A quantitative protein interaction network for the ErbB receptors using protein microarrays

Reverse-phase protein microarrays: application to biomarker discovery and translational medicine

Mapping of protein signaling networks within tumors can identify new targets for therapy and provide a means to stratify patients for individualized therapy. Kinases are important drug targets, as such kinase network information could become the basis for development of therapeutic strategies for improving treatment outcome. An urgent clinical goal is to identify functionally important molecular networks associated with subpopulations of patients that may not respond to conventional combination chemotherapy. Reverse-phase protein microarrays are a technology platform designed for quantitative, multiplexed analysis of specific phosphorylated, cleaved, or total (phosphorylated and nonphosphorylated) forms of cellular proteins from a limited amount of sample. This class of microarray can be used to interrogate cellular samples, serum or body fluids. This review focuses on the application of reverse-phase protein microarrays for translational research and therapeutic drug target discovery.

Arraying proteins by cell-free synthesis

Recent advances in life science have led to great motivation for the development of protein arrays to study functions of genome-encoded proteins. While traditional cell-based methods have been commonly used for generating protein arrays, they are usually a time-consuming process with a number of technical challenges. Cell-free protein synthesis offers an attractive system for making protein arrays, not only does it rapidly converts the genetic information into functional proteins without the need for DNA cloning, but also presents a flexible environment amenable to production of folded proteins or proteins with defined modifications. Recent advancements have made it possible to rapidly generate protein arrays from PCR DNA templates through parallel on-chip protein synthesis. This article reviews current cell-free protein array technologies and their proteomic applications.

Use of multidimensional separation protocols for the purification of trace components in complex biological samples for proteomics analysis

The routine detection of low abundance components in complex samples for detailed proteomics analysis continues to be a challenge. Whilst the potential of multidimensional chromatographic fractionation for this purpose has been proposed for some years, and was used effectively for the purification to homogeneity of trace components in bulk biological samples for N-terminal sequence analysis, its practical application in the proteomics arena is still limited. This article reviews some of the recent data using these approaches, including the use of microaffinity purification as part of multidimensional protocols for downstream proteomics analysis.

Potential protein toxicity of synthetic pigments: binding of poncean S to human serum albumin

Using various methods, e.g., spectrophotometry, circular dichroism, and isothermal titration calorimetry, the interaction of poncean S (PS) with human serum albumin (HSA) was characterized at pH 1.81, 3.56, and 7.40 using the spectral correction technique, and Langmuir and Temkin isothermal models. The consistency among results concerning, e.g., binding number, binding energy, and type of binding, showed that ion pair electrostatic attraction fixed the position of PS in HSA and subsequently induced a combination of multiple noncovalent bonds such as H-bonds, hydrophobic interactions, and van der Waals forces. Ion pair attraction and H-bonds produced a stable PS-HSA complex and led to a marked change in the secondary structure of HSA in acidic media. The PS-HSA binding pattern and the process of change in HSA conformation were also investigated. The potentially toxic effect of PS on the transport function of HSA in a normal physiological environment was analyzed. This work provides a useful experimental strategy for studying the interaction of organic substances with biomacromolecules, helping us to understand the activity or mechanism of toxicity of an organic compound.

Insulin receptor substrate-1 involvement in epidermal growth factor receptor and insulin-like growth factor receptor signalling: implication for Gefitinib ('Iressa') response and resistance

Classically the insulin receptor substrate-1 (IRS-1) is an essential component of insulin-like growth factor type 1 receptor (IGF-IR) signalling, providing an interface between the receptor and key downstream signalling cascades. Here, however, we show that in tamoxifen-resistant MCF-7 (Tam-R) breast cancer cells, that are highly dependent on epidermal growth factor receptor (EGFR) for growth, IRS-1 can interact with EGFR and be preferentially phosphorylated on tyrosine (Y) 896, a Grb2 binding site. Indeed, phosphorylation of this site is greatly enhanced by exposure of these cells, and other EGFR-positive cell lines, to EGF. Importantly, while IGF-II promotes phosphorylation of IRS-1 on Y612, a PI3-K recruitment site, it has limited effect on Y896 phosphorylation in Tam-R cells. Furthermore, EGF and IGF-II co-treatment, reduces the ability of IGF-II to phosphorylate Y612, whilst maintaining Y896 phosphorylation, suggesting that the EGFR is the dominant recruiter of IRS-1 in this cell line. Significantly, challenge of Tam-R cells with the EGFR-selective tyrosine kinase inhibitor gefitinib, for 7 days, reduces IRS-1/EGFR association and IRS-1 Y896 phosphorylation, while promoting IRS-1/IGF-IR association and IRS-1 Y612 phosphorylation. Furthermore, gefitinib significantly enhances IGF-II-mediated phosphorylation of IRS-1 Y612 and AKT in Tam-R cells. Importantly, induction of this pathway by gefitinib can be abrogated by inhibition/downregulation of the IGF-IR. Our data would therefore suggest a novel association exists between the EGFR and IRS-1 in several EGFR-positive cancer cell lines. This association acts to promote phosphorylation of IRS-1 at Y896 and drive MAPK signalling whilst preventing recruitment of IRS-1 by the IGF-IR and inhibiting signalling via this receptor. Treatment with gefitinib alters the dynamics of this system, promoting IGF-IR signalling, the dominant gefitinib-resistant growth regulatory pathway in Tam-R cells, thus, potentially limiting its efficacy.

