Robust co-regulation of tyrosine phosphorylation sites on proteins reveals novel protein interactions

PDLIM1 interacts with HK2 to promote gastric cancer progression through enhancing the Warburg effect via Wnt/β-catenin signaling

PDZ and LIM domain protein 1 (PDLIM1) is a cytoskeletal protein and is associated with the malignant pathological features of several tumors. However, the prognostic value of PDLIM1 and the molecular mechanisms by which it is involved in the metabolism and progression in gastric cancer (GC) are still unclear. The GEPIA database was used to predict the expression and prognosis of PDLIM1 in GC. qRT-PCR and western blot assays were applied to detect the mRNA and protein expression in GC tissues and cells. Loss- and gain-of-function experiments were performed to evaluate the biological role of PDLIM1 in GC cells. The Warburg effect was detected by a battery of glycolytic indicators. The interaction of PDLIM1 and hexokinase 2 (HK2) was determined by a co-immunoprecipitation assay. Furthermore, the modulatory effects of PDLIM1 and HK2 on Wnt/β-catenin signaling were assessed. The results showed that PDLIM1 expression was upregulated in GC tissues and cells and was associated with a poor prognosis for GC patients. PDLIM1 inhibition reduced GC cell proliferation, migration and invasion and promoted cell apoptosis. In the glucose deprivation (GLU-D) condition, the PDLIM1 level was reduced and PDLIM1 overexpression led to an increase in glycolysis. Besides, mechanistic investigation showed that PDLIM1 interacted with HK2 to mediate biological behaviors and the glycolysis of GC through Wnt/β-catenin signaling under glucose deprivation. In conclusion, PDLIM1 interacts with HK2 to promote gastric cancer progression by enhancing the Warburg effect via Wnt/β-catenin signaling.

The unexpected versatility of ALP/Enigma family proteins

One of the most intriguing features of multicellular animals is their ability to move. On a cellular level, this is accomplished by the rearrangement and reorganization of the cytoskeleton, a dynamic network of filamentous proteins which provides stability and structure in a stationary context, but also facilitates directed movement by contracting. The ALP/Enigma family proteins are a diverse group of docking proteins found in numerous cellular milieus and facilitate these processes among others. In vertebrates, they are characterized by having a PDZ domain in combination with one or three LIM domains. The family is comprised of CLP-36 (PDLIM1), Mystique (PDLIM2), ALP (PDLIM3), RIL (PDLIM4), ENH (PDLIM5), ZASP (PDLIM6), and Enigma (PDLIM7). In this review, we will outline the evolution and function of their protein domains which confers their versatility. Additionally, we highlight their role in different cellular environments, focusing specifically on recent advances in muscle research using Drosophila as a model organism. Finally, we show the relevance of this protein family to human myopathies and the development of muscle-related diseases.

Phosphoproteomics: a valuable tool for uncovering molecular signaling in cancer cells

INTRODUCTION

Many pathologies, including cancer, have been associated with aberrant phosphorylation-mediated signaling networks that drive altered cell proliferation, migration, metabolic regulation, and can lead to systemic inflammation. Phosphoproteomics, the large-scale analysis of protein phosphorylation sites, has emerged as a powerful tool to define signaling network regulation and dysregulation in normal and pathological conditions.

AREAS COVERED

We provide an overview of methodology for global phosphoproteomics as well as enrichment of specific subsets of the phosphoproteome, including phosphotyrosine and phospho-motif enrichment of kinase substrates. We review quantitative methods, advantages and limitations of different mass spectrometry acquisition formats, and computational approaches to extract biological insight from phosphoproteomics data. Throughout, we discuss various applications and their challenges in implementation.

EXPERT OPINION

Over the past 20 years the field of phosphoproteomics has advanced to enable deep biological and clinical insight through the quantitative analysis of signaling networks. Future areas of development include Clinical Laboratory Improvement Amendments (CLIA)-approved methods for analysis of clinical samples, continued improvements in sensitivity to enable analysis of small numbers of rare cells and tissue microarrays, and computational methods to integrate data resulting from multiple systems-level quantitative analytical methods.

PDLIM1: Structure, function and implication in cancer

PDLIM1, a member of the PDZ-LIM family, is a cytoskeletal protein and functions as a platform to form distinct protein complexes, thus participating in multiple physiological processes such as cytoskeleton regulation and synapse formation. Emerging evidence demonstrates that PDLIM1 is dysregualted in a variety of tumors and plays essential roles in tumor initiation and progression. In this review, we summarize the structure and function of PDLIM1, as well as its important roles in human cancers.

