QUICK identification and SPR validation of signal transducers and activators of transcription 3 (Stat3) interacting proteins

Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) for Quantitative Proteomics

Stable isotope labeling by amino acids in cell culture (SILAC) is a powerful approach for high-throughput quantitative proteomics. SILAC allows highly accurate protein quantitation through metabolic encoding of whole cell proteomes using stable isotope labeled amino acids. Since its introduction in 2002, SILAC has become increasingly popular. In this chapter we review the methodology and application of SILAC, with an emphasis on three research areas: dynamics of posttranslational modifications, protein-protein interactions, and protein turnover.

Current Understanding of the TCTP Interactome

Evolutionarily conserved and pleiotropic, the translationally controlled tumor protein (TCTP) is a housekeeping protein present in eukaryotic organisms. It plays an important role in regulating many fundamental processes, such as cell proliferation, cell death, immune responses, and apoptosis. As a result of the pioneer work by Adam Telerman and Robert Amson, the critical role of TCTP in tumor reversion was revealed. Moreover, TCTP has emerged as a regulator of cell fate determination and a promising therapeutic target for cancers. The multifaceted action of TCTP depends on its ability to interact with different proteins. Through this interaction network, TCTP regulates diverse physiological and pathological processes in a context-dependent manner. Complete mapping of the entire sets of TCTP protein interactions (interactome) is essential to understand its various cellular functions and to lay the foundation for the rational design of TCTP-based therapeutic approaches. So far, the global profiling of the interacting partners of TCTP has rarely been performed, but many interactions have been identified in small-scale studies in a specific biological system. This chapter, based on information from protein interaction databases and the literature, illustrates current knowledge of the TCTP interactome.

4-Carbonyl-2,6-dibenzylidenecyclohexanone derivatives as small molecule inhibitors of STAT3 signaling pathway

Inhibition of STAT3 signaling pathway is proposed to be a promising strategy for cancer treatment. In this study, a series of 4-carbonyl-2,6-dibenzylidenecyclohexanone derivatives were prepared and evaluated as anticancer agents. The most potent compound 13r was discovered to exhibit antiproliferative activity against a broad rang of cancer cell lines and relatively low cytotoxicity against normal human cells. Besides, 13r effectively suppressed STAT3 expression as well as phosphorylation, and surface plasmon resonance analysis confirmed the direct interaction of 13r with STAT3. Docking simulation showed that 13r could inhibit STAT3 by targeting SH2 domain. This study provided evidence for these compounds to be further developed as antitumor agents through inhibition of the STAT3 pathway.

A mass spectrometry view of stable and transient protein interactions

Through an impressive range of dynamic interactions, proteins succeed to carry out the majority of functions in a cell. These temporally and spatially regulated interactions provide the means through which one single protein can perform diverse functions and modulate different cellular pathways. Understanding the identity and nature of these interactions is therefore critical for defining protein functions and their contribution to health and disease processes. Here, we provide an overview of workflows that incorporate immunoaffinity purifications and quantitative mass spectrometry (frequently abbreviated as IP-MS or AP-MS) for characterizing protein-protein interactions. We discuss experimental aspects that should be considered when optimizing the isolation of a protein complex. As the presence of nonspecific associations is a concern in these experiments, we discuss the common sources of nonspecific interactions and present label-free and metabolic labeling mass spectrometry-based methods that can help determine the specificity of interactions. The effective regulation of cellular pathways and the rapid reaction to various environmental stresses rely on the formation of stable, transient, and fast-exchanging protein-protein interactions. While determining the exact nature of an interaction remains challenging, we review cross-linking and metabolic labeling approaches that can help address this important aspect of characterizing protein interactions and macromolecular assemblies.