Robust protein protein interactions in crowded cellular environments

The capacity of proteins to interact specifically with one another underlies our conceptual understanding of how living systems function. Systems-level study of specificity in protein-protein interactions is complicated by the fact that the cellular environment is crowded and heterogeneous; interaction pairs may exist at low relative concentrations and thus be presented with many more opportunities for promiscuous interactions compared with specific interaction possibilities. Here we address these questions by using a simple computational model that includes specifically designed interacting model proteins immersed in a mixture containing hundreds of different unrelated ones; all of them undergo simulated diffusion and interaction. We find that specific complexes are quite robust to interference from promiscuous interaction partners only in the range of temperatures T(design) > T > T(rand). At T > T(design), specific complexes become unstable, whereas at T < T(rand), formation of specific complexes is suppressed by promiscuous interactions. Specific interactions can form only if T(design) > T(rand). This condition requires an energy gap between binding energy in a specific complex and set of binding energies between randomly associating proteins, providing a general physical constraint on evolutionary selection or design of specific interacting protein interfaces. This work has implications for our understanding of how the protein repertoire functions and evolves within the context of cellular systems.

Quantitative Analysis of Carbohydrate−Protein Interactions Using Glycan Microarrays: Determination of Surface and Solution Dissociation Constants

Carbohydrate-protein interactions on surface and in solution were quantitatively measured by a glycan microarray. Assessing carbohydrate affinities is typically difficult due to weak affinities and limited sources of structurally complex glycans. We described here a sensitive, high-throughput, and convenient glycan microarray technology for the simultaneous determination of a wide variety of parameters in a single experiment using small amounts of materials. Assay systems based on this technology were developed to analyze multivalent interactions and determine the surface dissociation constant (KD,surf) for surface-coated mannose derivatives with mannose binding lectins and antibodies. Competition experiments that employed monovalent ligands in solution yielded KD and Ki values in solution similar to equilibrium binding constants obtained in titration microcalorimetry and surface plasmon resonance experiments.

Dissecting kinase signaling pathways

Aberrant protein kinase signaling is a hallmark of many human diseases including cancer, diabetes, and neurological disorders. Kinase inhibitors have shown to be successful at treating some of these diseases, implying that understanding kinase signaling pathways may lead to additional, non-kinase drug targets. However, identifying substrates of protein kinases is difficult due to the universality of the chemical mechanism kinases utilize and the ability of multiple kinases to phosphorylate the same protein substrates. In this review, we explore the advantages and disadvantages of several techniques for identifying kinase substrates. Once putative substrates are identified, their validation as physiological substrates remains a major challenge. We propose three criteria for confirming the physiological relevance of a putative substrate's interaction with a kinase.

High-throughput phosphotyrosine profiling using SH2 domains

Protein tyrosine phosphorylation controls many aspects of signaling in multicellular organisms. One of the major consequences of tyrosine phosphorylation is the creation of binding sites for proteins containing Src homology 2 (SH2) domains. To profile the global tyrosine phosphorylation state of the cell, we have developed proteomic binding assays encompassing nearly the full complement of human SH2 domains. Here we provide a global view of SH2 domain binding to cellular proteins based on large-scale far-western analyses. We also use reverse-phase protein arrays to generate comprehensive, quantitative SH2 binding profiles for phosphopeptides, recombinant proteins, and entire proteomes. As an example, we profiled the adhesion-dependent SH2 binding interactions in fibroblasts and identified specific focal adhesion complex proteins whose tyrosine phosphorylation and binding to SH2 domains are modulated by adhesion. These results demonstrate that high-throughput comprehensive SH2 profiling provides valuable mechanistic insights into tyrosine kinase signaling pathways.

ErbB receptors: from oncogenes to targeted cancer therapies

Understanding the genetic origin of cancer at the molecular level has facilitated the development of novel targeted therapies. Aberrant activation of the ErbB family of receptors is implicated in many human cancers and is already the target of several anticancer therapeutics. The use of mAbs specific for the extracellular domain of ErbB receptors was the first implementation of rational targeted therapy. The cytoplasmic tyrosine kinase domain is also a preferred target for small compounds that inhibit the kinase activity of these receptors. However, current therapy has not yet been optimized, allowing for opportunities for optimization of the next generation of targeted therapy, particularly with regards to inhibiting heteromeric ErbB family receptor complexes.

PDZ domain binding selectivity is optimized across the mouse proteome

PDZ domains have long been thought to cluster into discrete functional classes defined by their peptide-binding preferences. We used protein microarrays and quantitative fluorescence polarization to characterize the binding selectivity of 157 mouse PDZ domains with respect to 217 genome-encoded peptides. We then trained a multidomain selectivity model to predict PDZ domain-peptide interactions across the mouse proteome with an accuracy that exceeds many large-scale, experimental investigations of protein-protein interactions. Contrary to the current paradigm, PDZ domains do not fall into discrete classes; instead, they are evenly distributed throughout selectivity space, which suggests that they have been optimized across the proteome to minimize cross-reactivity. We predict that focusing on families of interaction domains, which facilitates the integration of experimentation and modeling, will play an increasingly important role in future investigations of protein function.

A lock on phosphotyrosine signaling

Protein phosphorylation plays a major role in cell signaling and human disease, so understanding the effects of tyrosine phosphorylation on protein structure and function is an area of intense investigation. A new technique allows site-specific incorporation of a non-hydrolyzable phosphotyrosine analogue into recombinant proteins, providing a new strategy for research in this important area.

