Browsing by Subject "Proteomics"

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Open Access
3D-MSCs A151 ODN-loaded exosomes are immunomodulatory and reveal a proteomic cargo that sustains wound resolution
(Elsevier B.V., 2022-11) Camões, Sérgio P.; Bulut, Özlem; Yazar, Volkan; Gaspar, Maria M.; Simões, Sandra; Ferreira, Rita; Vitorino, Rui; Santos, Jorge M.; Gürsel, İhsan; Miranda, Joana P.
Introduction: Non-healing wounds remain a major burden due to the lack of effective treatments. Mesenchymal stem cell-derived exosomes (MSC-Exo) have emerged as therapeutic options given their pro-regenerative and immunomodulatory features. Still, little is known on the exact mechanisms mediated by MSC-Exo. Importantly, modulation of their efficacy through 3D-physiologic cultures together with loading strategies continues underexplored. Objectives: To uncover the MSC-Exo-mediated mechanism via proteomic analyses, and to use 3D-culture and loading technologies to expand MSC-Exo efficacy for cutaneous wound healing. Methods: MSC-Exo were produced in either 3D or 2D cultures (Exo3D/Exo2D) and loaded with an exogenous immunosuppressive oligodeoxynucleotide (A151 ODN). Both, loaded and naïve exosomes were characterised regarding size, morphology and the presence of specific protein markers; while IPA analyses enabled to correlate their protein content with the effects observed in vitro and in vivo. The Exo3D/Exo2D regenerative potential was evaluated in vitro by assessing keratinocyte and fibroblast mitogenicity, motogenicity, and cytokine secretion as well as using an in vivo wound splinting model. Accordingly, the modulation of inflammatory and immune responses by A151-loaded Exo3D/Exo2D was also assessed. Results: Exo3D stimulated mitogenically and motogenically keratinocytes and fibroblasts in vitro, with upregulation of IL-1α and VEGF-α or increased secretion of TGF-β, TNF-α and IL-10. In vivo, Exo3D reduced the granulation tissue area and promoted complete re-epithelization of the wound. These observations were sustained by the proteomic profiling of the Exo3D cargo that identified wound healing-related proteins, such as TGF-β, ITGA1-3/5, IL-6, CDC151, S100A10 and Wnt5α. Moreover, when loaded with A151 ODN, Exo3D differentially mediated wound healing-related trophic factors reducing the systemic levels of IL-6 and TNF-α at the late stage of wound healing in vivo. Conclusion: Our results support the potential of A151-loaded Exo3D for the treatment of chronic wounds by promoting skin regeneration, while modulating the systemic levels of the pro-inflammatory cytokines. © 2022
Open Access
Analyzing causal relationships in proteomic profiles using CausalPath
(Cell Press, 2021-12-17) Luna, A.; Siper, M. C.; Korkut, A.; Durupinar, F.; Aslan, J. E.; Sander, C.; Demir, E.; Babur, O.; Doğrusöz, Uğur
CausalPath (causalpath.org) evaluates proteomic measurements against prior knowledge of biological pathways and infers causality between changes in measured features, such as global protein and phospho-protein levels. It uses pathway resources to determine potential causality between observable omic features, which are called prior relations. The subset of the prior relations that are supported by the proteomic profiles are reported and evaluated for statistical significance. The end result is a network model of signaling that explains the patterns observed in the experimental dataset.
Open Access
Biological properties of extracellular vesicles and their physiological functions
(Taylor & Francis, 2015) Yáñez-Mó, M.; Siljander, P. R. M.; Andreu, Z.; Zavec, A. B.; Borràs, F. E.; Buzas, E. I.; Buzas, K.; Casal, E.; Cappello, F.; Carvalho, J.; Colás, E.; Cordeiro-Da, S. A.; Fais, S.; Falcon-Perez, J. M.; Ghobrial, I. M.; Giebel, B.; Gimona, M.; Graner, M.; Gursel, I.; Gursel, M.; Heegaard, N. H. H.; Hendrix, A.; Kierulf, P.; Kokubun, K.; Kosanovic, M.; Kralj-Iglic, V.; Krämer-Albers, E. M.; Laitinen, S.; Lässer, C.; Lener, T.; Ligeti, E.; Line, A.; Lipps, G.; Llorente, A.; Lötvall, J.; Manček-Keber, M.; Marcilla, A.; Mittelbrunn, M.; Nazarenko, I.; Nolte-'t Hoen, E. N. M.; Nyman, T. A.; O'Driscoll, L.; Olivan, M.; Oliveira, C.; Pállinger, E.; Del Portillo, H. A.; Reventós, J.; Rigau, M.; Rohde, E.; Sammar, M.; Sánchez-Madrid, F.; Santarém, N.; Schallmoser, K.; Ostenfeld, M. S.; Stoorvogel, W.; Stukelj, R.; Grein V. D. S.G.; Helena,ü V. M.; Wauben, M. H. M.; De Wever, O.
