9,752 research outputs found

    Prototype Foamy Virus Capsid – Nucleic Acid Interactions: Mechanistic Insights & Application for Efficient RNA Transfer

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    Foamy viruses (FV) represent a distinct genus in the retrovirus family and separate themselves from the large group of orthoretroviruses by various distinct features in their replication cycle (reviewed in Lindemann & Rethwilm, 2011). In gene therapy retroviruses are commonly used as vectors to deliver genetic information into target cells and also FV has been successfully used for example in a canine genetic disease model (Trobridge et al., 2009). Here we investigated the interactions between the FV capsid-forming protein ‘Gag’ and nucleic acids. We found that prototype FV (PFV) Gag binds various cellular mRNAs, incorporates them into the nascent particle and thereby enables their transfer into the cytosol of target cells. There these mRNAs can serve as template for protein translation. This feature seems uniquely efficient for PFV and we developed it further into a “RNA transfer vector system” allowing efficient transgene mRNA transfer into target cells, as showed in proof-of-principle experiments in vitro and in vivo (Hamann et al., 2014a). In parallel we started investigating the specificity in viral RNA genome packaging (Hamann et al., 2014b). To date little is known how PFV selects its RNA genome over the vast excess of cellular RNAs present in the cytosol. Elevated fundamental knowledge of this mechanism could help to make the “RNA transfer vector system” even more efficient since it would allow enrichment of certain specific “designer-RNAs” in virus particles

    HuCoPIA: An Atlas of Human vs. SARS-CoV-2 Interactome and the Comparative Analysis with Other Coronaviridae Family Viruses

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    SARS-CoV-2, a novel betacoronavirus strain, has caused a pandemic that has claimed the lives of nearly 6.7M people worldwide. Vaccines and medicines are being developed around the world to reduce the disease spread, fatality rates, and control the new variants. Understanding the protein-protein interaction mechanism of SARS-CoV-2 in humans, and their comparison with the previous SARS-CoV and MERS strains, is crucial for these efforts. These interactions might be used to assess vaccination effectiveness, diagnose exposure, and produce effective biotherapeutics. Here, we present the HuCoPIA database, which contains approximately 100,000 protein-protein interactions between humans and three strains (SARS-CoV-2, SARS-CoV, and MERS) of betacoronavirus. The interactions in the database are divided into common interactions between all three strains and those unique to each strain. It also contains relevant functional annotation information of human proteins. The HuCoPIA database contains SARS-CoV-2 (41,173), SARS-CoV (31,997), and MERS (26,862) interactions, with functional annotation of human proteins like subcellular localization, tissue-expression, KEGG pathways, and Gene ontology information. We believe HuCoPIA will serve as an invaluable resource to diverse experimental biologists, and will help to advance the research in better understanding the mechanism of betacoronaviruses

    Computing Interpretable Representations of Cell Morphodynamics

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    Shape changes (morphodynamics) are one of the principal ways cells interact with their environments and perform key intrinsic behaviours like division. These dynamics arise from a myriad of complex signalling pathways that often organise with emergent simplicity to carry out critical functions including predation, collaboration and migration. A powerful method for analysis can therefore be to quantify this emergent structure, bypassing the low-level complexity. Enormous image datasets are now available to mine. However, it can be difficult to uncover interpretable representations of the global organisation of these heterogeneous dynamic processes. Here, such representations were developed for interpreting morphodynamics in two key areas: mode of action (MoA) comparison for drug discovery (developed using the economically devastating Asian soybean rust crop pathogen) and 3D migration of immune system T cells through extracellular matrices (ECMs). For MoA comparison, population development over a 2D space of shapes (morphospace) was described using two models with condition-dependent parameters: a top-down model of diffusive development over Waddington-type landscapes, and a bottom-up model of tip growth. A variety of landscapes were discovered, describing phenotype transitions during growth, and possible perturbations in the tip growth machinery that cause this variation were identified. For interpreting T cell migration, a new 3D shape descriptor that incorporates key polarisation information was developed, revealing low-dimensionality of shape, and the distinct morphodynamics of run-and-stop modes that emerge at minute timescales were mapped. Periodically oscillating morphodynamics that include retrograde deformation flows were found to underlie active translocation (run mode). Overall, it was found that highly interpretable representations could be uncovered while still leveraging the enormous discovery power of deep learning algorithms. The results show that whole-cell morphodynamics can be a convenient and powerful place to search for structure, with potentially life-saving applications in medicine and biocide discovery as well as immunotherapeutics.Open Acces

    Integrated computational analysis reveals HOX genes cluster as oncogenic drivers in head and neck squamous cell carcinoma

