Browsing by Subject "Molecular biology"

Now showing 1 - 9 of 9

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
The BioPAX community standard for pathway data sharing
(Nature Publishing Group, 2010-09) Demir, Emek; Cary, M. P.; Paley, S.; Fukuda, K.; Lemer, C.; Vastrik, I.; Wu, G.; D'Eustachio, P.; Schaefer, C.; Luciano, J.; Schacherer, F.; Martinez-Flores, I.; Hu, Z.; Jimenez-Jacinto, V.; Joshi-Tope, G.; Kandasamy, K.; Lopez-Fuentes, A. C.; Mi, H.; Pichler, E.; Rodchenkov, I.; Splendiani, A.; Tkachev, S.; Zucker, J.; Gopinath, G.; Rajasimha, H.; Ramakrishnan, R.; Shah, I.; Syed, M.; Anwar, N.; Babur, Özgün; Blinov, M.; Brauner, E.; Corwin, D.; Donaldson, S.; Gibbons, F.; Goldberg, R.; Hornbeck, P.; Luna, A.; Murray-Rust, P.; Neumann, E.; Reubenacker, O.; Samwald, M.; Iersel, Martijn van; Wimalaratne, S.; Allen, K.; Braun, B.; Whirl-Carrillo, M.; Cheung, Kei-Hoi; Dahlquist, K.; Finney, A.; Gillespie, M.; Glass, E.; Gong, L.; Haw, R.; Honig, M.; Hubaut, O.; Kane, D.; Krupa, S.; Kutmon, M.; Leonard, J.; Marks, D.; Merberg, D.; Petri, V.; Pico, A.; Ravenscroft, D.; Ren, L.; Shah, N.; Sunshine, M.; Tang R.; Whaley, R.; Letovksy, S.; Buetow, K. H.; Rzhetsky, A.; Schachter, V.; Sobral, B. S.; Doğrusöz, Uğur; McWeeney, S.; Aladjem, M.; Birney, E.; Collado-Vides, J.; Goto, S.; Hucka, M.; Novère, Nicolas Le; Maltsev, N.; Pandey, A.; Thomas, P.; Wingender, E.; Karp, P. D.; Sander, C.; Bader, G. D.
Biological Pathway Exchange (BioPAX) is a standard language to represent biological pathways at the molecular and cellular level and to facilitate the exchange of pathway data. The rapid growth of the volume of pathway data has spurred the development of databases and computational tools to aid interpretation; however, use of these data is hampered by the current fragmentation of pathway information across many databases with incompatible formats. BioPAX, which was created through a community process, solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. Using BioPAX, millions of interactions, organized into thousands of pathways, from many organisms are available from a growing number of databases. This large amount of pathway data in a computable form will support visualization, analysis and biological discovery. © 2010 Nature America, Inc. All rights reserved.
Open Access
Cellular internalization of therapeutic oligonucleotides by peptide amphiphile nanofibers and nanospheres
(American Chemical Society, 2016-04) Mumcuoglu, D.; S. Ekiz, M.; Gunay, G.; Tekinay, T.; Tekinay, A. B.; Güler, Mustafa O.
Oligonucleotides are promising drug candidates due to the exceptionally high specificity they exhibit toward their target DNA and RNA sequences. However, their poor pharmacokinetic and pharmacodynamic properties, in conjunction with problems associated with their internalization by cells, necessitates their delivery through specialized carrier systems for efficient therapy. Here, we investigate the effects of carrier morphology on the cellular internalization mechanisms of oligonucleotides by using self-assembled fibrous or spherical peptide nanostructures. Size and geometry were both found to be important parameters for the oligonucleotide internalization process; direct penetration was determined to be the major mechanism for the internalization of nanosphere carriers, whereas nanofibers were internalized by clathrin- and dynamin-dependent endocytosis pathways. We further showed that glucose conjugation to carrier nanosystems improved cellular internalization in cancer cells due to the enhanced glucose metabolism associated with oncogenesis, and the internalization of the glucose-conjugated peptide/oligonucleotide complexes was found to be dependent on glucose transporters present on the surface of the cell membrane.
