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ABSTRACT: The epidermal growth factor receptor (EGFR) belongs to the ErbB family of receptor tyrosine kinases, and controls a diverse set of cellular responses relevant to development and tumorigenesis. ErbB activation is a complex process involving receptor-ligand binding, receptor dimerization, phosphorylation, and trafficking (internalization, recycling and degradation), which together dictate the spatio-temporal distribution of active receptors within the cell. The ability to predict this distribution, and elucidation of the factors regulating it, would help to establish a mechanistic link between ErbB expression levels and the cellular response. Towards this end, we constructed mathematical models to determine the contributions of receptor dimerization and phosphorylation to EGFR activation, and to examine the dependence of these processes on sub-cellular location. We collected experimental datasets for EGFR activation dynamics in human mammary epithelial cells, with the specific goal of model parameterization, and used the data to estimate parameters for several alternate models. Model-based analysis indicated that: (1) signal termination via receptor dephosphorylation in late endosomes, prior to degradation, is an important component of the response, (2) less than 40% of the receptors in the cell are phosphorylated at any given time, even at saturating ligand doses, and (3) receptor phosphorylation kinetics at the cell surface and early endosomes are comparable. We validated the last finding by measuring the EGFR dephosphorylation rates at various times following ligand addition both in whole cells and in endosomes using ELISAs and fluorescent imaging. Overall, our results provide important information on how EGFR phosphorylation levels are regulated within cells. This study demonstrates that an iterative cycle of experiments and modeling can be used to gain mechanistic insight regarding complex cell signaling networks.
Molecular BioSystems 09/2012; 8(11):2868-82. · 3.53 Impact Factor
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ABSTRACT: With currently available RNA-Seq pipelines, expression estimates for most genes are very noisy. We here introduce MapAl, a tool for RNA-Seq expression profiling that builds on the established programs Bowtie and Cufflinks. In the post-processing of RNA-Seq reads, it incorporates gene models already at the stage of read alignment, increasing the number of reliably measured known transcripts consistently by 50%. Adding genes identified de novo then allows a reliable assessment of double the total number of transcripts compared to other available pipelines. This substantial improvement is of general relevance: 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.
Frontiers in genetics. 01/2012; 3:28.
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ABSTRACT: To understand how integration of multiple data types can help decipher cellular responses at the systems level, we analyzed the mitogenic response of human mammary epithelial cells to epidermal growth factor (EGF) using whole genome microarrays, mass spectrometry-based proteomics and large-scale western blots with over 1000 antibodies. A time course analysis revealed significant differences in the expression of 3172 genes and 596 proteins, including protein phosphorylation changes measured by western blot. Integration of these disparate data types showed that each contributed qualitatively different components to the observed cell response to EGF and that varying degrees of concordance in gene expression and protein abundance measurements could be linked to specific biological processes. Networks inferred from individual data types were relatively limited, whereas networks derived from the integrated data recapitulated the known major cellular responses to EGF and exhibited more highly connected signaling nodes than networks derived from any individual dataset. While cell cycle regulatory pathways were altered as anticipated, we found the most robust response to mitogenic concentrations of EGF was induction of matrix metalloprotease cascades, highlighting the importance of the EGFR system as a regulator of the extracellular environment. These results demonstrate the value of integrating multiple levels of biological information to more accurately reconstruct networks of cellular response.
PLoS ONE 01/2012; 7(3):e34515. · 4.09 Impact Factor
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ABSTRACT: 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.
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.
rnaseq10@boku.ac.at
Bioinformatics 07/2011; 27(13):i383-91. · 5.47 Impact Factor
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ABSTRACT: The extracellular signal-regulated kinase (ERK) pathway is a central signaling pathway in development and disease and is regulated by multiple negative and positive feedback loops. Recent studies have shown negative feedback from ERK to upstream regulators can give rise to biochemical oscillations with a periodicity of between 15 and 30min. Feedback due to the stimulated transcription of negative regulators of the ERK pathway can also give rise to transcriptional oscillations with a periodicity of one to two hours. The biological significance of these oscillations is not clear, but recent evidence suggests that transcriptional oscillations participate in developmental processes, such as somite formation. Biochemical oscillations are more enigmatic, but could provide a mechanism for encoding different types of inputs into a common signaling pathway.
