Proteomics Methods for Probing Molecular Mechanisms in Signal Transduction

Sheffield, Lewis G.; Gavinski, Jennifer J.

doi:10.3168/jds.s0022-0302(03)74044-2

Cited by 3 publications

(3 citation statements)

References 88 publications

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“…The use of IP allows endogenous proteins to be isolated without the need for cDNAs encoding the protein of interest or the need to express the fusion construct; however, for HT applications this would require a specific ASR for every protein of interest, whereas tag‐based affinity purifications using a single isolation chemistry can be applied to all proteins. To identify the binding partners, the proteins that associate with the index protein are often separated by gel electrophoresis and can be probed either with specific reagents on western blots (if their identities are suspected and the corresponding reagents are available), or they can be digested before or after separation by specific proteases followed by analysis on a mass spectrometer [13,14]. This approach has the potential to capture natural protein complexes and does not require that the interacting proteins are known in advance or that their genes are even cloned.…”

Section: Common Methods For Studying Protein Interactionsmentioning

confidence: 99%

Emerging tools for real‐time label‐free detection of interactions on functional protein microarrays

et al. 2005

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The wide variety of protein interactions in a cell comprises a biochemical wiring network that controls everything from growth and division to the cell's response to its environment. These interactions include metabolites, lipids, nucleic acids, carbohydrates, proteins (both self and other proteins) and drugs [1][2][3][4][5][6][7]. Understanding the dynamic nature of these interactions will reveal the functional responsibilities of proteins and the circuits in which they operate [8]. The complex milieu of the living cell has slowed many attempts at assaying for protein function in vivo. The broad dynamic range of protein abundance in biological samples [9,10], and the ability of proteins to undergo post-translational modifications (PTMs), such as phosphorylation, glycosylation and myristoylation, further encumber the ability to build sensitive and accurate assays for studying protein function. This is a result of the dependence of many protein interactions The availability of extensive genomic information and content has spawned an era of high-throughput screening that is generating large sets of functional genomic data. In particular, the need to understand the biochemical wiring within a cell has introduced novel approaches to map the intricate networks of biological interactions arising from the interactions of proteins. The current technologies for assaying protein interactions -yeast twohybrid and immunoprecipitation with mass spectrometric detection -have met with considerable success. However, the parallel use of these approaches has identified only a small fraction of physiologically relevant interactions among proteins, neglecting all nonprotein interactions, such as with metabolites, lipids, DNA and small molecules. This highlights the need for further development of proteome scale technologies that enable the study of protein function. Here we discuss recent advances in high-throughput technologies for displaying proteins on functional protein microarrays and the real-time label-free detection of interactions using probes of the local index of refraction, carbon nanotubes and nanowires, or microelectromechanical systems cantilevers. The combination of these technologies will facilitate the large-scale study of protein interactions with proteins as well as with other biomolecules.

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Section: Common Methods For Studying Protein Interactionsmentioning

confidence: 99%

Emerging tools for real‐time label‐free detection of interactions on functional protein microarrays

et al. 2005

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“…In‐depth investigation of modulations in signal transduction pathways, and proteins responsible for causing such alterations can play a crucial role in revealing the molecular alterations associated with cancers, studying their pathogenesis, and identification of novel therapeutic targets . In the field of cancer research, proteomics has been widely implemented for mapping cancer‐related signaling pathways and networks , since proteome‐level studies can help in deciphering the mechanism of the disease pathobiology and the alterations in biological systems under various diseased conditions . The differential tissue proteome expression profile enables a deeper understanding of mechanism of the tumerigenesis and can help in identification of several potential biomarkers that can discriminate between different grades of brain tumors .…”

Section: Introductionmentioning

confidence: 99%

Multipronged quantitative proteomic analyses indicate modulation of various signal transduction pathways in human meningiomas

Sharma

Mukherjee

et al. 2015

Proteomics

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Meningiomas (MGs) are frequent tumors of the CNS originating from the meningeal layers of the spinal cord and the brain. In this study, comparative tissue proteomic analysis of low and high grades of MGs was performed by using iTRAQ-based quantitative proteomics in combination with ESI-quadrupole-TOF and Q-Exactive MS, and results were validated by employing ELISA. Combining the results obtained from two MS platforms, we were able to identify overall 4308 proteins (1% false discover rate), among which 2367 exhibited differential expression (more than and equal to 2 peptide and ≥ 1.5-fold in at least one grade) in MGs. Several differentially expressed proteins were found to be associated with diverse signaling pathways, including integrin, Wnt, Ras, epidermal growth factor receptor, and FGR signaling. Proteins, such as vinculin or histones, which act as the signaling activators to initiate multiple signaling pathways, were found to be upregulated in MGs. Quite a few candidates, such as protein S-100A6, aldehyde dehydrogenase mitochondrial, AHNAK, cytoskeleton-associated protein 4, and caveolin, showed sequential increase in low- and high-grade MGs, whereas differential expressions of collagen alpha-1 (VI), protein S100-A9, 14 kDa phosphohistidine phosphatase, or transgelin-2 were found to be grade specific. Our findings provide new insights regarding the association of various signal transduction pathways in MG pathogenesis and may introduce new opportunities for the early detection and prognosis of MGs.

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“…These interactions form the basis of several sophisticated molecular machinery mandatory for various cellular processes . External stimulus initiates several dynamic interactions amongst the biomolecules, which are usually transient, resulting in activation of diverse signalling cascades and even crosstalking between the pathways, eventually ending with the changes at transcription and translation levels . Mapping and clustering of these static signalling events forms the basis of dynamic protein interaction networks.…”

Section: Introductionmentioning

confidence: 99%

Array‐based proteomic approaches to study signal transduction pathways: Prospects, merits and challenges

Gahoi

Srivastava

2014

Proteomics

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Very often dysfunctional aspects of various signalling networks are found to be associated with human diseases and disorders. The major characteristics of signal transduction pathways are specificity, amplification of the signal, desensitisation and integration, which is accomplished not solely, but majorly by proteins. Array-based profiling of protein-protein and other biomolecular interactions is a versatile approach, which holds immense potential for multiplex interactome mapping and provides an inclusive representation of the signal transduction pathways and networks. Protein microarrays such as analytical protein microarrays (antigen-antibody interactions, autoantibody screening), RP microarrays (interaction of a particular ligand with all the possible targets in cell), functional protein microarrays (protein-protein or protein-ligand interactions) are implemented for various applications, including analysis of protein interactions and their significance in signalling cascades. Additionally, successful amalgamation of the array-based approaches with different label-free detection techniques allows real-time analysis of interaction kinetics of multiple interaction events simultaneously. This review discusses the prospects, merits and limitations of different variants of array-based techniques and their promising applications for studying the modifications and interactions of biomolecules, and highlights the studies associated with signal transduction pathways and their impact on disease pathobiology.

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Proteomics Methods for Probing Molecular Mechanisms in Signal Transduction

Cited by 3 publications

References 88 publications

Emerging tools for real‐time label‐free detection of interactions on functional protein microarrays

Emerging tools for real‐time label‐free detection of interactions on functional protein microarrays

Multipronged quantitative proteomic analyses indicate modulation of various signal transduction pathways in human meningiomas

Array‐based proteomic approaches to study signal transduction pathways: Prospects, merits and challenges

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