Robust associations of four new chromosome regions from genome-wide analyses of type 1 diabetes

The Wellcome Trust Case Control Consortium (WTCCC) primary genome-wide association (GWA) scan on seven diseases, including the multifactorial autoimmune disease type 1 diabetes (T1D), shows associations at P < 5 x 10(-7) between T1D and six chromosome regions: 12q24, 12q13, 16p13, 18p11, 12p13 and 4q27. Here, we attempted to validate these and six other top findings in 4,000 individuals with T1D, 5,000 controls and 2,997 family trios independent of the WTCCC study. We confirmed unequivocally the associations of 12q24, 12q13, 16p13 and 18p11 (P(follow-up) Collapse

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MESH Headings

• Adolescent
• Case-Control Studies
• Chromosome Mapping
• Diabetes Mellitus, Type 1/genetics
• Genetic Predisposition to Disease
• Genome, Human
• Humans
• Polymorphism, Single Nucleotide

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Grants

• 061859 Wellcome Trust
• 089989 Wellcome Trust
• G0000934 Medical Research Council
• Wellcome Trust
• 061858 Wellcome Trust

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Affiliation(s)

John A Todd Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, University of Cambridge, Addenbrooke's Hospital, Cambridge CB2 0XY, UK.
Neil M Walker
Jason D Cooper
Deborah J Smyth
Kate Downes
Vincent Plagnol
Rebecca Bailey
Sergey Nejentsev
Sarah F Field
Felicity Payne
Christopher E Lowe
Jeffrey S Szeszko
Jason P Hafler
Lauren Zeitels
Jennie H M Yang
Adrian Vella
Sarah Nutland
Helen E Stevens
Helen Schuilenburg
Gillian Coleman
Meeta Maisuria
William Meadows
Luc J Smink
Barry Healy
Oliver S Burren
Alex A C Lam
Nigel R Ovington
James Allen
Ellen Adlem
Hin-Tak Leung
Chris Wallace
Joanna M M Howson
Cristian Guja
Constantin Ionescu-Tîrgovişte
Matthew J Simmonds
Joanne M Heward
Stephen C L Gough
David B Dunger
Linda S Wicker
David G Clayton

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Development of surface plasmon resonance mass spectrometry array platform

Protein microarrays are the format of choice for high-throughput, high-content protein interaction analysis. In most of the array formats, reporter molecules are used in multistep detection of the protein interactions. Among the few existing label-free detection approaches, surface plasmon resonance (SPR) and mass spectrometry (MS) stand out as most promising for utilization in protein microarrays, albeit both have been used only sporadically for high-content protein arrays. Shown here for the first time is the combination of SPR and MS detection on a single high-content protein microarray. Antibodies to five human plasma proteins were arrayed in a 10 x 10 spot arrangement on a chemically activated gold-coated glass chip. Binding of proteins to their corresponding antibodies was monitored via SPR imaging across the entire surface of the chip. Following protein affinity retrieval, the chip was overlaid with MALDI matrix and MS analyzed, producing protein-specific mass spectra from distinct spots on the array. The SPR-MS dual detection is well suited for high-content protein microarrays and comprehensive protein analysis-from quantitative assessment of the protein concentration to detection of structural protein variants arising from genetic variations and postexpression processing.

ErbB-2 induces the cyclin D1 gene in prostate epithelial cells in vitro and in vivo

The receptor tyrosine kinase ErbB-2 plays an important role in the regulation of growth factor-induced signal transduction cascades in the epithelium, and ErbB-2 is frequently overexpressed in epithelial tumors. Our previous studies on clinical prostate cancer specimens indicated that ErbB-2 expression was increased in patients undergoing hormone ablation therapy. We had also shown that the critical cell cycle regulatory gene cyclin D1 and its promoter were targets of proliferative signaling in prostate cancer cell lines, and that cyclin D1 was required for ErbB-2-induced mammary tumorigenesis. In the current studies, we found that increased ErbB-2 membrane expression correlated with increased nuclear cyclin D1 staining in clinical prostate cancer specimens, and that expression of ErbB-2 was capable of inducing cell cycle progression in human prostate cancer cell lines. We further showed that ErbB-2 induced the cyclin D1 promoter in DU145 cells, and that small interfering RNA knockdown of cyclin D1 protein levels blocked a significant proportion of the heregulin-induced cell cycle progression in LNCaP cells. Probasin promoter-targeted expression of an activated ErbB-2 isoform induced cyclin D1 expression in the mouse prostate, commensurate with prostate intraepithelial neoplasia. Together, these in vitro and in vivo studies identify cyclin D1 as a critical downstream target of ErbB-2 in the prostate epithelium, both of which are possible therapeutic targets for cancer intervention. Furthermore, our novel mouse model provides a useful platform for ongoing in vivo investigations of ErbB-2 signaling in the prostate epithelium.

A domain-based approach to predict protein-protein interactions

Background

Knowing which proteins exist in a certain organism or cell type and how these proteins interact with each other are necessary for the understanding of biological processes at the whole cell level. The determination of the protein-protein interaction (PPI) networks has been the subject of extensive research. Despite the development of reasonably successful methods, serious technical difficulties still exist. In this paper we present DomainGA, a quantitative computational approach that uses the information about the domain-domain interactions to predict the interactions between proteins.