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    Alterations in homeobox (HOX) gene expression are involved in the progression of several cancer types including head and neck squamous cell carcinoma (HNSCC). However, regulation of the entire HOX cluster in the pathophysiology of HNSCC is still elusive. By using different comprehensive databases, we have identified the significance of differentially expressed HOX genes (DEHGs) in stage stratification and HPV status in the cancer genome atlas (TCGA)-HNSCC datasets. The genetic and epigenetic alterations, druggable genes, their associated functional pathways and their possible association with cancer hallmarks were identified. We have performed extensive analysis to identify the target genes of DEHGs driving HNSCC. The differentially expressed HOX cluster-embedded microRNAs (DEHMs) in HNSCC and their association with HOX-target genes were evaluated to construct a regulatory network of the HOX cluster in HNSCC. Our analysis identified sixteen DEHGs in HNSCC and determined their importance in stage stratification and HPV infection. We found a total of 55 HNSCC driver genes that were identified as targets of DEHGs. The involvement of DEHGs and their targets in cancer-associated signaling mechanisms have confirmed their role in pathophysiology. Further, we found that their oncogenic nature could be targeted by using the novel and approved anti-neoplastic drugs in HNSCC. Construction of the regulatory network depicted the interaction between DEHGs, DEHMs and their targets genes in HNSCC. Hence, aberrantly expressed HOX cluster genes function in a coordinated manner to drive HNSCC. It could provide a broad perspective to carry out the experimental investigation, to understand the underlying oncogenic mechanism and allow the discovery of new clinical biomarkers for HNSCC

    Special Topics in Information Technology

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    This open access book presents thirteen outstanding doctoral dissertations in Information Technology from the Department of Electronics, Information and Bioengineering, Politecnico di Milano, Italy. Information Technology has always been highly interdisciplinary, as many aspects have to be considered in IT systems. The doctoral studies program in IT at Politecnico di Milano emphasizes this interdisciplinary nature, which is becoming more and more important in recent technological advances, in collaborative projects, and in the education of young researchers. Accordingly, the focus of advanced research is on pursuing a rigorous approach to specific research topics starting from a broad background in various areas of Information Technology, especially Computer Science and Engineering, Electronics, Systems and Control, and Telecommunications. Each year, more than 50 PhDs graduate from the program. This book gathers the outcomes of the thirteen best theses defended in 2020-21 and selected for the IT PhD Award. Each of the authors provides a chapter summarizing his/her findings, including an introduction, description of methods, main achievements and future work on the topic. Hence, the book provides a cutting-edge overview of the latest research trends in Information Technology at Politecnico di Milano, presented in an easy-to-read format that will also appeal to non-specialists

    Differential Models, Numerical Simulations and Applications

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    This Special Issue includes 12 high-quality articles containing original research findings in the fields of differential and integro-differential models, numerical methods and efficient algorithms for parameter estimation in inverse problems, with applications to biology, biomedicine, land degradation, traffic flows problems, and manufacturing systems

    Recent Advances in Single-Particle Tracking: Experiment and Analysis

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    This Special Issue of Entropy, titled “Recent Advances in Single-Particle Tracking: Experiment and Analysis”, contains a collection of 13 papers concerning different aspects of single-particle tracking, a popular experimental technique that has deeply penetrated molecular biology and statistical and chemical physics. Presenting original research, yet written in an accessible style, this collection will be useful for both newcomers to the field and more experienced researchers looking for some reference. Several papers are written by authorities in the field, and the topics cover aspects of experimental setups, analytical methods of tracking data analysis, a machine learning approach to data and, finally, some more general issues related to diffusion

    Structure, Activity, and Function of Protein Methyltransferases

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    This collection of review articles describes the structure, function and mechanism of individual protein methyltransferase enzymes including protein lysine methyltransferases, protein arginine methyltransferases, and also the less abundant protein histidine methyltransferases and protein N-terminal end methyltransferases. The topics covered in the individual reviews include structural aspects (domain architecture, homologs and paralogs, and structure), biochemical properties (mechanism, sequence specificity, product specificity, regulation, and histone and non-histone substrates), cellular features (subcellular localization, expression patterns, cellular roles and function, biological effects of substrate protein methylation, connection to cell signaling pathways, and connection to chromatin regulation) and their role in diseases. This review book is a useful resource for scientists working on protein methylation and protein methyltransferases and those interested in joining this emerging research field

    Experimental models of focal neuroinflammation - Efficacy assessment of pharmaceuticals of multiple sclerosis using PET imaging