Current opinion in genetics & development 12/2010; 20(6):650-5. · 8.99 Impact Factor
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ABSTRACT: Transactivation of the epidermal growth factor receptor (EGFR) is thought to be a process by which a variety of cellular inputs can be integrated into a single signaling pathway through either stimulated proteolysis (shedding) of membrane-anchored EGFR ligands or by modification of the activity of the EGFR. As a first step towards building a predictive model of the EGFR transactivation circuit, we quantitatively defined how signals from multiple agonists were integrated both upstream and downstream of the EGFR to regulate extracellular signal regulated kinase (ERK) activity in human mammary epithelial cells. By using a "non-binding" reporter of ligand shedding, we found that transactivation triggers a positive feedback loop from ERK back to the EGFR such that ligand shedding drives EGFR-stimulated ERK that in turn drives further ligand shedding. Importantly, activated Ras and ERK levels were nearly linear functions of ligand shedding and the effect of multiple, sub-saturating inputs was additive. Simulations showed that ERK-mediated feedback through ligand shedding resulted in a stable steady-state level of activated ERK, but also showed that the extracellular environment can modulate the level of feedback. Our results suggest that the transactivation circuit acts as a context-dependent integrator and amplifier of multiple extracellular signals and that signal integration can effectively occur at multiple points in the EGFR pathway.
Molecular BioSystems 07/2010; 6(7):1293-306. · 3.53 Impact Factor
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ABSTRACT: Heparin-binding EGF-like growth factor (HB-EGF) is a ligand for EGF receptor (EGFR) and possesses the ability to signal in juxtacrine, autocrine and/or paracrine mode, with these alternatives being governed by the degree of proteolytic release of the ligand. Although the spatial range of diffusion of released HB-EGF is restricted by binding heparan-sulfate proteoglycans (HSPGs) in the extracellular matrix and/or cellular glycocalyx, ascertaining mechanisms governing non-released HB-EGF localization is also important for understanding its effects. We have employed a new method for independently tracking the localization of the extracellular EGF-like domain of HB-EGF and the cytoplasmic C-terminus. A striking observation was the absence of the HB-EGF transmembrane pro-form from the leading edge of COS-7 cells in a wound-closure assay; instead, this protein localized in regions of cell-cell contact. A battery of detailed experiments found that this localization derives from a trans interaction between extracellular HSPGs and the HB-EGF heparin-binding domain, and that disruption of this interaction leads to increased release of soluble ligand and a switch in cell phenotype from juxtacrine-induced growth inhibition to autocrine-induced proliferation. Our results indicate that extracellular HSPGs serve to sequester the transmembrane pro-form of HB-EGF at the point of cell-cell contact, and that this plays a role in governing the balance between juxtacrine versus autocrine and paracrine signaling.
Journal of Cell Science 07/2010; 123(Pt 13):2308-18. · 6.11 Impact Factor
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ABSTRACT: The regulation of extracellular signal-regulated kinase (ERK) oscillations in the context of wound healing and carcinogenesis have been investigated in premalignant and malignant JB6 mouse epidermal cells stimulated with basic fibroblast growth factor (bFGF) and 12-O-tetradecanoyl phorbol-13-acetate (TPA). In premalignant JB6 cells, bFGF stimulation (1) increases cellular phospho-ERK and phospho-c-Jun levels, (2) increases serum-dependent cell proliferation, (3) induces an apparent epithelial-to-mesenchymal transition, and (4) induces the persistent nuclear-cytosolic oscillation of an ERK1-green fluorescent protein (ERK1-GFP) chimera. In contrast, TPA induces persistent activation of ERK in the absence of oscillations and does not induce efficient migration. Treatment of malignant or transformed JB6 cells with bFGF is associated with a transient nuclear translocation of ERK1-GFP but not oscillations or efficient cell migration. Our data suggest that bFGF regulates ERK oscillations in premalignant but not malignant JB6 cells.
Journal of Investigative Dermatology 12/2009; 130(5):1444-56. · 6.31 Impact Factor
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ABSTRACT: Knowledge about signaling pathways is typically compiled based on data gathered using different cell lines. This approach implicitly assumes that the cell line dependence is not important. However, different cell lines do not always respond to a particular stimulus in the same way, and lack of coherent data collected from closely related cellular systems can be detrimental to the efforts to understand the regulation of biological processes. To address this issue, we created a clone library of human mammary epithelial (HME) cells that expresses different levels of HER2 and HER3 receptors in combination with endogenous EGFR/HER1. Using our clone library, we have quantified the receptor activation patterns and systematically tested the validity of the existing hypotheses about the interaction patterns between HER1-3 receptors.