Results

DomainGA is a multi-parameter optimization method in which the available PPI information is used to derive a quantitative scoring scheme for the domain-domain pairs. Obtained domain interaction scores are then used to predict whether a pair of proteins interacts. Using the yeast PPI data and a series of tests, we show the robustness and insensitivity of the DomainGA method to the selection of the parameter sets, score ranges, and detection rules. Our DomainGA method achieves very high explanation ratios for the positive and negative PPIs in yeast. Based on our cross-verification tests on human PPIs, comparison of the optimized scores with the structurally observed domain interactions obtained from the iPFAM database, and sensitivity and specificity analysis; we conclude that our DomainGA method shows great promise to be applicable across multiple organisms.

Conclusion

We envision the DomainGA as a first step of a multiple tier approach to constructing organism specific PPIs. As it is based on fundamental structural information, the DomainGA approach can be used to create potential PPIs and the accuracy of the constructed interaction template can be further improved using complementary methods. Explanation ratios obtained in the reported test case studies clearly show that the false prediction rates of the template networks constructed using the DomainGA scores are reasonably low, and the erroneous predictions can be filtered further using supplementary approaches such as those based on literature search or other prediction methods.

Systematic identification of SH3 domain-mediated human protein–protein interactions by peptide array target screening

Systematic identification of direct protein-protein interactions is often hampered by difficulties in expressing and purifying the corresponding full-length proteins. By taking advantage of the modular nature of many regulatory proteins, we attempted to simplify protein-protein interactions to the corresponding domain-ligand recognition and employed peptide arrays to identify such binding events. A group of 12 Src homology (SH) 3 domains from eight human proteins (Swiss-Prot ID: SRC, PLCG1, P85A, NCK1, GRB2, FYN, CRK) were used to screen a peptide target array composed of 1536 potential ligands, which led to the identification of 921 binary interactions between these proteins and 284 targets. To assess the efficiency of the peptide array target screening (PATS) method in identifying authentic protein-protein interactions, we examined a set of interactions mediated by the PLCgamma1 SH3 domain by coimmunoprecipitation and/or affinity pull-downs using full-length proteins and achieved a 75% success rate. Furthermore, we characterized a novel interaction between PLCgamma1 and hematopoietic progenitor kinase 1 (HPK1) identified by PATS and demonstrated that the PLCgamma1 SH3 domain negatively regulated HPK1 kinase activity. Compared to protein interactions listed in the online predicted human interaction protein database (OPHID), the majority of interactions identified by PATS are novel, suggesting that, when extended to the large number of peptide interaction domains encoded by the human genome, PATS should aid in the mapping of the human interactome.

Functional identification of novel activities: Activity-based selection of proteins from complete proteomes

The identification of proteins with desired activities, especially from complex samples such as plasma and whole blood, is a continual challenge. We have developed a technology platform called Functional Identification of Novel Activities (FIoNA) to discover desired protein activities from complex biological samples. FIoNA uses immobilized libraries of combinatorial peptide ligands to purify and concentrate essentially all of the components of a complex mixture on ligands synthesized on individual beads. No depletion or prefractionation of the starting material is performed before it is incubated with the library, and no a priori knowledge of the active protein or of the ligand to which it binds is required. Instead, the protein-loaded beads are individually evaluated en masse in disease- relevant assays to identify proteins possessing a desired function. Beads associated with the activity are selected, and the ligand is sequenced and resynthesized in bulk on the original backbone for purification and characterization of the active component. Here we illustrate the use of FIoNA in a cell proliferation assay to detect a growth factor present in conditioned cell medium at nanogram/milliliter concentrations. We also have selected beads associated with hydrolysis of nerve agent analogs in assays performed in 100,000-well microtiter plates.

HER2 therapy. HER2 (ERBB2): functional diversity from structurally conserved building blocks

EGFR-type receptor tyrosine kinases achieve a broad spectrum of cellular responses by utilizing a set of structurally conserved building blocks. Based on available crystal structures and biochemical information, significant new insights have emerged into modes of receptor control, its deregulation in cancer, and the nuances that differentiate the four human receptors. This review gives an overview of current models of the control of receptor activity with a special emphasis on HER2 and HER3.

Culture conditions affect proliferative responsiveness of olfactory ensheathing glia to neuregulins

Olfactory ensheathing glia (OEG) have been used to improve outcome after experimental spinal cord injury and are being trialed clinically. Their rapid proliferation in vitro is essential to optimize clinical application, with neuregulins (NRG) being potential mitogens. We examined the effects of NRG-1beta, NRG-2alpha, and NRG3 on proliferation of p75-immunopurified adult OEG. OEG were grown in serum-containing medium with added bovine pituitary extract and forskolin (added mitogens) or in serum-containing medium (no added mitogens). Cultures were switched to chemically defined medium (no added mitogens or serum), NRG added and OEG proliferation assayed using BrdU. OEG grown initially with added mitogens were not responsive to added NRGs and pre-exposure to forskolin and pituitary extract increased basal proliferation rates so that OEG no longer responded to added NRG. However, NRG promoted proliferation but only if cells were initially grown in mitogen-free medium. Primary OEG express ErbB2, ErbB3, and small levels of ErbB4 receptors; functional blocking indicates that ErbB2 and ErbB3 are the main NRG receptors utilized in the presence of NRG-1beta. The long-term stimulation of OEG proliferation by initial culture conditions raises the possibility of manipulating OEG before therapeutic transplantation.