Open Access
Community-driven roadmap for integrated disease maps
(Oxford University Press, 2018) Ostaszewski, M.; Gebel, S.; Kuperstein, I.; Mazein, A.; Zinovyev, A.; Doğrusöz, Uğur; Hasenauer, J.; Fleming, R. M. T.; Novere, N. L.; Gawron, P.; Ligon, T.; Niarakis, A.; Nickerson, D.; Weindl, D.; Balling, R.; Barillot, E.; Auffray, C.; Schneider, R.
The Disease Maps Project builds on a network of scientific and clinical groups that exchange best practices, share information and develop systems biomedicine tools. The project aims for an integrated, highly curated and user-friendly platform for disease-related knowledge. The primary focus of disease maps is on interconnected signaling, metabolic and gene regulatory network pathways represented in standard formats. The involvement of domain experts ensures that the key disease hallmarks are covered and relevant, up-to-date knowledge is adequately represented. Expert-curated and computer readable, disease maps may serve as a compendium of knowledge, allow for data-supported hypothesis generation or serve as a scaffold for the generation of predictive mathematical models. This article summarizes the 2nd Disease Maps Community meeting, highlighting its important topics and outcomes. We outline milestones on the roadmap for the future development of disease maps, including creating and maintaining standardized disease maps; sharing parts of maps that encode common human disease mechanisms; providing technical solutions for complexity management of maps; and Web tools for in-depth exploration of such maps. A dedicated discussion was focused on mathematical modeling approaches, as one of the main goals of disease map development is the generation of mathematically interpretable representations to predict disease comorbidity or drug response and to suggest drug repositioning, altogether supporting clinical decisions.
Open Access
Deepside: predicting drug side effects with deep learning
(2019-09) Üner, Onur Can
Drug failures due to unforeseen adverse effects at clinical trials pose health risks for the participants and cause substantial financial losses. Side effect prediction algorithms, on the other hand, have the potential to guide the drug design process. LINCS L1000 dataset provides a vast resource of gene expression profiles across different cell lines that are induced with different dosages taken at different time points. The state-of-the-art approach in the literature relies on high-quality experiments in LINCS L1000 and discard a large portion of the recorded experiments. In this study, we investigate whether more information can be extracted from this remaining set of experiments with a deep learning-based approach. We experiment with 6 different deep learning architectures that use (i) gene expression data from the LINCS L1000 project, (ii) chemical structure fingerprints of drugs, (iii) SMILES string representation of drug structure, and (iv) the atomic structure of the drug molecules. The multilayer perceptron (MLP) based model which uses chemical structures and gene expression features achieve 88% micro- AUC and 79% macro-AUC, thus offering better performance in comparison to the state-of-the-art studies on side effect prediction. We observe that the chemical structure is more predictive than the gene expression profiles despite the fact that the features are extracted with different deep learning models. Finally, the convolutional neural network-based model that uses only SMILES strings of the drugs provides 82% macro-AUC, and 88%micro-AUC improvements, better performing than the models that use gene expression and chemical structure features simultaneously.
Open Access
Hybridization of fano and vibrational resonances in surface-enhanced infrared absorption spectroscopy of streptavidin monolayers on metamaterial substrates
(2014) Alici, K. B.
We present spectral hybridization of organic and inorganic resonant materials and related bio-sensing mechanism. We utilized a bound protein (streptavidin) and a Fano-resonant metasurface to illustrate the concept. The technique allows us to investigate the vibrational modes of the streptavidin and how they couple to the underlying metasurface. This optical, label-free, nonperturbative technique is supported by a coupled mode-theory analysis that provides information on the structure and orientation of bound proteins. We can also simultaneously monitor the binding of analytes to the surface through monitoring the shift of the metasurface resonance. All of this data opens up interesting opportunities for applications in biosensing, molecular electronics and proteomics. © 2014 IEEE.