Mass Spectrometry-Based Analysis of Time-Resolved Proteome Quantification

The aspect of time is essential in biological processes and thus it is important to be able to monitor signaling molecules through time. Proteins are key players in cellular signaling and they respond to many stimuli and change their expression in many time-dependent processes. Mass spectrometry (MS) is an important tool for studying proteins, including their posttranslational modifications and their interaction partners-both in qualitative and quantitative ways. In order to distinguish the different trends over time, proteins, modification sites, and interacting proteins must be compared between different time points, and therefore relative quantification is preferred. In this review, the progress and challenges for MS-based analysis of time-resolved proteome dynamics are discussed. Further, aspects on model systems, technologies, sampling frequencies, and presentation of the dynamic data are discussed.

Targeted Quantification of Phosphorylation Dynamics in the Context of EGFR-MAPK Pathway

Large-scale phosphoproteomics with coverage of over 10,000 sites of phosphorylation have now been routinely achieved with advanced mass spectrometry (MS)-based workflows. However, accurate targeted MS-based quantification of phosphorylation dynamics, an important direction for gaining quantitative understanding of signaling pathways or networks, has been much less investigated. Herein, we report an assessment of the targeted workflow in the context of signal transduction pathways, using the epidermal growth factor receptor (EGFR)-mitogen-activated protein kinase (MAPK) pathway as our model. A total of 43 phosphopeptides from the EGFR-MAPK pathway were selected for the study. The recovery and sensitivity of two commonly used enrichment methods, immobilized metal affinity chromatography (IMAC) and titanium oxide (TiO₂), combined with selected reaction monitoring (SRM)-MS were evaluated. The recovery of phosphopeptides by IMAC and TiO₂ enrichment was quantified to be 38 ± 5% and 58 ± 20%, respectively, based on internal standards. Moreover, both enrichment methods provided comparable sensitivity from 1 to 100 μg starting peptides. Robust quantification was consistently achieved for most targeted phosphopeptides when starting with 25-100 μg peptides. However, the numbers of quantified targets significantly dropped when peptide samples were in the 1-25 μg range. Finally, IMAC-SRM was applied to quantify signaling dynamics of EGFR-MAPK pathway in Hs578T cells following 10 ng/mL EGF treatment. The kinetics of phosphorylation clearly revealed early and late phases of phosphorylation, even for very low abundance proteins. These results demonstrate the feasibility of robust targeted quantification of phosphorylation dynamics for specific pathways, even starting with relatively small amounts of protein.

VEGFR1 promotes cell migration and proliferation through PLCγ and PI3K pathways

The ability to control vascular endothelial growth factor (VEGF) signaling offers promising therapeutic potential for vascular diseases and cancer. Despite this promise, VEGF-targeted therapies are not clinically effective for many pathologies, such as breast cancer. VEGFR1 has recently emerged as a predictive biomarker for anti-VEGF efficacy, implying a functional VEGFR1 role beyond its classically defined decoy receptor status. Here we introduce a computational approach that accurately predicts cellular responses elicited via VEGFR1 signaling. Aligned with our model prediction, we show empirically that VEGFR1 promotes macrophage migration through PLCγ and PI3K pathways and promotes macrophage proliferation through a PLCγ pathway. These results provide new insight into the basic function of VEGFR1 signaling while offering a computational platform to quantify signaling of any receptor.

Ensemble clustering of phosphoproteomic data identifies differences in protein interactions and cell-cell junction integrity of HER2-overexpressing cells

Overexpression of HER2, a receptor tyrosine kinase of the ERBB family, in breast cancer is related to increased cancer progression and aggressiveness. A breast epithelial cell model with the single perturbation of HER2 overexpression is capable of replicating the increased aggressiveness of HER2 overexpressing cancers. In previous work, Wolf-Yadlin and colleagues (Wolf-Yadlin et al., Mol. Syst. Biol., 2006, 2) measured the proximal tyrosine phosphorylation dynamics of the parental and HER2 overexpressing cells (24H) in response to EGF. Here, we apply an ensemble clustering approach to dynamic phosphorylation measurements of the two cell models in order to identify signaling events that explain the increased migratory potential of HER2 overexpressing cells. The use of an ensemble approach for identifying relationships within a dataset and how these relationships change across datasets uncovers relationships that cannot be found by the direct comparison of dynamic responses in the two conditions. Of particular note is a drastic change in the clustering of SHC1 phosphorylation (on site Y349) from an EGFR-MAPK module in parental cells to a module consisting of an E-cadherin junction protein phosphorylation site, catenin delta-1 Y228, in HER2 overexpressing (24H) cells. Given the importance of E-cadherin junctions in healthy epithelial wound healing and migration, we chose to test the computationally-derived identification of altered cell junctions and CTNND1:SHC1 relationships. Our cell and molecular biology experiments demonstrate that SHC and CTNND1 interact in an EGF- and HER2-dependent manner and that the cell junctions are phenotypically affected by HER2, breaking down in response to EGF and yet avoiding apoptosis as a result of cell junction loss. The results suggest a mechanism by which HER2 alters the localization of the SHC-MAPK signaling axis and a phenotypic effect on cell junction integrity.