Our study identified HER2 as the dominant dimerization partner for both EGFR and HER3. Contrary to earlier suggestions, we find that lateral interactions with HER2 do not lead to strong transactivation between EGFR and HER3, i.e., EGFR activation and HER3 activation are only weakly linked in HME cells. We also find that observed weak transactivation is uni-directional where stimulation of EGFR leads to HER3 activation whereas HER3 stimulation does not activate the EGFR. Repeating our experiments at lower cell confluency established that cell confluency is not a major factor in the observed interaction patterns. We have also quantified the dependence of the kinetics of Erk and Akt activation on different HER receptors. We found that HER3 signaling makes the strongest contribution to Akt activation and that, stimulation of either EGFR or HER3 leads to significant Erk activation.
Our study shows that clone cell libraries can be a powerful resource in systems biology research by making it possible to differentiate between various hypotheses in a consistent cellular background. Using our constructed clone library we profiled the cell signaling patterns to establish the role of HER2 in the crosstalk between EGFR and HER3 receptors in HME cells. Our results for HME cells show that the weak linkage between EGFR and HER3 pathways can lead to distinct downstream cellular signaling patterns in response to the ligands of these two receptors.
BMC Cell Biology 10/2009; 10:78. · 2.59 Impact Factor
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Tyler H Heibeck,
Shi-Jian Ding,
Lee K Opresko,
Rui Zhao,
Athena A Schepmoes,
Feng Yang,
Aleksey V Tolmachev,
Matthew E Monroe,
David G Camp,
Richard D Smith, H Steven Wiley,
Wei-Jun Qian
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ABSTRACT: Protein tyrosine phosphorylation represents a central regulatory mechanism in cell signaling. Here, we present an extensive survey of tyrosine phosphorylation sites in a normal-derived human mammary epithelial cell (HMEC) line by applying antiphosphotyrosine peptide immunoaffinity purification coupled with high sensitivity capillary liquid chromatography tandem mass spectrometry. A total of 481 tyrosine phosphorylation sites (covered by 716 unique peptides) from 285 proteins were confidently identified in HMEC following the analysis of both the basal condition and acute stimulation with epidermal growth factor (EGF). The estimated false discovery rate was 1.0% as determined by searching against a scrambled database. Comparison of these data with existing literature showed significant agreement for previously reported sites. However, we observed 281 sites that were not previously reported for HMEC cultures and 29 of which have not been reported for any human cell or tissue system. The analysis showed that a majority of highly phosphorylated proteins were relatively low-abundance. Large differences in phosphorylation stoichiometry for sites within the same protein were also observed, raising the possibility of more important functional roles for such highly phosphorylated pTyr sites. By mapping to major signaling networks, such as the EGF receptor and insulin growth factor-1 receptor signaling pathways, many known proteins involved in these pathways were revealed to be tyrosine phosphorylated, which provides interesting targets for future hypothesis-driven and targeted quantitative studies involving tyrosine phosphorylation in HMEC or other human systems.
Journal of Proteome Research 07/2009; 8(8):3852-61. · 5.11 Impact Factor
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ABSTRACT: 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 approximately 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.
Molecular Systems Biology 01/2009; 5:332. · 8.63 Impact Factor
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Ronald C. Taylor,
Mudita Singhal,
Don Simone Daly,
Jason M. Gilmore,
William R. Cannon,
Kelly Domico,
Amanda M. White,
Deanna L. Auberry,
Kenneth J. Auberry,
Brian Hooker,
Gregory B. Hurst,
Jason E. McDermott,
W. Hayes McDonald,
Dale Pelletier,
Denise Schmoyer, H. Steven Wiley
IJDMB. 01/2009; 3:409-430.
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Ronald C Taylor,
Mudita Singhal,
Don S Daly,
Jason Gilmore,
William R Cannon,
Kelly Domico,
Amanda M White,
Deanna L Auberry,
Kenneth J Auberry,
Brian S Hooker,
Greg Hurst,
Jason E McDermott,
W Hayes McDonald,
Dale A Pelletier,
Denise Schmoyer, H Steven Wiley
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ABSTRACT: We present a platform for the reconstruction of protein-protein interaction networks inferred from Mass Spectrometry (MS) bait-prey data. The Software Environment for Biological Network Inference (SEBINI), an environment for the deployment of network inference algorithms that use high-throughput data, forms the platform core. Among the many algorithms available in SEBINI is the Bayesian Estimator of Probabilities of Protein-Protein Associations (BEPro3) algorithm, which is used to infer interaction networks from such MS affinity isolation data. Also, the pipeline incorporates the Collective Analysis of Biological Interaction Networks (CABIN) software. We have thus created a structured workflow for protein-protein network inference and supplemental analysis.