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    Neuroinflammation (NI) is a key player in neurodegenerative diseases, such as multiple sclerosis (MS). Magnetic resonance imaging is the gold standard imaging method for diagnosis of MS, however, better diagnostic tools are needed for the follow-up of disease progression, earlier diagnosis, and assessment of patients’ response to therapy. Positron emission tomography (PET) is a sensitive and selective functional imaging method for investigating mechanisms of diseases at a molecular level. NI can be visualised in PET by targeting the 18 kDa translocator protein (TSPO), which is upregulated during NI on the mitochondria of glial cells. This study aimed to evaluate the properties of [18F]GE-180, a 2nd generation TSPO PET radiotracer, in a unilateral model of acute NI and evaluate the efficacy of immunomodulatory drugs, anti-VLA-4 and dimethyl fumarate (DMF), in two different focal rat models of experimental autoimmune encephalomyelitis (EAE), the fDTH-EAE and fMOG-EAE models. The applied methods were in vivo PET imaging, digital autoradiography, and immunohistochemical (IHC) staining. Study I indicated improved binding potential of [18F]GE-180 over the 1st generation tracer [11C]PK11195 and showed that the unilateral model of acute NI is suitable for the evaluation of novel PET tracers of NI. Study II indicated that anti- VLA-4 had no short-term treatment effects in the fDHT-EAE-rat model. However, discontinuation of the treatment caused a rebound that could be detected with [18F]GE-180. Study III showed, that short-term, but not long-term, DMF treatment decreases uptake of [18F]GE-180 in the fDTH-EAE rat model, and no rebound effect was detected after halting the treatment for 10 weeks. Nevertheless, the efficacy of DMF was detected using IHC for CD4+ and CD8+ cells. No DMF treatment effect was observed in the fMOG-EAE model. In conclusion, focal animal models of NI are applicable for evaluating novel PET tracers. Furthermore, efficacy assessment of immunomodulatory drugs can be evaluated using TSPO PET when the tracer is binding to the same biomarker that the drug is affectingPesäkkeisen aivotulehduksen kokeelliset mallit – multippeliskleroosin lääkkeiden vaikuttavuuden arviointi käyttäen PETkuvantamista Keskushermoston tulehdus on tila, joka ilmenee useissa hermorappeumasairauksissa, kuten pesäkekovettumataudissa (MS-tauti). MS-taudin kuvantamisdiagnostiikan ensisijainen menetelmä on magneettikuvaus, mutta uusia diagnostisia menetelmiä tarvitaan taudin mahdollisimman varhaiseksi toteamiseksi, etenemisen seuraamiseksi, ja uusien lääkehoitojen tehon arvioimiseksi. Positroniemissiotomografia (PET) on kajoamaton kuvantamismenetelmä, jonka avulla on mahdollista seurata aivojen tulehdusreaktiota hyödyntämällä tulehduksen aikana yliilmentyvään translokaatioproteiiniin (TSPO) sitoutuvia PET-merkkiaineita. Tämän tutkimuksen tavoitteena oli verrata TSPO-molekyyliin sitoutuvan toisen sukupolven PET-merkkiaineen ([18F]GE-180) sekä jo käytössä olevan merkkiaineen ([11C]PK11195) ominaisuuksia akuutin tulehduksen rottamallissa. Lisäksi tavoitteena oli arvioida immuunivastetta muokkaavien lääkkeiden, anti-VLA-4:n ja dimetyylifumaraatin, tehokkuutta lyhyt- ja pitkäaikaishoidossa fDTH-EAE- ja fMOG-EAE-malleissa, joissa rotille aiheutetaan pesäkkeinen autoimmuunienkefalomyeliitti. Tulehdusreaktiossa tapahtuvia muutoksia seurattiin hyödyntäen in vivo [18F]GE-180-PET-kuvantamista, autoradiografiaa, sekä kudosvärjäyksiä. Ensimmäisessä osatyössä [18F]GE-180-merkkiaineen havaittiin soveltuvan [11C]PK11195-merkkiainetta paremmin aivotulehduksen kuvantamiseen eläinmalleissa: aivojen tulehdusalue oli merkittävästi suurempi ja merkkiaineen sitoutumiskyky ja spesifisyys parempi. Toisessa osatyössä anti-VLA-4-lääkehoidon vaikutusta ei ollut mahdollista seurata [18F]GE-180-PET-kuvantamisella fDTHEAE-mallin kroonisen tulehduksen vaiheessa. Hoidon lopettamisen jälkeen ilmenevä voimakas tulehduksen uudelleenaktivoituminen oli kuitenkin mahdollista havaita PET-kuvauksella. Kolmannessa osatyössä dimetyylifumaraatin havaittiin hillitsevän tulehdusta fDTH-EAE-mallissa lyhytaikaishoidossa yhden viikon hoidon jälkeen, mutta ei enää myöhemmissä aikapisteissä, eikä fMOG-EAE-mallissa. Tämä väitöskirjatutkimus osoitti, että pesäkkeisen tulehduksen rottamalleja voidaan hyödyntää uusien tulehdusta kuvantavien PET-merkkiaineiden, sekä immuunivastetta muokkaavien lääkkeiden tehokkuuden arvioinnissa
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