EGFR kinase domain mutations - functional impact and relevance for lung cancer therapy

In 2004 remarkable clinical responses in non-small-cell lung cancer (NSCLC) patients treated with the epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor gefitinib were reported to correlate with the presence of certain somatic EGFR kinase domain mutations in tumors. Since then, a surge of enthusiasm has been encountered in the field of molecular and clinical oncology. Beyond the promise of a tailored medicine, questions about the molecular mechanisms underlying the observed effects have arisen. In vitro analysis of NSCLC cells with endogenous EGFR mutations, recombinant expression of EGFR variants by transfection of several cell lines and the generation of transgenic mice expressing mutant EGFR were applied to study the impact of these genetic alterations on cellular signaling and cell fate. This review outlines the current mechanistic knowledge derived from such studies and discusses the relevance of EGFR kinase domain mutations for EGFR-directed therapies, including monoclonal antibodies.

A Network Analysis of Changes in Molecular Interactions in Cellular Signaling

Multiprotein complexes play an essential role in the propagation and integration of cellular signals. However, systems level analyses of signaling-dependent changes in the pattern of molecular interactions are still missing. Signaling in T-lymphocytes is one prominent example in which multiprotein complexes orchestrate signal transduction. We implemented peptide microarrays comprising a set of interaction motifs of signaling proteins for network-based analyses of signaling-dependent changes in molecular interactions. Lysates of resting or stimulated cells were incubated on these arrays, and the binding of signaling proteins was detected by immunofluorescence. Signaling-dependent complex formation led to changes of signals on the microarrays in two ways. 1) Masking of a binding site of a signaling protein for a peptide on the array resulted in a signal decrease. 2) Interaction of a protein with a second protein, which in turn binds to a peptide on the array, resulted in a signal increase for the first protein. Dissipation of complexes led to the reverse changes. Competition with peptides corresponding to interaction motifs provided detailed information on the architecture of complexes; lack of individual signaling proteins revealed the functional interdependence of interactions in the network. We show that complex formation through phosphorylation of the scaffolding protein LAT (linker for activation of T-cells) acted as a signal amplifier. PLCgamma1 deficiency increased the resting state levels of LAT-dependent complexes and augmented the recruitment of the phosphatase SHPTP2 into complexes. For the analysis of signaling networks, the parallel detection of changes in interactions enabled the identification of functional interdependencies with minimum a priori knowledge.

Oncogenic re-wiring of cellular signaling pathways

Signaling pathways in mammalian cells are assembled and regulated by a finely controlled network of protein-protein and protein-phospholipid interactions, mediated by dedicated signaling domains and their cognate binding motifs. The domain-based modular architecture of signaling proteins may have facilitated the evolution of complex biological systems, and can be exploited experimentally to generate synthetic signaling pathways and artificial mechanisms of autoregulation. Pathogenic proteins, such as those encoded by bacteria and viruses, frequently form ectopic signaling complexes to respecify cellular behavior. In a similar fashion, proteins expressed as a consequence of oncogenic fusions, mutations or amplifications can elicit ectopic protein-protein interactions that re-wire signaling pathways, in a fashion that promotes malignancy. Compounds that directly or indirectly reverse these aberrant interactions offer new possibilities for therapy in cancer.

The EGF receptor family: spearheading a merger of signaling and therapeutics

The ErbB receptor tyrosine kinases evolved as key regulatory entities enabling the extracellular milieu to communicate with the intracellular machinery to bring forth the appropriate biological response in an ever-changing environment. Since its discovery, many aspects of the ErbB family have been deciphered, with emphasis on aberration of signaling in human diseases. However, only now, with the availability of the atomic coordinates of these receptors, can we construct a comprehensive model of the mechanisms underlying ligand-induced receptor dimerization and subsequent tyrosine kinase activation. Furthermore, the recent introduction of new high-throughput screening methodologies, combined with the materialization of a systems biology perspective, reveals an overwhelming network complexity, enabling robust signaling and evolvability. This knowledge is likely to impact our view of diseases as system perturbations and resistance to ErbB-targeted therapeutics as manifestations of robustness.

A chemical approach to the identification of tensin-binding proteins

Many protein-protein interactions are mediated by small modular domains, which recognize short peptide motifs in their partner proteins. However, for the great majority of these domains, the identity of their partner proteins remains unknown. In this work, a chemical/bioinformatics approach has been developed to identify phosphotyrosyl (pY) proteins that bind to tensin, a protein involved in the formation of actin cytoskeleton and signal transduction. A pY peptide library was chemically synthesized and screened against the Src homology 2 (SH2) domain of tensin to identify the peptide motifs that bind to the SH2 domain. Next, protein databases were searched for proteins containing the SH2 domain-binding peptide motifs. Finally, the potential tensin-binding proteins were confirmed (or disproved) by in vitro pull-down and coimmunoprecipitation assays. This procedure identified phosphoinositide-dependent kinase-1 and downstream of tyrosine kinase 2 as novel tensin-binding proteins. In addition, a cell-permeable pY peptide was designed as tensin SH2 domain inhibitor, which caused the disruption of actin filaments in NIH 3T3 cells. This method should be generally applicable to other modular domains that recognize small peptide motifs.

Receptor tyrosine kinases: mechanisms of activation and signaling

Receptor tyrosine kinases (RTKs) are essential components of signal transduction pathways that mediate cell-to-cell communication. These single-pass transmembrane receptors, which bind polypeptide ligands - mainly growth factors - play key roles in processes such as cellular growth, differentiation, metabolism and motility. Recent progress has been achieved towards an understanding of the precise (and varied) mechanisms by which RTKs are activated by ligand binding and by which signals are propagated from the activated receptors to downstream targets in the cell.

