities for modulatory lipid-protein interactions that will be considered in detail in the second part of the manuscript. Although qualitative and quantitative alterations in lipids in cancer are not sufficient in their own right to drive the malignant transformation, they both contribute to tumor formation and also provide ways to treat cancer. The review will be concluded with a summary of these medical aspects of lipid-protein interactions.

EGFR transactivates RON to drive oncogenic crosstalk

Crosstalk between different receptor tyrosine kinases (RTKs) is thought to drive oncogenic signaling and allow therapeutic escape. EGFR and RON are two such RTKs from different subfamilies, which engage in crosstalk through unknown mechanisms. We combined high-resolution imaging with biochemical and mutational studies to ask how EGFR and RON communicate. EGF stimulation promotes EGFR-dependent phosphorylation of RON, but ligand stimulation of RON does not trigger EGFR phosphorylation – arguing that crosstalk is unidirectional. Nanoscale imaging reveals association of EGFR and RON in common plasma membrane microdomains. Two-color single particle tracking captured formation of complexes between RON and EGF-bound EGFR. Our results further show that RON is a substrate for EGFR kinase, and that transactivation of RON requires formation of a signaling competent EGFR dimer. These results support a role for direct EGFR/RON interactions in propagating crosstalk, such that EGF-stimulated EGFR phosphorylates RON to activate RON-directed signaling.

Identification of Predictive ERBB Mutations by Leveraging Publicly Available Cell Line Databases

Although targeted therapies can be effective for a subgroup of patients, identification of individuals who benefit from the treatments is challenging. At the same time, the predictive significance of the majority of the thousands of mutations observed in the cancer tissues remains unknown. Here, we describe the identification of novel predictive biomarkers for ERBB-targeted tyrosine kinase inhibitors (TKIs) by leveraging the genetic and drug screening data available in the public cell line databases: Cancer Cell Line Encyclopedia, Genomics of Drug Sensitivity in Cancer, and Cancer Therapeutics Response Portal. We assessed the potential of 412 ERBB mutations in 296 cell lines to predict responses to 10 different ERBB-targeted TKIs. Seventy-six ERBB mutations were identified that were associated with ERBB TKI sensitivity comparable with non-small cell lung cancer cell lines harboring the well-established predictive EGFR L858R mutation or exon 19 deletions. Fourteen (18.4%) of these mutations were classified as oncogenic by the cBioPortal database, whereas 62 (81.6%) were regarded as novel potentially predictive mutations. Of the nine functionally validated novel mutations, EGFR Y1069C and ERBB2 E936K were transforming in Ba/F3 cells and demonstrated enhanced signaling activity. Mechanistically, the EGFR Y1069C mutation disrupted the binding of the ubiquitin ligase c-CBL to EGFR, whereas the ERBB2 E936K mutation selectively enhanced the activity of ERBB heterodimers. These findings indicate that integrating data from publicly available cell line databases can be used to identify novel, predictive nonhotspot mutations, potentially expanding the patient population benefiting from existing cancer therapies.

Multisite EGFR phosphorylation is regulated by adaptor protein abundances and dimer lifetimes

Differential epidermal growth factor receptor (EGFR) phosphorylation is thought to couple receptor activation to distinct signaling pathways. However, the molecular mechanisms responsible for biased signaling are unresolved due to a lack of insight into the phosphorylation patterns of full-length EGFR. We extended a single-molecule pull-down technique previously used to study protein-protein interactions to allow for robust measurement of receptor phosphorylation. We found that EGFR is predominantly phosphorylated at multiple sites, yet phosphorylation at specific tyrosines is variable and only a subset of receptors share phosphorylation at the same site, even with saturating ligand concentrations. We found distinct populations of receptors as soon as 1 min after ligand stimulation, indicating early diversification of function. To understand this heterogeneity, we developed a mathematical model. The model predicted that variations in phosphorylation are dependent on the abundances of signaling partners, while phosphorylation levels are dependent on dimer lifetimes. The predictions were confirmed in studies of cell lines with different expression levels of signaling partners, and in experiments comparing low- and high-affinity ligands and oncogenic EGFR mutants. These results reveal how ligand-regulated receptor dimerization dynamics and adaptor protein concentrations play critical roles in EGFR signaling.

Homo- and Heteroassociations Drive Activation of ErbB3

Dimerization or the formation of higher-order oligomers is required for the activation of ErbB receptor tyrosine kinases. The heregulin (HRG) receptor, ErbB3, must heterodimerize with other members of the family, preferentially ErbB2, to form a functional signal transducing complex. Here, we applied single molecule imaging capable of detecting long-lived and mobile associations to measure their stoichiometry and mobility and analyzed data from experiments globally, taking the different lateral mobility of monomeric and dimeric molecular species into account. Although ErbB3 was largely monomeric in the absence of stimulation and ErbB2 co-expression, a small fraction was present as constitutive homodimers exhibiting a ∼40% lower mobility than monomers. HRG stimulation increased the homodimeric fraction of ErbB3 significantly and reduced the mobility of homodimers fourfold compared to constitutive homodimers. Expression of ErbB2 elevated the homodimeric fraction of ErbB3 even in unstimulated cells and induced a ∼2-fold reduction in the lateral mobility of ErbB3 homodimers. The mobility of ErbB2 was significantly lower than that of ErbB3, and HRG induced a less pronounced decrease in the diffusion coefficient of all ErbB2 molecules and ErbB3/ErbB2 heterodimers than in the mobility of ErbB3. The slower diffusion of ErbB2 compared to ErbB3 was abolished by depolymerizing actin filaments, whereas ErbB2 expression induced a substantial rearrangement of microfilaments, implying a bidirectional interaction between ErbB2 and actin. HRG stimulation of cells co-expressing ErbB3 and ErbB2 led to the formation of ErbB3 homodimers and ErbB3/ErbB2 heterodimers in a competitive fashion. Although pertuzumab, an antibody binding to the dimerization arm of ErbB2, completely abolished the formation of constitutive and HRG-induced ErbB3/ErbB2 heterodimers, it only slightly blocked ErbB3 homodimerization. The results imply that a dynamic equilibrium exists between constitutive and ligand-induced homo- and heterodimers capable of shaping transmembrane signaling.

