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1. Additional file 1 of Neutralising reactivity against SARS-CoV-2 Delta and Omicron variants by vaccination and infection history

Author

Lavezzo, Enrico, Pacenti, Monia, Manuto, Laura, Boldrin, Caterina, Cattai, Margherita, Grazioli, Marco, Bianca, Federico, Sartori, Margherita, Caldart, Federico, Castelli, Gioele, Nicoletti, Michele, Nieddu, Eleonora, Salvadoretti, Elisa, Labella, Beatrice, Fava, Ludovico, Vanuzzo, Maria Cristina, Lisi, Vittoria, Antonello, Maria, Grimaldi, Carmela Ileana, Zulian, Chiara, Del Vecchio, Claudia, Plebani, Mario, Padoan, Andrea, Cirillo, Daniela Maria, Brazzale, Alessandra R., Tonon, Giovanni, Toppo, Stefano, Dorigatti, Ilaria, and Crisanti, Andrea

Abstract

Additional file 1: Figure S1. Anti-N antibody titres and dynamics in vaccinated and unvaccinated subjects; Figure S2. Anti-N antibody titres of vaccinated and unvaccinated individuals previously exposed to SARS-CoV-2 infection differ according to age; Figure S3. Correlation among DiaSorin S1/S2, DiaSorin trimeric tests and neutralisation assay; Figure S4. Features of the cohorts analysed in this study. Table S1. Concordance between S1/S2 and trimericS DiaSorin assays.

Published
2022
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3. The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

Author

Zhou, Naihui, Jiang, Yuxiang, Bergquist, Timothy R, Lee, Alexandra J, Kacsoh, Balint Z, Crocker, Alex W, Lewis, Kimberley A, Georghiou, George, Nguyen, Huy N, Hamid, Md Nafiz, Davis, Larry, Dogan, Tunca, Atalay, Volkan, Rifaioglu, Ahmet S, Dalkıran, Alperen, Cetin Atalay, Rengul, Zhang, Chengxin, Hurto, Rebecca L, Freddolino, Peter L, Zhang, Yang, Bhat, Prajwal, Supek, Fran, Fernández, José M, Gemovic, Branislava, Perovic, Vladimir R, Davidović, Radoslav S, Sumonja, Neven, Veljkovic, Nevena, Asgari, Ehsaneddin, Mofrad, Mohammad RK, Profiti, Giuseppe, Savojardo, Castrense, Martelli, Pier Luigi, Casadio, Rita, Boecker, Florian, Schoof, Heiko, Kahanda, Indika, Thurlby, Natalie, McHardy, Alice C, Renaux, Alexandre, Saidi, Rabie, Gough, Julian, Freitas, Alex A, Antczak, Magdalena, Fabris, Fabio, Wass, Mark N, Hou, Jie, Cheng, Jianlin, Wang, Zheng, Romero, Alfonso E, Paccanaro, Alberto, Yang, Haixuan, Goldberg, Tatyana, Zhao, Chenguang, Holm, Liisa, Törönen, Petri, Medlar, Alan J, Zosa, Elaine, Borukhov, Itamar, Novikov, Ilya, Wilkins, Angela, Lichtarge, Olivier, Chi, Po-Han, Tseng, Wei-Cheng, Linial, Michal, Rose, Peter W, Dessimoz, Christophe, Vidulin, Vedrana, Dzeroski, Saso, Sillitoe, Ian, Das, Sayoni, Lees, Jonathan Gill, Jones, David T, Wan, Cen, Cozzetto, Domenico, Fa, Rui, Torres, Mateo, Warwick Vesztrocy, Alex, Rodriguez, Jose Manuel, Tress, Michael L, Frasca, Marco, Notaro, Marco, Grossi, Giuliano, Petrini, Alessandro, Re, Matteo, Valentini, Giorgio, Mesiti, Marco, Roche, Daniel B, Reeb, Jonas, Ritchie, David W, Aridhi, Sabeur, Alborzi, Seyed Ziaeddin, Devignes, Marie-Dominique, Koo, Da Chen Emily, Bonneau, Richard, Gligorijević, Vladimir, Barot, Meet, Fang, Hai, Toppo, Stefano, and Lavezzo, Enrico

