H. Steven Wiley

The Enhanced Tumorigenic Activity of a Mutant Epidermal Growth Factor Receptor Common in Human Cancers Is Mediated by Threshold Levels of Constitutive Tyrosine Phosphorylation and Unattenuated Signaling

Deregulation of signaling by the epidermal growth factor receptor (EGFR) is common in human malignancy progression. One mutant EGFR (variously named ΔEGFR, de2-7 EGFR, or EGFRvIII), which occurs frequently in human cancers, lacks a portion of the extracellular ligand-binding domain due to genomic deletions that eliminate exons 2 to 7 and confers a dramatic enhancement of brain tumor cell tumorigenicity in vivo. In order to dissect the molecular mechanisms of this activity, we analyzed location, autophosphorylation, and attenuation of the mutant receptors. The mutant receptors were expressed on the cell surface and constitutively autophosphorylated at a significantly decreased level compared with wild-type EGFR activated by ligand treatment. Unlike wild-type EGFR, the constitutively active ΔEGFR were not down-regulated, suggesting that the altered conformation of the mutant did not result in exposure of receptor sequence motifs required for endocytosis and lysosomal sorting. Mutational analysis showed that the enhanced tumorigenicity was dependent on intrinsic tyrosine kinase activity and was mediated through the carboxyl terminus. In contrast with wild-type receptor, mutation of any major tyrosine autophosphorylation site abolished these activities suggesting that the biological functions of ΔEGFR are due to low constitutive activation with mitogenic effects amplified by failure to attenuate signaling by receptor down-regulation.

Flow-cytometric isolation of human antibodies from a nonimmune Saccharomyces cerevisiae surface display library

A nonimmune library of 109 human antibody scFv fragments has been cloned and expressed on the surface of yeast, and nanomolar-affinity scFvs routinely obtained by magnetic bead screening and flow-cytometric sorting. The yeast library can be amplified 1010-fold without measurable loss of clonal diversity, allowing its effectively indefinite expansion. The expression, stability, and antigen-binding properties of >50 isolated scFv clones were assessed directly on the yeast cell surface by immunofluorescent labeling and flow cytometry, obviating separate subcloning, expression, and purification steps and thereby expediting the isolation of novel affinity reagents. The ability to use multiplex library screening demonstrates the usefulness of this approach for high-throughput antibody isolation for proteomics applications.

Trafficking of the ErbB receptors and its influence on signaling

Although members of the ErbB receptor family are found predominantly at the cell surface, these receptors undergo constant cycling between the plasma membrane and the endosomal compartment. In the absence of an activating ligand, these receptors are slowly internalized (t(1/2) approximately 30 min) but are quickly recycled. The constitutive degradation rate of the epidermal growth factor (EGF) receptor (EGFR) is slower than other ErbB family members and only the EGFR appears to alter its trafficking pattern in response to ligand binding. This altered pattern is characterized by accelerated internalization and enhanced lysosomal targeting. Ligand-regulated trafficking of the EGFR is mediated by a series of motifs distributed through the cytoplasmic domain of the receptor that are exposed by a combination of activation-mediated conformation changes and the binding of proteins such as Grb2. As a consequence of induced internalization, most EGFR signaling occurs within endosomes whereas signaling by the other members of the ErbB family appear to be generated predominantly from the cell surface. Overexpression of ErbB family members can disrupt normal receptor trafficking by driving heterodimerization of receptors with disparate trafficking patterns. Because different ErbB receptor substrates are localized in different cellular compartments, disrupted trafficking could be an important factor in the altered signaling patterns observed as a consequence of receptor overexpression.

Computational modeling of the EGF-receptor system: a paradigm for systems biology

Computational models have rarely been used as tools by biologists but, when models provide experimentally testable predictions, they can be extremely useful. The epidermal growth factor receptor (EGFR) is probably the best-understood receptor system, and computational models have played a significant part in its elucidation. For many years, models have been used to analyze EGFR dynamics and to interpret mutational studies, and are now being used to understand processes including signal transduction, autocrine loops and developmental patterning. The success of EGFR modeling can be a guide to combining models and experiments productively to understand complex biological processes as integrated systems.