In the past decade, extracellular vesicles (EVs) have been recognized as potent vehicles of intercellular communication, both in prokaryotes and eukaryotes. This is due to their capacity to transfer proteins, lipids and nucleic acids, thereby influencing various physiological and pathological functions of both recipient and parent cells.While intensive investigation has targeted the role of EVs in different pathological processes, for example, in cancer and autoimmune diseases, the EV-mediated maintenance of homeostasis and the regulation of physiological functions have remained less explored. Here, we provide a comprehensive overview of the current understanding of the physiological roles of EVs, which has been written by crowd-sourcing, drawing on the unique EV expertise of academia-based scientists, clinicians and industry based in 27 European countries, the United States and Australia. This review is intended to be of relevance to both researchers already working on EV biology and to newcomers who will encounter this universal cell biological system. Therefore, here we address the molecular contents and functions of EVs in various tissues and body fluids from cell systems to organs. We also review the physiological mechanisms of EVs in bacteria, lower eukaryotes and plants to highlight the functional uniformity of this emerging communication system.
Open Access
Causal interactions from proteomic profiles: Molecular data meet pathway knowledge
(Cell Press, 2021-06) Babur, Ö.; Luna, A.; Korkut, A.; Durupınar, F.; Siper, M. C.; Doğrusöz, Uğur; Jacome, A. S. V.; Peckner, R.; Christiansen, K. E.; Jaffe, J.D; Spellman, P.T.; Aslan, J. E.; Sander, C.; Demir, E.
We present a computational method to infer causal mechanisms in cell biology by analyzing changes in high-throughput proteomic profiles on the background of prior knowledge captured in biochemical reaction knowledge bases. The method mimics a biologist's traditional approach of explaining changes in data using prior knowledge but does this at the scale of hundreds of thousands of reactions. This is a specific example of how to automate scientific reasoning processes and illustrates the power of mapping from experimental data to prior knowledge via logic programming. The identified mechanisms can explain how experimental and physiological perturbations, propagating in a network of reactions, affect cellular responses and their phenotypic consequences. Causal pathway analysis is a powerful and flexible discovery tool for a wide range of cellular profiling data types and biological questions. The automated causation inference tool, as well as the source code, are freely available at http://causalpath.org.
Open Access
Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal
(American Association for the Advancement of Science (A A A S), 2013) Gao J.; Aksoy, B. A.; Dogrusoz, U.; Dresdner, G.; Gross, B.; Sumer, S. O.; Sun, Y.; Jacobsen, A.; Sinha, R.; Larsson, E.; Cerami, E.; Sander, C.; Schultz, N.
The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics. © 2013 American Association for the Advancement of Science.
Open Access
PATIKA: an integrated visual environment for collaborative construction and analysis of cellular pathways
(Oxford University Press, 2002-06) Demir, Emek; Babur, Özgün; Doğrusöz, Uğur; Gürsoy, Atilla; Nişancı, Gürkan; Çetin Atalay, Rengül; Öztürk, Mehmet
Motivation: Availability of the sequences of entire genomes shifts the scientific curiosity towards the identification of function of the genomes in large scale as in genome studies. In the near future, data produced about cellular processes at molecular level will accumulate with an accelerating rate as a result of proteomics studies. In this regard, it is essential to develop tools for storing, integrating, accessing, and analyzing this data effectively. Results: We define an ontology for a comprehensive representation of cellular events. The ontology presented here enables integration of fragmented or incomplete pathway information and supports manipulation and incorporation of the stored data, as well as multiple levels of abstraction. Based on this ontology, we present the architecture of an integrated environment named PATIKA (Pathway Analysis Tool for Integration and Knowledge Acquisition). PATIKA is composed of a server-side, scalable, object-oriented database and client-side editors to provide an integrated, multi-user environment for visualizing and manipulating network of cellular events. This tool features automated pathway layout, functional computation support, advanced querying and a user-friendly graphical interface. We expect that PATIKA will be a valuable tool for rapid knowledge acquisition, microarray generated large-scale data interpretation, disease gene identification, and drug development.