Subjects
Bioinformatics, Long-Term, Long-term memory, Memory, Information and Computing Sciences, Candida albicans, Genetics, Animals, Humans, Genome, Biofilm, Human Genome, Bacterial, Molecular Sequence Annotation, Biological Sciences, Critical assessment, Drosophila melanogaster, Fungal, Networking and Information Technology R&D (NITRD), Biofilms, Pseudomonas aeruginosa, Generic health relevance, Community challenge, Protein function prediction, Locomotion, Environmental Sciences
Abstract

BACKGROUND:The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. RESULTS:Here, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory. CONCLUSION:We conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens.

Published
2019

4. MOESM2 of The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

Author

Naihui Zhou, Yuxiang Jiang, Bergquist, Timothy, Lee, Alexandra, Balint Kacsoh, Crocker, Alex, Lewis, Kimberley, Georghiou, George, Nguyen, Huy, Md Nafiz Hamid, Davis, Larry, Tunca Dogan, Atalay, Volkan, Rifaioglu, Ahmet, Dalkıran, Alperen, Rengul Cetin Atalay, Chengxin Zhang, Hurto, Rebecca, Freddolino, Peter, Zhang, Yang, Prajwal Bhat, Supek, Fran, Fernández, José, Gemovic, Branislava, Perovic, Vladimir, Davidović, Radoslav, Sumonja, Neven, Veljkovic, Nevena, Ehsaneddin Asgari, Mofrad, Mohammad, Profiti, Giuseppe, Castrense Savojardo, Martelli, Pier Luigi, Casadio, Rita, Boecker, Florian, Schoof, Heiko, Indika Kahanda, Thurlby, Natalie, McHardy, Alice, Renaux, Alexandre, Saidi, Rabie, Gough, Julian, Freitas, Alex, Antczak, Magdalena, Fabris, Fabio, Wass, Mark, Hou, Jie, Jianlin Cheng, Wang, Zheng, Romero, Alfonso, Paccanaro, Alberto, Haixuan Yang, Goldberg, Tatyana, Chenguang Zhao, Holm, Liisa, Törönen, Petri, Medlar, Alan, Zosa, Elaine, Borukhov, Itamar, Novikov, Ilya, Wilkins, Angela, Lichtarge, Olivier, Po-Han Chi, Tseng, Wei-Cheng, Linial, Michal, Rose, Peter, Dessimoz, Christophe, Vidulin, Vedrana, Saso Dzeroski, Sillitoe, Ian, Sayoni Das, Lees, Jonathan Gill, Jones, David, Wan, Cen, Cozzetto, Domenico, Fa, Rui, Torres, Mateo, Vesztrocy, Alex Warwick, Rodriguez, Jose Manuel, Tress, Michael, Frasca, Marco, Notaro, Marco, Grossi, Giuliano, Petrini, Alessandro, Re, Matteo, Valentini, Giorgio, Mesiti, Marco, Roche, Daniel, Reeb, Jonas, Ritchie, David, Sabeur Aridhi, Alborzi, Seyed Ziaeddin, Marie-Dominique Devignes, Koo, Da Chen Emily, Bonneau, Richard, Gligorijević, Vladimir, Meet Barot, Fang, Hai, Toppo, Stefano, Lavezzo, Enrico, Falda, Marco, Berselli, Michele, Tosatto, Silvio, Carraro, Marco, Piovesan, Damiano, Hafeez Ur Rehman, Qizhong Mao, Shanshan Zhang, Vucetic, Slobodan, Black, Gage, Jo, Dane, Suh, Erica, Dayton, Jonathan, Larsen, Dallas, Omdahl, Ashton, McGuffin, Liam, Brackenridge, Danielle, Babbitt, Patricia, Yunes, Jeffrey, Fontana, Paolo, Zhang, Feng, Shanfeng Zhu, Ronghui You, Zihan Zhang, Suyang Dai, Shuwei Yao, Weidong Tian, Renzhi Cao, Chandler, Caleb, Amezola, Miguel, Johnson, Devon, Chang, Jia-Ming, Wen-Hung Liao, Liu, Yi-Wei, Pascarelli, Stefano, Yotam Frank, Hoehndorf, Robert, Kulmanov, Maxat, Boudellioua, Imane, Politano, Gianfranco, Carlo, Stefano Di, Benso, Alfredo, Hakala, Kai, Ginter, Filip, Mehryary, Farrokh, Suwisa Kaewphan, Björne, Jari, Moen, Hans, Tolvanen, Martti, Salakoski, Tapio, Kihara, Daisuke, Aashish Jain, Šmuc, Tomislav, Altenhoff, Adrian, Ben-Hur, Asa, Rost, Burkhard, Brenner, Steven, Orengo, Christine, Jeffery, Constance, Bosco, Giovanni, Hogan, Deborah, Martin, Maria, O’Donovan, Claire, Mooney, Sean, Greene, Casey, Radivojac, Predrag, and Friedberg, Iddo