Phosphorylated STAT3 physically interacts with NPM and transcriptionally enhances its expression in cancer

The signal transducer and activator of transcription 3 (STAT3) can be activated by the tyrosine kinase domain of the chimeric protein nucleophosmin/anaplastic lymphoma kinase (NPM/ALK), and has a pivotal role in mediating NPM/ALK-related malignant cell transformation. Although the role of STAT3 and wild-type NPM in oncogenesis has been extensively investigated, the relationship between both molecules in cancer remains poorly understood. In the present study, we first demonstrate that STAT3 phosphorylation at tyrosine 705 is accompanied by a concomitant increase in the expression level of NPM. Nuclear co-translocation of phosphorylated STAT3 with NPM can be triggered by interferon-alpha (IFN-α) stimulation of Jurkat cells and phosphorylated STAT3 co-localizes with NPM in cancer cells showing constitutive STAT3 activation. We further demonstrate that STAT3 phosphorylation can transcriptionally mediate NPM upregulation in IFN-α-stimulated Jurkat cells and is responsible for maintaining its expression in cancer cells showing constitutive STAT3 activation. Inhibition of STAT3 phosphorylation or knockdown of NPM expression abrogates their simultaneous transnuclear movements. Finally, we found evidence for a physical interaction between NPM and STAT3 in conditions of STAT3 activation. In conclusion, NPM is a downstream effector of the STAT3 signaling, and can facilitate the nuclear entry of phosphorylated STAT3. These observations might open novel opportunities for targeting the STAT3 pathway in cancer.

Real-time quantification of proteins secreted by artificial connective tissue made from uni- or multidirectional collagen I scaffolds and oral mucosa fibroblasts

Previously, we found that oral autologous artificial connective tissue (AACT) had a different protein secretion profile to that of clot-embedded AACT. Other oral mucosa substitutes, having different cell types and scaffolds, had dissimilar secretion profiles of proteins (including that for AACT) that influence healing outcome; thus, to ascertain the profiles of factors secreted by artificial tissue and whether they are influenced by their microstructure might help in understanding their bioactivity. An important component of tissue microstructure is the fiber orientation of the scaffold used for manufacturing it. This work developed a surface plasmon resonance (SPR) methodology to quantify factors secreted by oral artificial connective tissue (ACT) in culture medium, and a method to manufacture unidirectional laminar collagen I scaffolds. The SPR methodology was used for assessing differences in the protein secretion profile of ACT made with collagen scaffolds having different fiber orientation (unidirectional vs multidirectional). Oral fibroblasts seeded onto unidirectional scaffolds increased the secretion of six factors involved in modulating healing compared to those seeded onto multidirectional scaffolds. Histological analysis of uni- and multidirectional ACT showed that cells differ in their alignment and morphology. This SPR-methodology led to nanoscale detection of paracrine factors and might be useful to study biomarkers of three-dimensional cell growth, cell differentiation, and wound-healing progression.

Stable isotope labeling by amino acids in cell culture (SILAC) for quantitative proteomics

Stable isotope labeling by amino acids in cell culture (SILAC) is a powerful approach for high-throughput quantitative proteomics. SILAC allows highly accurate protein quantitation through metabolic encoding of whole cell proteomes using stable isotope labeled amino acids. Since its introduction in 2002, SILAC has become increasingly popular. In this chapter we review the methodology and application of SILAC, with an emphasis on three research areas: dynamics of posttranslational modifications, protein-protein interactions, and protein turnover.

Approaches for assessing and discovering protein interactions in cancer

Significant insight into the function of proteins can be delineated by discovering and characterizing interacting proteins. There are numerous methods for the discovery of unknown associated protein networks, with purification of the bait (the protein of interest) followed by mass spectrometry as a common theme. In recent years, advances have permitted the purification of endogenous proteins and methods for scaling down starting material. As such, approaches for rapid, unbiased identification of protein interactomes are becoming a standard tool in the researchers toolbox, rather than a technique that is only available to specialists. This review will highlight some of the recent technical advances in proteomic-based discovery approaches, the pros and cons of various methods and some of the key findings in cancer-related systems.