EGFR signaling pathways are wired differently in normal 184A1L5 human mammary epithelial and MDA-MB-231 breast cancer cells

Because of differences in the downstream signaling patterns of its pathways, the role of the human epidermal growth factor family of receptors (HER) in promoting cell growth and survival is cell line and context dependent. Using two model cell lines, we have studied how the regulatory interaction network among the key proteins of HER signaling pathways may be rewired upon normal to cancerous transformation. We in particular investigated how the transcription factor STAT3 and several key kinases' involvement in cancer-related signaling processes differ between normal 184A1L5 human mammary epithelial (HME) and MDA-MB-231 breast cancer epithelial cells. Comparison of the responses in these cells showed that normal-to-cancerous cellular transformation causes a major re-wiring of the growth factor initiated signaling. In particular, we found that: i) regulatory interactions between Erk, p38, JNK and STAT3 are triangulated and tightly coupled in 184A1L5 HME cells, and ii) STAT3 is only weakly associated with the Erk-p38-JNK pathway in MDA-MB-231 cells. Utilizing the concept of pathway substitution, we predicted how the observed differences in the regulatory interactions may affect the proliferation/survival and motility responses of the 184A1L5 and MDA-MB-231 cells when exposed to various inhibitors. We then validated our predictions experimentally to complete the experiment-computation-experiment iteration loop. Validated differences in the regulatory interactions of the 184A1L5 and MDA-MB-231 cells indicated that instead of inhibiting STAT3, which has severe toxic side effects, simultaneous inhibition of JNK together with Erk or p38 could be a more effective strategy to impose cell death selectively to MDA-MB-231 cancer cells while considerably lowering the side effects to normal epithelial cells. Presented analysis establishes a framework with examples that would enable cell signaling researchers to identify the signaling network structures which can be used to predict the phenotypic responses in particular cell lines of interest.

Avoiding common pitfalls when clustering biological data

Clustering is an unsupervised learning method, which groups data points based on similarity, and is used to reveal the underlying structure of data. This computational approach is essential to understanding and visualizing the complex data that are acquired in high-throughput multidimensional biological experiments. Clustering enables researchers to make biological inferences for further experiments. Although a powerful technique, inappropriate application can lead biological researchers to waste resources and time in experimental follow-up. We review common pitfalls identified from the published molecular biology literature and present methods to avoid them. Commonly encountered pitfalls relate to the high-dimensional nature of biological data from high-throughput experiments, the failure to consider more than one clustering method for a given problem, and the difficulty in determining whether clustering has produced meaningful results. We present concrete examples of problems and solutions (clustering results) in the form of toy problems and real biological data for these issues. We also discuss ensemble clustering as an easy-to-implement method that enables the exploration of multiple clustering solutions and improves robustness of clustering solutions. Increased awareness of common clustering pitfalls will help researchers avoid overinterpreting or misinterpreting the results and missing valuable insights when clustering biological data.

Three-Dimensional Distribution of UBF and Nopp140 in Relationship to Ribosomal DNA Transcription During Mouse Preimplantation Development

The nucleolus is a dynamic nuclear compartment that is mostly involved in ribosome subunit biogenesis; however, it may also play a role in many other biological processes, such as stress response and the cell cycle. Mainly using electron microscopy, several studies have tried to decipher how active nucleoli are set up during early development in mice. In this study, we analyzed nucleologenesis during mouse early embryonic development using 3D-immunofluorescent detection of UBF and Nopp140, two proteins associated with different nucleolar compartments. UBF is a transcription factor that helps maintain the euchromatic state of ribosomal genes; Nopp140 is a phosphoprotein that has been implicated in pre-rRNA processing. First, using detailed image analyses and the in situ proximity ligation assay technique, we demonstrate that UBF and Nopp140 dynamic redistribution between the two-cell and blastocyst stages (time of implantation) is correlated with morphological and structural modifications that occur in embryonic nucleolar compartments. Our results also support the hypothesis that nucleoli develop at the periphery of nucleolar precursor bodies. Finally, we show that the RNA polymerase I inhibitor CX-5461: 1) disrupts transcriptional activity, 2) alters preimplantation development, and 3) leads to a complete reorganization of UBF and Nopp140 distribution. Altogether, our results underscore that highly dynamic changes are occurring in the nucleoli of embryos and confirm a close link between ribosomal gene transcription and nucleologenesis during the early stages of development.