Subjects
Pharmacology, FOS: Biological sciences, Genetics, Molecular Biology, 69999 Biological Sciences not elsewhere classified, Developmental Biology
Abstract

Additional file 2 Review History.

Published
2019
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8. Mapping and characterization of G-quadruplexes in Mycobacterium tuberculosis gene promoter regions

Author

Perrone, Rosalba, Lavezzo, Enrico, Riello, Erika, Manganelli, Riccardo, Palù, Giorgio, Toppo, Stefano, Provvedi, Roberta, and Richter, Sara N.

Subjects
0301 basic medicine, Tuberculosis, Science, Antitubercular Agents, Biology, G-quadruplex, Genome, Article, Mycobacterium tuberculosis, 03 medical and health sciences, In vivo, medicine, heterocyclic compounds, Promoter Regions, Genetic, Gene, Genetics, Multidisciplinary, 030102 biochemistry & molecular biology, Computational Biology, Promoter, medicine.disease, biology.organism_classification, 3. Good health, G-Quadruplexes, 030104 developmental biology, Immunology, Nucleic acid, Medicine, Genome, Bacterial
Abstract

Mycobacterium tuberculosis is the causative agent of tuberculosis (TB), one of the top 10 causes of death worldwide in 2015. The recent emergence of strains resistant to all current drugs urges the development of compounds with new mechanisms of action. G-quadruplexes are nucleic acids secondary structures that may form in G-rich regions to epigenetically regulate cellular functions. Here we implemented a computational tool to scan the presence of putative G-quadruplex forming sequences in the genome of Mycobacterium tuberculosis and analyse their association to transcription start sites. We found that the most stable G-quadruplexes were in the promoter region of genes belonging to definite functional categories. Actual G-quadruplex folding of four selected sequences was assessed by biophysical and biomolecular techniques: all molecules formed stable G-quadruplexes, which were further stabilized by two G-quadruplex ligands. These compounds inhibited Mycobacterium tuberculosis growth with minimal inhibitory concentrations in the low micromolar range. These data support formation of Mycobacterium tuberculosis G-quadruplexes in vivo and their potential regulation of gene transcription, and prompt the use of G4 ligands to develop original antitubercular agents.

Published
2017
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9. An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Author