Open Access
PATIKA: an integrated visual environment for collaborative construction and analysis of cellular pathways
(American Society for Biochemistry and Molecular Biology(ASBMB), 2002-09) Demir, Emek; Babur, Özgün; Doğrusöz, Uğur; Gürsoy, Atilla; Nişancı, Gürkan; Çetin Atalay, Rengül; Öztürk, Mehmet
Open Access
PATIKAmad: putting microarray data into pathway context
(Wiley - V C H Verlag GmbH & Co. KGaA, 2008-06) Babur, Özgün; Colak, Recep; Demir, Emek; Doğrusöz, Uğur
High-throughput experiments, most significantly DNA microarrays, provide us with system-scale profiles. Connecting these data with existing biological networks poses a formidable challenge to uncover facts about a cell's proteome. Studies and tools with this purpose are limited to networks with simple structure, such as protein-protein interaction graphs, or do not go much beyond than simply displaying values on the network. We have built a microarray data analysis tool, named PATIKAmad, which can be used to associate microarray data with the pathway models in mechanistic detail, and provides facilities for visualization, clustering, querying, and navigation of biological graphs related with loaded microarray experiments. PATIKAmad is freely available to noncommercial users as a new module of PATIKAweb at http://web.patika.org. © 2008 Wiley-VCH Verlag GmbH & Co. KGaA.
Open Access
PATIKAweb: a Web interface for analyzing biological pathways through advanced querying and visualization
(Oxford University Press, 2006-02-01) Doğrusöz, Uğur; Erson, E. Zeynep; Giral, Erhan; Demir, Emek; Babur, Özgün; Çetintaş, Ahmet; Çolak, Recep
Summary: PATIKAweb provides a Web interface for retrieving and analyzing biological pathways in the PATIKA database, which contains data integrated from various prominent public pathway databases. It features a user-friendly interface, dynamic visualization and automated layout, advanced graph-theoretic queries for extracting biologically important phenomena, local persistence capability and exporting facilities to various pathway exchange formats. © The Author 2005. Published by Oxford University Press. All rights reserved.
Open Access
Profiling the interactome of STK10 by using proximity-based biotinylation
(2023-05) Carus, Yağmur Öykü
Breast cancer accounts for a quarter of all newly diagnosed cancer cases globally in women. It is also the primary cause of death in female cancer patients. In 2020, it was responsible for 15% of all cancer-related deaths in women. The PI3K pathway is the most commonly deregulated pathway in breast cancer. As a result, numerous inhibitors for druggable targets within the pathway have been developed. Unfortunately, drug resistance is frequently observed after treatment with these inhibitors. The mechanisms behind this resistance are widely studied. AKT has been known to be the kinase responsible for transmitting the signal to downstream targets. However, new studies suggested there can be AKT-independent kinases relaying the signal to downstream targets causing PI3K inhibitor drug resistance. Previously, our group hypothesized that they could find an AKT-independent protein that confers resistance to PI3K inhibition. Their bioinformatical analyses identified STK10 (Serine-Threonine Kinase 10) as a possible druggable target for PI3K pathway inhibitor resistance in an AKT-independent manner. They performed wet lab experiments to show STK10’s impact on PI3K inhibitor resistance in breast cancer. They showed STK10 knock-down sensitizing resistant breast cancer cells to PI3K inhibitor. Although their experiments supported the hypothesis of STK10 affecting the PI3K inhibitor resistance of breast cancer cells, they could not identify the molecular mechanisms behind this interaction. In this study, by using APEX2 proximity-based biotinylation followed by mass spectrometry, we profiled STK10’s interactome. We aimed to understand how STK10 contributes to the progression of breast cancer and the development of resistance to treatment. Our bioinformatics analyses indicated possible interaction between STK10 and the candidate proteins we obtained from our mass spectrometry analysis. Immunofluorescence and Co-IP experiments supported some of the putative interactions we discovered. The proteins discovered near STK10 were primarily linked to the reorganization of the cytoskeleton, which is encouraging since STK10 is recognized for its involvement in cell migration through the phosphorylation of ERM proteins. Based on our observations, it is possible to hypothesize that STK10 is influencing the cytoskeletal reorganization in breast cancer cells. However, further experiments are needed to be done to understand the molecular mechanisms behind STK10’s possible functions in breast cancer. These experiments could lead to uncovering the role of STK10 in PI3K inhibitor resistance and help us to identify new therapeutic options to battle breast cancer.