Dynamical regulations of protein-ligand bindings at single molecular level

We present new quantitative regulations of the binding-affinity using dynamical single-molecule detection system with X-rays. In the study of antigen-antibody interactions, we found that structural fluctuations of single-molecules were negatively regulated by antigen-binding. Although strategies to produce ligand-induced stability have been well studied from the macro aspect both theoretically and experimentally, our dynamical single-molecular experimental results are first observations with angstrom accuracy in the real-time and space. It is considered that those negative regulations of protein structural fluctuations with binding event are related to biological functions. In addition, we clarified that ratio between antigen-binding condition and no-binding one in observed structural fluctuations are extremely relative to the binding-affinity. These results indicate that the phenomena of protein-ligand interactions considered as stable states can be defined as results of dynamical processes at the single-molecule level. Such new quantifications from angstrom-level structural fluctuations can be applied to various biological science and biotechnologies.

The insulin and EGF receptor structures: new insights into ligand-induced receptor activation

The insulin receptor (IR) and epidermal growth factor receptor (EGFR; also known as ErbB) families exhibit similarities in the composition of their ectodomains. The past five years have seen structures determined for all members of the EGFR family including some complexes with ligand or monoclonal antibody fragments. These structures have led to a clearer understanding of their mechanism of activation and inhibition. By contrast, obtaining equivalent understanding of the IR family has lagged behind. However, within the past year, structures of partial and complete ectodomains of the IR have been published that show that the extracellular region of the receptor adopts an unexpected 'inverted V' conformation relative to the cell membrane. This is very different from the folded-over (tethered) conformation of the unactivated EGFR and provides insight into the potential mechanism of activation of the IR.

Protein tyrosine phosphatase 1B deficiency or inhibition delays ErbB2-induced mammary tumorigenesis and protects from lung metastasis

We investigated the role of protein tyrosine phosphatase 1B (PTP1B) in mammary tumorigenesis using both genetic and pharmacological approaches. It has been previously shown that transgenic mice with a deletion mutation in the region of Erbb2 encoding its extracellular domain (referred to as NDL2 mice, for 'Neu deletion in extracellular domain 2') develop mammary tumors that progress to lung metastasis. However, deletion of PTP1B activity in the NDL2 transgenic mice either by breeding with Ptpn1-deficient mice or by treatment with a specific PTP1B inhibitor results in significant mammary tumor latency and resistance to lung metastasis. In contrast, specific overexpression of PTP1B in the mammary gland leads to spontaneous breast cancer development. The regulation of ErbB2-induced mammary tumorigenesis by PTB1B occurs through the attenuation of both the MAP kinase (MAPK) and Akt pathways. This report provides a rationale for the development of PTP1B as a new therapeutic target in breast cancer.

Multivalence and spot heterogeneity in microarray-based measurement of binding constants

Microarray technology is increasingly used for a miniaturised and parallel measurement of binding constants. In microarray experiments heterogeneous functionalization of surfaces with capture molecules is a problem commonly encountered. For multivalent ligands, especially, however, binding is strongly affected by receptor density. Here we show that high-resolution imaging of microarrays followed by image segmentation and separate analysis of bright and dark parts provides valuable information about ligand binding. Binding titrations were conducted with monovalent and bivalent fluorescent ligand peptides for the model receptor vancomycin. Microarrays were scanned with a confocal microscope and inhomogeneous spots were evaluated either as a whole or after segmentation into bright and dark areas. Whereas the binding constant for the monovalent ligand was hardly affected by spot heterogeneity, for the bivalent ligand affinity was higher for the parts of the spots with a greater density of receptors. This information was lost if the spots were analysed as a whole. These results reveal that imaging resolution may be a key factor in miniaturised binding assays, emphasising the importance of high-resolution images and image segmentation for new techniques, for example SPR imaging.

A systems approach to measuring the binding energy landscapes of transcription factors

A major goal of systems biology is to predict the function of biological networks. Although network topologies have been successfully determined in many cases, the quantitative parameters governing these networks generally have not. Measuring affinities of molecular interactions in high-throughput format remains problematic, especially for transient and low-affinity interactions. We describe a high-throughput microfluidic platform that measures such properties on the basis of mechanical trapping of molecular interactions. With this platform we characterized DNA binding energy landscapes for four eukaryotic transcription factors; these landscapes were used to test basic assumptions about transcription factor binding and to predict their in vivo function.

Label-free detection methods for protein microarrays

With the growth of the "-omics" such as functional genomics and proteomics, one of the foremost challenges in biotechnologies has become the development of novel methods to monitor biological process and acquire the information of biomolecular interactions in a systematic manner. To fully understand the roles of newly discovered genes or proteins, it is necessary to elucidate the functions of these molecules in their interaction network. Microarray technology is becoming the method of choice for such a task. Although protein microarray can provide a high throughput analytical platform for protein profiling and protein-protein interaction, most of the current reports are limited to labeled detection using fluorescence or radioisotope techniques. These limitations deflate the potential of the method and prevent the technology from being adapted in a broader range of proteomics applications. In recent years, label-free analytical approaches have gone through intensified development and have been coupled successfully with protein microarray. In many examples of label-free study, the microarray has not only offered the high throughput detection in real time, but also provided kinetics information as well as in situ identification. This article reviews the most significant label-free detection methods for microarray technology, including surface plasmon resonance imaging, atomic force microscope, electrochemical impedance spectroscopy and MS and their applications in proteomics research.