SH2-PLA: a sensitive in-solution approach for quantification of modular domain binding by proximity ligation and real-time PCR

BACKGROUND

There is a great interest in studying phosphotyrosine dependent protein-protein interactions in tyrosine kinase pathways that play a critical role in many aspects of cellular function. We previously established SH2 profiling, a phosphoproteomic approach based on membrane binding assays that utilizes purified Src Homology 2 (SH2) domains as a molecular tool to profile the global tyrosine phosphorylation state of cells. However, in order to use this method to investigate SH2 binding sites on a specific target in cell lysate, additional procedures such as pull-down or immunoprecipitation which consume large amounts of sample are required.

RESULTS

We have developed PLA-SH2, an alternative in-solution modular domain binding assay that takes advantage of Proximity Ligation Assay and real-time PCR. The SH2-PLA assay utilizes oligonucleotide-conjugated anti-GST and anti-EGFR antibodies recognizing a GST-SH2 probe and cellular EGFR, respectively. If the GST-SH2 and EGFR are in close proximity as a result of SH2-phosphotyrosine interactions, the two oligonucleotides are brought within a suitable distance for ligation to occur, allowing for efficient complex amplification via real-time PCR. The assay detected signal across at least 3 orders of magnitude of lysate input with a linear range spanning 1-2 orders and a low femtomole limit of detection for EGFR phosphotyrosine. SH2 binding kinetics determined by PLA-SH2 showed good agreement with established far-Western analyses for A431 and Cos1 cells stimulated with EGF at various times and doses. Further, we showed that PLA-SH2 can survey lung cancer tissues using 1 μl lysate without requiring phospho-enrichment.

CONCLUSIONS

We showed for the first time that interactions between SH2 domain probes and EGFR in cell lysate can be determined in a microliter-scale assay using SH2-PLA. The obvious benefit of this method is that the low sample requirement allows detection of SH2 binding in samples which are difficult to analyze using traditional protein interaction assays. This feature along with short assay runtime makes this method a useful platform for the development of high throughput assays to determine modular domain-ligand interactions which could have wide-ranging applications in both basic and translational cancer research.

ProteomeScout: a repository and analysis resource for post-translational modifications and proteins

ProteomeScout (https://proteomescout.wustl.edu) is a resource for the study of proteins and their post-translational modifications (PTMs) consisting of a database of PTMs, a repository for experimental data, an analysis suite for PTM experiments, and a tool for visualizing the relationships between complex protein annotations. The PTM database is a compendium of public PTM data, coupled with user-uploaded experimental data. ProteomeScout provides analysis tools for experimental datasets, including summary views and subset selection, which can identify relationships within subsets of data by testing for statistically significant enrichment of protein annotations. Protein annotations are incorporated in the ProteomeScout database from external resources and include terms such as Gene Ontology annotations, domains, secondary structure and non-synonymous polymorphisms. These annotations are available in the database download, in the analysis tools and in the protein viewer. The protein viewer allows for the simultaneous visualization of annotations in an interactive web graphic, which can be exported in Scalable Vector Graphics (SVG) format. Finally, quantitative data measurements associated with public experiments are also easily viewable within protein records, allowing researchers to see how PTMs change across different contexts. ProteomeScout should prove useful for protein researchers and should benefit the proteomics community by providing a stable repository for PTM experiments.

Understanding and applying tyrosine biochemical diversity

This review highlights some of the recent advances made in our understanding of the diversity of tyrosine biochemistry and shows how this has inspired novel applications in numerous areas of molecular design and synthesis, including chemical biology and bioconjugation. The pathophysiological implications of tyrosine biochemistry will be presented from a molecular perspective and the opportunities for therapeutic intervention explored.

System level dynamics of post-translational modifications

Attempts to characterize cellular behaviors with static, univariate measurements cannot fully capture biological complexity and lead to an inadequate interpretation of cellular processes. Significant biological insight can be gleaned by considering the contribution of dynamic protein post-translational modifications (PTMs) utilizing systems-level quantitative analysis. High-resolution mass spectrometry coupled with computational modeling of dynamic signal-response relationships is a powerful tool to reveal PTM-mediated regulatory networks. Recent advances using this approach have defined network kinetics of growth factor signaling pathways, identified systems level responses to cytotoxic perturbations, elucidated kinase-substrate relationships, and unraveled the dynamics of PTM cross-talk. Innovations in multiplex measurement capacity, PTM annotation accuracy, and computational integration of datasets promise enhanced resolution of dynamic PTM networks and further insight into biological intricacies.