Regulation of Receptor Tyrosine Kinase Signaling by Endocytic Trafficking

Activated receptor tyrosine kinase (RTK) receptors are rapidly internalized and eventually delivered to the lysosomes. Although ligand‐induced endocytosis was originally thought to be a mechanism of receptor inactivation, many studies suggest that receptors remain active within endosomes. This review discusses the role that internalized signaling complexes may play in different RTK systems including recent data on how ubiquitination may regulate this process. In general, it appears that some receptor systems have evolved to enhance endosomal signaling, as is the case for TrkA and NGF. In contrast, the insulin receptor system appears to limit the extent of endosomal signaling. The EGFR system is the intermediate example. In this case, some signals are specifically generated from the cell surface while others appear to be generated from within endosomes. This may act as a mechanism to produce ligand‐specific signals. Thus, trafficking could play diverse roles in receptor signaling, depending on the specific cell and tissue type.

Rapid and Sustained Nuclear-Cytoplasmic ERK Oscillations Induced by Epidermal Growth Factor

Although the ERK pathway has a central role in the response of cells to growth factors, its regulatory structure and dynamics are incompletely understood. To investigate ERK activation in real time, we expressed an ERK–GFP fusion protein in human mammary epithelial cells. On EGF stimulation, we observed sustained oscillations of the ERK–GFP fusion protein between the nucleus and cytoplasm with a periodicity of ∼15 min. The oscillations were persistent (>45 cycles), independent of cell cycle phase, and were highly dependent on cell density, essentially disappearing at confluency. Oscillations occurred even at ligand doses that elicited very low levels of ERK phosphorylation, and could be detected biochemically in both transfected and nontransfected cells. Mathematical modeling revealed that negative feedback from phosphorylated ERK to the cascade input was necessary to match the robustness of the oscillation characteristics observed over a broad range of ligand concentrations. Our characterization of single‐cell ERK dynamics provides a quantitative foundation for understanding the regulatory structure of this signaling cascade.

An integrated model of epidermal growth factor receptor trafficking and signal transduction.

Endocytic trafficking of many types of receptors can have profound effects on subsequent signaling events. Quantitative models of these processes, however, have usually considered trafficking and signaling independently. Here, we present an integrated model of both the trafficking and signaling pathway of the epidermal growth factor receptor (EGFR) using a probability weighted-dynamic Monte Carlo simulation. Our model consists of hundreds of distinct endocytic compartments and approximately 13,000 reactions/events that occur over a broad spatio-temporal range. By using a realistic multicompartment model, we can investigate the distribution of the receptors among cellular compartments as well as their potential signal transduction characteristics. Our new model also allows the incorporation of physiochemical aspects of ligand-receptor interactions, such as pH-dependent binding in different endosomal compartments. To determine the utility of this approach, we simulated the differential activation of the EGFR by two of its ligands, epidermal growth factor (EGF) and transforming growth factor-alpha (TGF-alpha). Our simulations predict that when EGFR is activated with TGF-alpha, receptor activation is biased toward the cell surface whereas EGF produces a signaling bias toward the endosomal compartment. Experiments confirm these predictions from our model and simulations. Our model accurately predicts the kinetics and extent of receptor downregulation induced by either EGF or TGF-alpha. Our results suggest that receptor trafficking controls the compartmental bias of signal transduction, rather than simply modulating signal magnitude. Our model provides a new approach to evaluating the complex effect of receptor trafficking on signal transduction. Importantly, the stochastic and compartmental nature of the simulation allows these models to be directly tested by high-throughput approaches, such as quantitative image analysis.