Mapping Tyrosine Kinase Receptor Dimerization to Receptor Expression and Ligand Affinities

Tyrosine kinase receptor (RTK) ligation and dimerization is a key mechanism for translating external cell stimuli into internal signaling events. This process is critical to several key cell and physiological processes, such as in angiogenesis and embryogenesis, among others. While modulating RTK activation is a promising therapeutic target, RTK signaling axes have been shown to involve complicated interactions between ligands and receptors both within and across different protein families. In angiogenesis, for example, several signaling protein families, including vascular endothelial growth factors and platelet-derived growth factors, exhibit significant cross-family interactions that can influence pathway activation. Computational approaches can provide key insight to detangle these signaling pathways but have been limited by the sparse knowledge of these cross-family interactions. Here, we present a framework for studying known and potential non-canonical interactions. We constructed generalized models of RTK ligation and dimerization for systems of two, three and four receptor types and different degrees of cross-family ligation. Across each model, we developed parameter-space maps that fully determine relative pathway activation for any set of ligand-receptor binding constants, ligand concentrations and receptor concentrations. Therefore, our generalized models serve as a powerful reference tool for predicting not only known ligand: Receptor axes but also how unknown interactions could alter signaling dimerization patterns. Accordingly, it will drive the exploration of cross-family interactions and help guide therapeutic developments across processes like cancer and cardiovascular diseases, which depend on RTK-mediated signaling.

In silico prediction of ErbB signal activation from receptor expression profiles through a data analytics pipeline

The ErbB signalling pathway has been studied extensively owing to its role in normal physiology and its dysregulation in cancer. Reverse engineering by mathematical models use the reductionist approach to characterize the network components. For an emergent, system-level view of the network, we propose a data analytics pipeline that can learn from the data generated by reverse engineering and use it to re-engineer the system with an agent-based approach. Data from a kinetic model that estimates the parameters by fitting to experiments on cell lines, were encoded into rules, for the interactions of the molecular species (agents) involved in biochemical reactions. The agent model, a digital representation of the cell line system, tracks the activation of ErbB1-3 receptors on binding with ligands, resulting in their dimerization, phosphorylation, trafficking and stimulation of downstream signalling through P13-Akt and Erk pathways. The analytics pipeline has been used to mechanistically link HER expression profile to receptor dimerization and activation of downstream signalling pathways. When applied to drug studies, the efficacy of a drug can be investigated in silico. The anti-tumour activity of Pertuzumab, a monoclonal antibody that inhibits HER2 dimerization, was simulated by blocking 80% of the cellular HER2 available, to observe the effect on signal activation.

Transcriptionally inducible Pleckstrin homology-like domain, family A, member 1, attenuates ErbB receptor activity by inhibiting receptor oligomerization

Feedback control is a key mechanism in signal transduction, intimately involved in regulating the outcome of the cellular response. Here, we report a novel mechanism by which PHLDA1, Pleckstrin homology-like domain, family A, member 1, negatively regulates ErbB receptor signaling by inhibition of receptor oligomerization. We have found that the ErbB3 ligand, heregulin, induces PHILDA1 expression in MCF-7 cells. Transcriptionally-induced PHLDA1 protein directly binds to ErbB3, whereas knockdown of PHLDA1 increases complex formation between ErbB3 and ErbB2. To provide insight into the mechanism for our time-course and single-cell experimental observations, we performed a systematic computational search of network topologies of the mathematical models based on receptor dimer-tetramer formation in the ErbB activation processes. Our results indicate that only a model in which PHLDA1 inhibits formation of both dimers and tetramer can explain the experimental data. Predictions made from this model were further validated by single-molecule imaging experiments. Our studies suggest a unique regulatory feature of PHLDA1 to inhibit the ErbB receptor oligomerization process and thereby control the activity of receptor signaling network.

Effect of Spatial Inhomogeneities on the Membrane Surface on Receptor Dimerization and Signal Initiation

Important signal transduction pathways originate on the plasma membrane, where microdomains may transiently entrap diffusing receptors. This results in a non-random distribution of receptors even in the resting state, which can be visualized as “clusters” by high resolution imaging methods. Here, we explore how spatial in-homogeneities in the plasma membrane might influence the dimerization and phosphorylation status of ErbB2 and ErbB3, two receptor tyrosine kinases that preferentially heterodimerize and are often co-expressed in cancer. This theoretical study is based upon spatial stochastic simulations of the two-dimensional membrane landscape, where variables include differential distributions and overlap of transient confinement zones (“domains”) for the two receptor species. The in silico model is parameterized and validated using data from single particle tracking experiments. We report key differences in signaling output based on the degree of overlap between domains and the relative retention of receptors in such domains, expressed as escape probability. Results predict that a high overlap of domains, which favors transient co-confinement of both receptor species, will enhance the rate of hetero-interactions. Where domains do not overlap, simulations confirm expectations that homo-interactions are favored. Since ErbB3 is uniquely dependent on ErbB2 interactions for activation of its catalytic activity, variations in domain overlap or escape probability markedly alter the predicted patterns and time course of ErbB3 and ErbB2 phosphorylation. Taken together, these results implicate membrane domain organization as an important modulator of signal initiation, motivating the design of novel experimental approaches to measure these important parameters across a wider range of receptor systems.