Open Access
Subsequence-based feature map for protein function classification
(Elsevier, 2008) Sarac, O. S.; Gürsoy-Yüzügüllü, O.; Cetin Atalay, R.; Atalay, V.
Automated classification of proteins is indispensable for further in vivo investigation of excessive number of unknown sequences generated by large scale molecular biology techniques. This study describes a discriminative system based on feature space mapping, called subsequence profile map (SPMap) for functional classification of protein sequences. SPMap takes into account the information coming from the subsequences of a protein. A group of protein sequences that belong to the same level of classification is decomposed into fixed-length subsequences and they are clustered to obtain a representative feature space mapping. Mapping is defined as the distribution of the subsequences of a protein sequence over these clusters. The resulting feature space representation is used to train discriminative classifiers for functional families. The aim of this approach is to incorporate information coming from important subregions that are conserved over a family of proteins while avoiding the difficult task of explicit motif identification. The performance of the method was assessed through tests on various protein classification tasks. Our results showed that SPMap is capable of high accuracy classification in most of these tasks. Furthermore SPMap is fast and scalable enough to handle large datasets. © 2007 Elsevier Ltd. All rights reserved.
Open Access
The systems biology graphical notation
(Nature Publishing Group, 2009-08) Le Novère, N.; Hucka, M.; Mi, H.; Moodie, S.; Schreiber, F.; Sorokin, A.; Demir, Emek; Wegner, K.; Aladjem, M. I.; Wimalaratne, S. M.; Bergman, F. T.; Gauges, R.; Ghazal, P.; Kawaji, H.; Li, L.; Matsuoka, Y.; Villéger, A.; Boyd, S. E.; Calzone, L.; Courtot, M.; Doğrusöz, Uğur; Freeman, T. C.; Funahashi, A.; Ghosh, S.; Jouraku, A.; Kim, S.; Kolpakov, F.; Luna, A.; Sahle, S.; Schmidt, E.; Watterson, S.; Wu, G.; Goryanin, I.; Kell, D. B.; Sander, C.; Sauro, H.; Snoep, J. L.; Kohn, K.; Kitano, H.
Circuit diagrams and Unified Modeling Language diagrams are just two examples of standard visual languages that help accelerate work by promoting regularity, removing ambiguity and enabling software tool support for communication of complex information. Ironically, despite having one of the highest ratios of graphical to textual information, biology still lacks standard graphical notations. The recent deluge of biological knowledge makes addressing this deficit a pressing concern. Toward this goal, we present the Systems Biology Graphical Notation (SBGN), a visual language developed by a community of biochemists, modelers and computer scientists. SBGN consists of three complementary languages: process diagram, entity relationship diagram and activity flow diagram. Together they enable scientists to represent networks of biochemical interactions in a standard, unambiguous way. We believe that SBGN will foster efficient and accurate representation, visualization, storage, exchange and reuse of information on all kinds of biological knowledge, from gene regulation, to metabolism, to cellular signaling. © 2009 Nature America, Inc.
Open Access
Transmission Near-Field Scanning Optical Microscopy Investigation on Cellular Uptake Behavior of Iron Oxide Nanoparticles
(2012) Zhang, Y.; Kyle J.R.; Penchev, M.; Yazdanpanah V.; Yu J.; Li, Y.; Yang, M.; Budak G.; Özbay, Ekmel; Ozkan, M.; Ozkan, C.S.
Cellular uptake behavior of iron oxide nanoparticles is investigated using a transmission near-field scanning optical microscopy (NSOM) without the need of fluorescent labeling. By using the transmission NSOM system, we could simultaneously explore the near-field optical analysis of the cell interior and record the topographic information of the cell surface. The cell endocytosis of iron oxide nanoparticles by normal breast MCF10A cells is first studied by this transmission NSOM system, and this dual functional nanoscale-resolution microscopy shows the capability of mapping the spatial localization of nanoparticles in/outside cell surface without the need of fluorescence labeling. Nanoscale optical signature patterns for iron oxide nanoparticle-loaded vesicles inside the cells were observed and analyzed. © Springer Science+Business Media, LLC 2012.