Analysis of the STAT3 interactome using in-situ biotinylation and SILAC

Signal transducer and activator of transcription 3 (STAT3) is activated by a variety of cytokines and growth factors. To generate a comprehensive data set of proteins interacting specifically with STAT3, we applied stable isotope labeling with amino acids in cell culture (SILAC). For high-affinity pull-down using streptavidin, we fused STAT3 with a short peptide tag allowing biotinylation in situ (bio-tag), which did not affect STAT3 functions. By this approach, 3642 coprecipitated proteins were detected in human embryonic kidney-293 cells. Filtering using statistical and functional criteria finally extracted 136 proteins as putative interaction partners of STAT3. Both, a physical interaction network analysis and the enrichment of known and predicted interaction partners suggested that our filtering criteria successfully enriched true STAT3 interactors. Our approach identified numerous novel interactors, including ones previously predicted to associate with STAT3. By reciprocal coprecipitation, we were able to verify the physical association between STAT3 and selected interactors, including the novel interaction with TOX4, a member of the TOX high mobility group box family. Applying the same method, we next investigated the activation-dependency of the STAT3 interactome. Again, we identified both known and novel interactions. Thus, our approach allows to study protein-protein interaction effectively and comprehensively.

BIOLOGICAL SIGNIFICANCE

The location, activity, function, degradation, and synthesis of proteins are significantly regulated by interactions of proteins with other proteins, biopolymers and small molecules. Thus, the comprehensive characterization of interactions of proteins in a given proteome is the next milestone on the path to understanding the biochemistry of the cell. In order to generate a comprehensive interactome dataset of proteins specifically interacting with a selected bait protein, we fused our bait protein STAT3 with a short peptide tag allowing biotinylation in situ (bio-tag). This bio-tag allows an affinity pull-down using streptavidin but affected neither the activation of STAT3 by tyrosine phosphorylation nor its transactivating potential. We combined SILAC for accurate relative protein quantification, subcellular fractionation to increase the coverage of interacting proteins, high-affinity pull-down and a stringent filtering method to successfully analyze the interactome of STAT3. With our approach we confirmed several already known and identified numerous novel STAT3 interactors. The approach applied provides a rapid and effective method, which is broadly applicable for studying protein-protein interactions and their dependency on post-translational modifications.

Bcl2-associated athanogene 3 interactome analysis reveals a new role in modulating proteasome activity

Bcl2-associated athanogene 3 (BAG3), a member of the BAG family of co-chaperones, plays a critical role in regulating apoptosis, development, cell motility, autophagy, and tumor metastasis and in mediating cell adaptive responses to stressful stimuli. BAG3 carries a BAG domain, a WW domain, and a proline-rich repeat (PXXP), all of which mediate binding to different partners. To elucidate BAG3's interaction network at the molecular level, we employed quantitative immunoprecipitation combined with knockdown and human proteome microarrays to comprehensively profile the BAG3 interactome in humans. We identified a total of 382 BAG3-interacting proteins with diverse functions, including transferase activity, nucleic acid binding, transcription factors, proteases, and chaperones, suggesting that BAG3 is a critical regulator of diverse cellular functions. In addition, we characterized interactions between BAG3 and some of its newly identified partners in greater detail. In particular, bioinformatic analysis revealed that the BAG3 interactome is strongly enriched in proteins functioning within the proteasome-ubiquitination process and that compose the proteasome complex itself, suggesting that a critical biological function of BAG3 is associated with the proteasome. Functional studies demonstrated that BAG3 indeed interacts with the proteasome and modulates its activity, sustaining cell survival and underlying resistance to therapy through the down-modulation of apoptosis. Taken as a whole, this study expands our knowledge of the BAG3 interactome, provides a valuable resource for understanding how BAG3 affects different cellular functions, and demonstrates that biologically relevant data can be harvested using this kind of integrated approach.

Quantitative proteomics: A strategic ally to map protein interaction networks

Many physiological processes are regulated by dynamic protein interaction networks whose characterization provides valuable information on cell biology. Several strategies can be used to analyze protein-protein interactions. Among them, affinity purification combined with mass spectrometry (AP-MS) is arguably the most widely employed technique, not only owing to its high throughput and sensitivity but also because it can answer critical questions such as where, when, and how protein-protein interactions occur. In AP-MS workflows, both the target protein and its interacting partners are isolated before being identified by MS. The main challenge of this approach is to distinguish bona fide binders from background contaminants. This review focuses on the different strategies designed to circumvent this limitation. In this regard, the combination of quantitative proteomics and affinity purification emerges as one of the most powerful, yet relatively simple, strategies to characterize protein-protein interactions.