Abi activates WASP to promote sensory organ development.

Actin polymerization is a key process for many cellular events during development. To a large extent, the formation of filamentous actin is controlled by the WASP and WAVE proteins that activate the Arp2/3 complex in different developmental processes. WAVE function is regulated through a protein complex containing Sra1, Kette and Abi. Using biochemical, cell biological and genetic tools, we show here that the Abi protein also has a central role in activating WASP-mediated processes. Abi binds WASP through its carboxy-terminal domain and acts as a potent stimulator of WASP-dependent F-actin formation. To elucidate the biological function of abi in Drosophila melanogaster, we studied bristle development, a process known to require wasp function. Reduction of abi function leads to a loss of bristles similar to that observed in wasp mutants. Activation of Abi results in the formation of ectopic bristles, a phenotype that is suppressed by a reduction of wasp activity but is not affected by the reduction of wave function. Thus, in vivo Abi may set the balance between WASP and WAVE in different actin-based developmental processes.

Contact spotting of protein microarrays coupled with spike-in of normalizer protein permits time-resolved analysis of ERBB receptor signaling.

Protein microarrays allow highly accurate comparison and quantification of numerous biological samples in parallel while requiring only little material. This qualifies protein arrays for systems biology and clinical research where only limited sample material is available, but a precise readout is required. With the introduction of signal normalization steps to monitor the drop size of manually contact-spotted RP protein arrays, the usefulness of normalizer proteins to ensure a high-throughput but inexpensive protein analysis was demonstrated. This approach was applied for the analysis of signaling through ERBB receptor activated kinases in the breast cancer cell line MCF-7. Activation of ERK1/2 and AKT by ERBB1 (EGFR), ERRB2 (HER2/neu), and ERBB3-4 was monitored in a time-resolved manner. Analysis of pathway activation by stimulation with epidermal growth factor and heregulin, or inhibition by blocking with gefitinib or herceptin allowed a characterization of the distinct signaling properties of the different ERBB receptor subtypes.

Antibody microarrays as an experimental platform for the analysis of signal transduction networks.

A significant bottleneck for the time-resolved and quantitative description of signaling networks is the limited sample capacity and sensitivity of existing methods. Recently, antibody microarrays have emerged as a promising experimental platform for the quantitative and comprehensive determination of protein abundance and protein phosphorylation. This review summarizes the development of microarray applications involving antibody-based capture of target proteins with a focus on quantitative applications. Technical aspects regarding the production of antibody microarrays, identification of suitable detection and capture antibody pairs, signal detection methods, detection limit, and data analysis are discussed in detail.

Reverse-phase protein arrays for application-orientated cancer research.

A detailed and quantitative analysis of disease-relevant signaling will greatly contribute to our understanding of tumorigenesis and cancer progression, and thus open new strategies for drug discovery. However, throughput and sensitivity of currently established methods available for proteome profiling do not comply with the needs of clinical research such as high sample capacity and low sample consumption. Protein microarrays emerged as a promising alternative to analyze the abundance of proteins and their phosphorylation status on a high-throughput level. Here we summarize recent methodological advancements in the field of reverse-phase protein arrays and demonstrate their potential for clinical research as well as for in vitro applications.

Modeling ERBB receptor-regulated G1/S transition to find novel targets for de novo trastuzumab resistance.

BACKGROUND: In breast cancer, overexpression of the transmembrane tyrosine kinase ERBB2 is an adverse prognostic marker, and occurs in almost 30% of the patients. For therapeutic intervention, ERBB2 is targeted by monoclonal antibody trastuzumab in adjuvant settings; however, de novo resistance to this antibody is still a serious issue, requiring the identification of additional targets to overcome resistance. In this study, we have combined computational simulations, experimental testing of simulation results, and finally reverse engineering of a protein interaction network to define potential therapeutic strategies for de novo trastuzumab resistant breast cancer. RESULTS: First, we employed Boolean logic to model regulatory interactions and simulated single and multiple protein loss-of-functions. Then, our simulation results were tested experimentally by producing single and double knockdowns of the network components and measuring their effects on G1/S transition during cell cycle progression. Combinatorial targeting of ERBB2 and EGFR did not affect the response to trastuzumab in de novo resistant cells, which might be due to decoupling of receptor activation and cell cycle progression. Furthermore, examination of c-MYC in resistant as well as in sensitive cell lines, using a specific chemical inhibitor of c-MYC (alone or in combination with trastuzumab), demonstrated that both trastuzumab sensitive and resistant cells responded to c-MYC perturbation. CONCLUSION: In this study, we connected ERBB signaling with G1/S transition of the cell cycle via two major cell signaling pathways and two key transcription factors, to model an interaction network that allows for the identification of novel targets in the treatment of trastuzumab resistant breast cancer. Applying this new strategy, we found that, in contrast to trastuzumab sensitive breast cancer cells, combinatorial targeting of ERBB receptors or of key signaling intermediates does not have potential for treatment of de novo trastuzumab resistant cells. Instead, c-MYC was identified as a novel potential target protein in breast cancer cells.

Infrared-based protein detection arrays for quantitative proteomics.

BACKGROUND: Protein microarrays have the potential to join the field of quantitative proteomics as a standard method. This antibody-based experimental platform allows the highly sensitive and highly specific quantification of selected target proteins and excels with high sample capacity. As a key feature, numerous arrays can be produced in parallel, thus minimizing sample consumption. OBJECTIVE: The recent progress made in the field of reverse phase protein arrays is summarized, with a focus on the introduction of normalization measures, as introduced in the authors' infrared-based protein arrays with quantitative readout approach. CONCLUSION: Tumor biology as well as drug discovery applications will soon benefit from the comprehensive description of signaling pathways and protein microarrays are an appropriate tool to achieve this goal.

Combinatorial RNAi for quantitative protein network analysis.

The elucidation of cross-talk events between intersecting signaling pathways is one main challenge in biological research. The complexity of protein networks, composed of different pathways, requires novel strategies and techniques to reveal relevant interrelations. Here, we established a combinatorial RNAi strategy for systematic single, double, and triple knockdown, and we measured the residual mRNAs and proteins quantitatively by quantitative real-time PCR and reverse-phase protein arrays, respectively, as a prerequisite for data analysis. Our results show that the parallel knockdown of at least three different genes is feasible while keeping both untargeted silencing and cytotoxicity low. The technique was validated by investigating the interplay of tyrosine kinase receptor ErbB2 and its downstream targets Akt-1 and MEK1 in cell invasion. This experimental approach combines multiple gene knockdown with a subsequent quantitative validation of reduced protein expression and is a major advancement toward the analysis of signaling pathways in systems biology.