Splice variants and expression patterns of SHEP1, BCAR3 and NSP1, a gene family involved in integrin and receptor tyrosine kinase signaling

SHEP1, BCAR3 and NSP1 are the three members of a family of cytoplasmic proteins involved in cell adhesion/migration and antiestrogen resistance. All three proteins contain an SH2 domain and an exchange factor-like domain that binds both Ras GTPases and the scaffolding protein Cas. SHEP1, BCAR3 and NSP1 mRNAs are widely expressed in tissues, and SHEP1 and BCAR3 have multiple splice variants that differ in their 5' untranslated regions and in some cases the beginning of their coding regions. Interestingly, our data suggest that SHEP1 is highly expressed in blood vessels in mouse breast cancer models. In contrast, BCAR3 and NSP1 are more highly expressed than SHEP1 in breast cancer cells. These expression patterns suggest differential roles for the three genes during breast cancer progression in either the vasculature or the tumor cells.

Cytomics - importance of multimodal analysis of cell function and proliferation in oncology

Cancer is a highly complex and heterogeneous disease involving a succession of genetic changes (frequently caused or accompanied by exogenous trauma), and resulting in a molecular phenotype that in turn results in a malignant specification. The development of malignancy has been described as a multistep process involving self-sufficiency in growth signals, insensitivity to antigrowth signals, evasion of apoptosis, limitless replicative potential, sustained angiogenesis, and finally tissue invasion and metastasis. The quantitative analysis of networking molecules within the cells might be applied to understand native-state tissue signalling biology, complex drug actions and dysfunctional signalling in transformed cells, that is, in cancer cells. High-content and high-throughput single-cell analysis can lead to systems biology and cytomics. The application of cytomics in cancer research and diagnostics is very broad, ranging from the better understanding of the tumour cell biology to the identification of residual tumour cells after treatment, to drug discovery. The ultimate goal is to pinpoint in detail these processes on the molecular, cellular and tissue level. A comprehensive knowledge of these will require tissue analysis, which is multiplex and functional; thus, vast amounts of data are being collected from current genomic and proteomic platforms for integration and interpretation as well as for new varieties of updated cytomics technology. This overview will briefly highlight the most important aspects of this continuously developing field.

Affinity profiling using the peptide microarray technology: a case study

Little about the reliability of measurements obtained using synthetic peptide microarrays is known. We report results from a study on the quantitative reliability of microarrays manufactured by robot-supported immobilization of presynthesized peptides for different microarray platforms. Technological precision is assessed for inter- and intra-device readout comparisons. Correlations between measured signals and known dissociation constants using a phenomenological model derived from the mass action law are discussed. Special emphasis is on discussing the pitfalls of high-throughput affinity measurements. We show that the quantitative determination of binding affinities is prone to be biased toward a mean affinity of around 10(-7)M, while the classification of peptides into either "binders" or "nonbinders" provides very high prediction accuracy. The experimental requirements needed to obtain reliable binding affinity predictions are discussed.

From protein-protein complexes to interactomics

Protein-protein interactions (or PPIs) are key elements for the normal functioning of a living cell. A large description of the protein interactomics field is given in this review where different aspects will be discussed. We first give an introduction of the different large scale experimental approaches from yeast two-hybrid to mass spectrometry used to discover PPIs and build protein interaction maps. Single PPI validation techniques such as co-immunoprecipitation or fluorescence methods are then presented as they are more and more integrated in global PPI discovery strategy. Data from different experimental sets are compared and an assessment of the different large scale technologies is presented. Bioinformatics tools can also predict with a good accuracy PPIs in silico, PPIs databases are now numerous and topological analysis has led to interesting insights into the nature of network connection. Finally, PPI, as an association of two proteins, has been structurally characterized for many protein complexes and is largely discussed throughout existing examples. The results obtained so far already provide the biologist with a large set of structured data from which knowledge on pathways and associated protein function can be extracted.

Reverse interactomics: decoding protein–protein interactions with combinatorial peptide libraries

Identification of binding partners is the crucial first step towards understanding the biological function of a protein. Many protein-protein interactions occur via modular domains that recognize short peptide motifs in their target proteins. Here we describe a chemical/bioinformatics approach for predicting the binding partners of modular domains. The optimal binding motif(s) of a protein domain is identified by screening a combinatorial peptide library. The resulting consensus sequence is used to search protein and genomic databases for potential binding proteins, which are subsequently confirmed (or disproved) by conventional protein binding assays (e.g. pull-down and co-immunoprecipitation).

Protein binding microarrays for the characterization of DNA-protein interactions

A number of important cellular processes, such as transcriptional regulation, recombination, replication, repair, and DNA modification, are performed by DNA binding proteins. Of particular interest are transcription factors (TFs) which, through their sequence-specific interactions with DNA binding sites, modulate gene expression in a manner required for normal cellular growth and differentiation, and also for response to environmental stimuli. Despite their importance, the DNA binding specificities of most DNA binding proteins still remain unknown, since prior technologies aimed at identifying DNA-protein interactions have been laborious, not highly scalable, or have required limiting biological reagents. Recently a new DNA microarray-based technology, termed protein binding microarrays (PBMs), has been developed that allows rapid, high-throughput characterization of the in vitro DNA binding site sequence specificities of TFs, other DNA binding proteins, or synthetic compounds. DNA binding site data from PBMs combined with gene annotation data, comparative sequence analysis, and gene expression profiling, can be used to predict what genes are regulated by a given TF, what the functions are of a given TF and its predicted target genes, and how that TF may fit into the cell's transcriptional regulatory network.