International Journal of Data Mining and Bioinformatics 01/2009; 3(4):409-30. · 0.43 Impact Factor
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ABSTRACT: 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.
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.
Matlab code is available from the authors on request.
Bioinformatics 11/2008; 24(24):2894-900. · 5.47 Impact Factor
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ABSTRACT: The number of distinct signaling pathways that can transactivate the epidermal growth factor receptor (EGFR) in a single cell type is unclear. Using a single strain of human mammary epithelial cells, we found that a wide variety of agonists, such as lysophosphatidic acid (LPA), uridine triphosphate, growth hormone, vascular endothelial growth factor, insulin-like growth factor-1 (IGF-1), and tumor necrosis factor-alpha, require EGFR activity to induce ERK phosphorylation. In contrast, hepatocyte growth factor can stimulate ERK phosphorylation independent of the EGFR. EGFR transactivation also correlated with an increase in cell proliferation and could be inhibited with metalloprotease inhibitors. However, there were significant differences with respect to transactivation kinetics and sensitivity to different inhibitors. In particular, IGF-1 displayed relatively slow transactivation kinetics and was resistant to inhibition by the selective ADAM-17 inhibitor WAY-022 compared with LPA-induced transactivation. Studies using anti-ligand antibodies showed that IGF-1 transactivation required amphiregulin production, whereas LPA was dependent on multiple ligands. Direct measurement of ligand shedding confirmed that LPA treatment stimulated shedding of multiple EGFR ligands, but paradoxically, IGF-1 had little effect on the shedding rate of any ligand, including amphiregulin. Instead, IGF-1 appeared to work by enhancing EGFR activation of Ras in response to constitutively produced amphiregulin. This enhancement of EGFR signaling was independent of both receptor phosphorylation and PI-3-kinase activity, suggestive of a novel mechanism. Our studies demonstrate that within a single cell type, the EGFR autocrine system can couple multiple signaling pathways to ERK activation and that this modulation of EGFR autocrine signaling can be accomplished at multiple regulatory steps.
Journal of Biological Chemistry 10/2008; 283(46):31477-87. · 4.77 Impact Factor
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ABSTRACT: Extracellular proteins released by mammary epithelial cells are critical mediators of cell communication, proliferation, and organization, yet the actual spectrum of proteins released by any given cell (the secretome) is poorly characterized. To define the set of proteins secreted by human mammary epithelial cells (HMEC), we combined analytical and computational approaches to define a secretome protein set based upon probable biological significance. Analysis of HMEC-conditioned medium by liquid chromatography-mass spectrometry resulted in identification of 889 unique proteins, of which 151 were found to be specifically enriched in the extracellular compartment when compared with a database of proteins expressed in whole HMEC lysates. Additional high mass accuracy analysis revealed 36 proteins whose extracellular abundance increased after treatment with phorbol ester (PMA), a protein kinase C agonist and general secretagogue. Many of the PMA stimulated proteins have been reported to be aberrantly expressed in human cancers and appear to be coregulated as multigene clusters. By inhibiting PMA-mediated transactivation of the epidermal growth factor receptor (EGFR), a pathway critically required for normal HMEC function, we found that the secretion of specific matrix metalloproteases was also coordinately regulated through EGFR transactivation. This study demonstrates a tiered strategy by which extracellular proteins can be identified and progressively assigned to classes of increasing confidence and regulatory importance.
Journal of Proteome Research 03/2008; 7(2):558-69. · 5.11 Impact Factor
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ABSTRACT: The molecular mechanisms that transmit information from cell surface receptors to the nucleus are exceedingly complex; thus, much effort has been expended in developing computational models to understand these processes. A recent study on modeling the nuclear-cytoplasmic shuttling of Smad2-Smad4 complexes in response to transforming growth factor-beta (TGF-beta) receptor activation has provided substantial insight into how this signaling network translates the degree of TGF-beta receptor activation (input) into the amount of nuclear Smad2-Smad4 complexes (output). The study addressed this question by combining a simple, mechanistic model with targeted experiments, an approach that proved particularly powerful for exploring the fundamental properties of a complex signaling network. The mathematical model revealed that Smad nuclear-cytoplasmic dynamics enables a proportional but time-delayed coupling between the input and the output. As a result, the output can faithfully track gradual changes in the input while the rapid input fluctuations that constitute signaling noise are dampened out.