Investigating the correspondence between transcriptomic and proteomic expression profiles using coupled cluster models

MOTIVATION Modern transcriptomics and proteomics enable us to survey the expression of RNAs and proteins at large scales. While these data are usually generated and analyzed separately, there is an increasing interest in comparing and co-analyzing transcriptome and proteome expression data. A major open question is whether transcriptome and proteome expression is linked and how it is coordinated. RESULTS Here we have developed a probabilistic clustering model that permits analysis of the links between transcriptomic and proteomic profiles in a sensible and flexible manner. Our coupled mixture model defines a prior probability distribution over the component to which a protein profile should be assigned conditioned on which component the associated mRNA profile belongs to. We apply this approach to a large dataset of quantitative transcriptomic and proteomic expression data obtained from a human breast epithelial cell line (HMEC). The results reveal a complex relationship between transcriptome and proteome with most mRNA clusters linked to at least two protein clusters, and vice versa. A more detailed analysis incorporating information on gene function from the Gene Ontology database shows that a high correlation of mRNA and protein expression is limited to the components of some molecular machines, such as the ribosome, cell adhesion complexes and the TCP-1 chaperonin involved in protein folding. AVAILABILITY Matlab code is available from the authors on request.

Characterization and improvement of RNA-Seq precision in quantitative transcript expression profiling

Motivation: Measurement precision determines the power of any analysis to reliably identify significant signals, such as in screens for differential expression, independent of whether the experimental design incorporates replicates or not. With the compilation of large-scale RNA-Seq datasets with technical replicate samples, however, we can now, for the first time, perform a systematic analysis of the precision of expression level estimates from massively parallel sequencing technology. This then allows considerations for its improvement by computational or experimental means. Results: We report on a comprehensive study of target identification and measurement precision, including their dependence on transcript expression levels, read depth and other parameters. In particular, an impressive recall of 84% of the estimated true transcript population could be achieved with 331 million 50 bp reads, with diminishing returns from longer read lengths and even less gains from increased sequencing depths. Most of the measurement power (75%) is spent on only 7% of the known transcriptome, however, making less strongly expressed transcripts harder to measure. Consequently, <30% of all transcripts could be quantified reliably with a relative error <20%. Based on established tools, we then introduce a new approach for mapping and analysing sequencing reads that yields substantially improved performance in gene expression profiling, increasing the number of transcripts that can reliably be quantified to over 40%. Extrapolations to higher sequencing depths highlight the need for efficient complementary steps. In discussion we outline possible experimental and computational strategies for further improvements in quantification precision. Contact: rnaseq10@boku.ac.at Supplementary information: Supplementary data are available at Bioinformatics online.

Trafficking and Proteolytic Release of Epidermal Growth Factor Receptor Ligands Are Modulated by Their Membrane-anchoring Domains

Ligands that bind to the epidermal growth factor (EGF) receptor are initially synthesized as integral membrane proteins that are released from the cell surface by regulated proteolysis. To study the role of the membrane-anchoring domain in ligand release, we made two artificial ligands. The first possessed the membrane-anchoring domain from EGF whereas the second had the corresponding domain from heparin binding EGF-like growth factor (HB-EGF). Both ligands lacked amino-terminal extensions, and were epitope-tagged at the carboxyl terminus. Following stable expression in human mammary epithelial cells, their cellular localization and rate of proteolytic release were examined. We found that constructs with the membrane-anchoring domain from EGF were found primarily at the cell surface and displayed a relatively high rate of constitutive release. Constructs with the HB-EGF membrane-anchoring domain displayed a higher internalized fraction and a very low rate of constitutive release. The two ligand constructs also displayed different patterns of stimulated release. Proteolysis of the chimera with the HB-EGF membrane-anchoring domain was stimulated by activation of protein kinase C, but release of EGF from constructs with the EGF membrane-anchoring domain was insensitive to this. Calcium ionophores, calmodulin antagonists, and tyrosine phosphatase inhibitors stimulated the release of both ligands. Furthermore, the release of the two constructs showed different sensitivity to metalloprotease inhibitors. Despite a large fold-increase in ligand proteolysis following cell stimulation, only a small fraction of total cell-associated ligand was released per hour. Our results show that the membrane-anchoring domain of EGF-like ligands can specify both their localization and proteolytic processing. The structures of the membrane-anchoring region of this class of ligands can thus regulate their activity.