A Peptide Microarray for the Detection of Protein Kinase Activity in Cell Lysate

DNA microarray enables the analysis of DNA or mRNA expression levels, but it has not been possible to completely understand life using obtained information. Consequently, protein or peptide arrays have attracted much interest. Since the development of a practical protein microarray is still far away in light of handling difficulties, the peptide microarray is a promising tool for analyzing protein functions. We have developed a peptide microarray to detect protein kinase activity in cell lysate. All substrate peptides for kinases were immobilized chemoselectively on amino-coated glass slides. After phosphorylation of the immobilized peptides, phosphorylation was detected by fluorescence imaging. We detected the protein kinase activities, including that in cell lysate, in response to drug stimulation. Therefore, this peptide microarray would be useful for a high-throughput kinase assay of intracellular signals and would be applicable to drug screening.

Using product kernels to predict protein interactions

There is a wide variety of experimental methods for the identification of protein interactions. This variety has in turn spurred the development of numerous different computational approaches for modeling and predicting protein interactions. These methods range from detailed structure-based methods capable of operating on only a single pair of proteins at a time to approximate statistical methods capable of making predictions on multiple proteomes simultaneously. In this chapter, we provide a brief discussion of the relative merits of different experimental and computational methods available for identifying protein interactions. Then we focus on the application of our particular (computational) method using Support Vector Machine product kernels. We describe our method in detail and discuss the application of the method for predicting protein-protein interactions, beta-strand interactions, and protein-chemical interactions.

An enzyme that regulates ether lipid signaling pathways in cancer annotated by multidimensional profiling

Hundreds, if not thousands, of uncharacterized enzymes currently populate the human proteome. Assembly of these proteins into the metabolic and signaling pathways that govern cell physiology and pathology constitutes a grand experimental challenge. Here, we address this problem by using a multidimensional profiling strategy that combines activity-based proteomics and metabolomics. This approach determined that KIAA1363, an uncharacterized enzyme highly elevated in aggressive cancer cells, serves as a central node in an ether lipid signaling network that bridges platelet-activating factor and lysophosphatidic acid. Biochemical studies confirmed that KIAA1363 regulates this pathway by hydrolyzing the metabolic intermediate 2-acetyl monoalkylglycerol. Inactivation of KIAA1363 disrupted ether lipid metabolism in cancer cells and impaired cell migration and tumor growth in vivo. The integrated molecular profiling method described herein should facilitate the functional annotation of metabolic enzymes in any living system.

Multiplexed Detection of Protein−Peptide Interaction and Inhibition Using Capillary Electrophoresis

High-speed capillary electrophoresis (CE) was employed to detect binding and inhibition of SH2 domain proteins using fluorescently labeled phosphopeptides as affinity probes. Single SH2 protein-phosphopeptide complexes were detected and confirmed by competition and fluorescence anisotropy. The assay was then extended to a multiplexed system involving separation of three SH2 domain proteins: Src, SH2-Bbeta, and Fyn. The selectivity of the separation was improved by altering the charge of the peptide binding partners used, thus demonstrating a convenient way to control resolution for the multiplexed assay. The separation was completed within 6 s, allowing rapidly dissociating complexes to be detected. Two low molecular weight inhibitors were tested for inhibition selectivity and efficacy. One inhibitor interrupted binding interaction of all three proteins, while the other selectively inhibited Src only leaving SH2-Bbeta and Fyn complex barely affected. IC(50) of both selective and nonselective inhibitors were determined and compared for different proteins. The IC(50) of the nonselective inhibitor was 49 +/- 9, 323 +/- 42, and 228 +/- 19 microM (n = 3) for Src, SH2-Bbeta, and Fyn, respectively, indicating different efficacy of the nonselective inhibitor for different SH2 domain protein. It is concluded that high-speed CE has the potential for multiplexed screening of drugs that disrupt protein-protein interactions.

Quantitative transcriptional control of ErbB receptor signaling undergoes graded to biphasic response for cell differentiation

ErbB receptor ligands, epidermal growth factor (EGF) and heregulin (HRG), induce dose-dependent transient and sustained intracellular signaling, proliferation, and differentiation of MCF-7 breast cancer cells, respectively. In an effort to delineate the ligand-specific cell determination mechanism, we investigated time course gene expressions induced by EGF and HRG that induce distinct cellular phenotypes in MCF-7 cells. To analyze independently the effects of ligand dosage and time for gene expression, we developed a statistical method for estimating the two effects. Our results indicated that signal transduction pathways convey quantitative properties of the dose-dependent activation of ErbB receptor to early transcription. The results also implied that moderate changes in the expression levels of a number of genes, not the predominant regulation of a few specific genes, might cooperatively work at the early stage of the transcription for determining cell fate. However, the EGF- and HRG-induced distinct signal durations resulted in the ligand-oriented biphasic induction of proteins after 20 min. The selected gene list and HRG-induced prolonged signaling suggested that transcriptional feedback to the intracellular signaling results in a graded to biphasic response in the cell determination process and that each ErbB receptor is inextricably responsible for the control of amplitude and duration of cellular biochemical reactions.