Science Signaling 02/2008; 1(36):pe41. · 7.50 Impact Factor
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ABSTRACT: EGF family ligands are synthesized as membrane-anchored precursors whose proteolytic release yields mature diffusible factors that can activate cell surface receptors in autocrine or paracrine mode. Expression of these ligands is altered in pathological states and in physiological processes, such as development and tissue regeneration. Despite the widely documented biological importance of autocrine EGF signaling, quantitative relationships between protease-mediated ligand release and consequent cell behavior have not been rigorously investigated. We thus explored the relationship between autocrine EGF release rates and cell behavioral responses along with activation of ERK, a key downstream signal, by expressing chimeric ligand precursors and modulating their proteolytic shedding using a metalloprotease inhibitor in human mammary epithelial cells. We found that ERK activation increased monotonically with increasing ligand release rate despite concomitant downregulation of EGF receptor levels. Cell migration speed was directly related to ligand release rate and proportional to steady-state phospho-ERK levels. Moreover, migration speed was significantly greater for autocrine stimulation compared with exogenous stimulation, even at comparable phospho-ERK levels. By contrast, cell proliferation rates were approximately equivalent at all ligand release rates and were similar regardless of whether the ligand was presented endogenously or exogenously. Thus, in our mammary epithelial cell system, migration and proliferation are differentially sensitive to the mode of EGF ligand presentation.
Journal of Cell Science 11/2007; 120(Pt 20):3688-99. · 6.11 Impact Factor
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Julia L Sharp,
Kevin K Anderson,
Gregory B Hurst,
Don S Daly,
Dale A Pelletier,
William R Cannon,
Deanna L Auberry,
Denise D Schmoyer,
W Hayes McDonald,
Amanda M White,
Brian S Hooker,
Kristin D Victry,
Michelle V Buchanan,
Vladimir Kery, H Steven Wiley
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ABSTRACT: Affinity isolation of protein complexes followed by protein identification by LC-MS/MS is an increasingly popular approach for mapping protein interactions. However, systematic and random assay errors from multiple sources must be considered to confidently infer authentic protein-protein interactions. To address this issue, we developed a general, robust statistical method for inferring authentic interactions from protein prey-by-bait frequency tables using a binomial-based likelihood ratio test (LRT) coupled with Bayes' Odds estimation. We then applied our LRT-Bayes' algorithm experimentally using data from protein complexes isolated from Rhodopseudomonas palustris. Our algorithm, in conjunction with the experimental protocol, inferred with high confidence authentic interacting proteins from abundant, stable complexes, but few or no authentic interactions for lower-abundance complexes. The algorithm can discriminate against a background of prey proteins that are detected in association with a large number of baits as an artifact of the measurement. We conclude that the experimental protocol including the LRT-Bayes' algorithm produces results with high confidence but moderate sensitivity. We also found that Monte Carlo simulation is a feasible tool for checking modeling assumptions, estimating parameters, and evaluating the significance of results in protein association studies.
Journal of Proteome Research 10/2007; 6(9):3788-95. · 5.11 Impact Factor
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ABSTRACT: Receptors constitute the interface of cells to their external environment. These molecules bind specific ligands involved in multiple processes, such as signal transduction and nutrient transport. Although a variety of cell surface receptors undergo endocytosis, the systems-level design principles that govern the evolution of receptor trafficking dynamics are far from fully understood. We have constructed a generalized mathematical model of receptor-ligand binding and internalization to understand how receptor internalization dynamics encodes receptor function and regulation. A given signaling or transport receptor system represents a particular implementation of this module with a specific set of kinetic parameters. Parametric analysis of the response of receptor systems to ligand inputs reveals that receptor systems can be characterized as being: i) avidity-controlled where the response control depends primarily on the extracellular ligand capture efficiency, ii) consumption-controlled where the ability to internalize surface-bound ligand is the primary control parameter, and iii) dual-sensitivity where both the avidity and consumption parameters are important. We show that the transferrin and low-density lipoprotein receptors are avidity-controlled, the vitellogenin receptor is consumption-controlled, and the epidermal growth factor receptor is a dual-sensitivity receptor. Significantly, we show that ligand-induced endocytosis is a mechanism to enhance the accuracy of signaling receptors rather than merely serving to attenuate signaling. Our analysis reveals that the location of a receptor system in the avidity-consumption parameter space can be used to understand both its function and its regulation.
PLoS Computational Biology 07/2007; 3(6):e101. · 5.22 Impact Factor