Jiang, Yuxiang, Oron, Tal Ronnen, Clark, Wyatt T, Bankapur, Asma R, D'Andrea, Daniel, Lepore, Rosalba, Funk, Christopher S, Kahanda, Indika, Verspoor, Karin M, Ben-Hur, Asa, Koo, Da Chen Emily, Penfold-Brown, Duncan, Shasha, Dennis, Youngs, Noah, Bonneau, Richard, Lin, Alexandra, Sahraeian, Sayed ME, Martelli, Pier Luigi, Profiti, Giuseppe, Casadio, Rita, Cao, Renzhi, Zhong, Zhaolong, Cheng, Jianlin, Altenhoff, Adrian, Skunca, Nives, Dessimoz, Christophe, Dogan, Tunca, Hakala, Kai, Kaewphan, Suwisa, Mehryary, Farrokh, Salakoski, Tapio, Ginter, Filip, Fang, Hai, Smithers, Ben, Oates, Matt, Gough, Julian, Törönen, Petri, Koskinen, Patrik, Holm, Liisa, Chen, Ching-Tai, Hsu, Wen-Lian, Bryson, Kevin, Cozzetto, Domenico, Minneci, Federico, Jones, David T, Chapman, Samuel, Bkc, Dukka, Khan, Ishita K, Kihara, Daisuke, Ofer, Dan, Rappoport, Nadav, Stern, Amos, Cibrian-Uhalte, Elena, Denny, Paul, Foulger, Rebecca E, Hieta, Reija, Legge, Duncan, Lovering, Ruth C, Magrane, Michele, Melidoni, Anna N, Mutowo-Meullenet, Prudence, Pichler, Klemens, Shypitsyna, Aleksandra, Li, Biao, Zakeri, Pooya, ElShal, Sarah, Tranchevent, Léon-Charles, Das, Sayoni, Dawson, Natalie L, Lee, David, Lees, Jonathan G, Sillitoe, Ian, Bhat, Prajwal, Nepusz, Tamás, Romero, Alfonso E, Sasidharan, Rajkumar, Yang, Haixuan, Paccanaro, Alberto, Gillis, Jesse, Sedeño-Cortés, Adriana E, Pavlidis, Paul, Feng, Shou, Cejuela, Juan M, Goldberg, Tatyana, Hamp, Tobias, Richter, Lothar, Salamov, Asaf, Gabaldon, Toni, Marcet-Houben, Marina, Supek, Fran, Gong, Qingtian, Ning, Wei, Zhou, Yuanpeng, Tian, Weidong, Falda, Marco, Fontana, Paolo, Lavezzo, Enrico, Toppo, Stefano, Ferrari, Carlo, and Giollo, Manuel

Subjects
q-bio.QM, Bioinformatics, Protein, 1.1 Normal biological development and functioning, Proteins, Computational Biology, Molecular Sequence Annotation, Biological Sciences, Disease gene prioritization, Structure-Activity Relationship, Databases, Gene Ontology, Networking and Information Technology R&D (NITRD), Underpinning research, Information and Computing Sciences, Genetics, Humans, Generic health relevance, Protein function prediction, Algorithms, Software, Environmental Sciences
Abstract

BackgroundA major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging.ResultsWe conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2.ConclusionsThe top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent.

Published
2016

10. Additional file 1 of An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Author

Yuxiang Jiang, Oron, Tal Ronnen, Clark, Wyatt T., Bankapur, Asma R., D’Andrea, Daniel, Lepore, Rosalba, Funk, Christopher S., Indika Kahanda, Verspoor, Karin M., Ben-Hur, Asa, Koo, Da Chen Emily, Penfold-Brown, Duncan, Shasha, Dennis, Youngs, Noah, Bonneau, Richard, Lin, Alexandra, Sahraeian, Sayed M. E., Martelli, Pier Luigi, Profiti, Giuseppe, Casadio, Rita, Renzhi Cao, Zhaolong Zhong, Jianlin Cheng, Altenhoff, Adrian, Skunca, Nives, Dessimoz, Christophe, Tunca Dogan, Hakala, Kai, Suwisa Kaewphan, Mehryary, Farrokh, Salakoski, Tapio, Ginter, Filip, Fang, Hai, Smithers, Ben, Oates, Matt, Gough, Julian, Törönen, Petri, Koskinen, Patrik, Holm, Liisa, Ching-Tai Chen, Hsu, Wen-Lian, Bryson, Kevin, Cozzetto, Domenico, Minneci, Federico, Jones, David T., Chapman, Samuel, Dukka BKC, Ishita K. Khan, Kihara, Daisuke, Ofer, Dan, Rappoport, Nadav, Stern, Amos, Cibrian-Uhalte, Elena, Denny, Paul, Foulger, Rebecca E., Hieta, Reija, Legge, Duncan, Lovering, Ruth C., Magrane, Michele, Melidoni, Anna N., Mutowo-Meullenet, Prudence, Pichler, Klemens, Shypitsyna, Aleksandra, Li, Biao, Pooya Zakeri, ElShal, Sarah, Léon-Charles Tranchevent, Sayoni Das, Dawson, Natalie L., Lee, David, Lees, Jonathan G., Sillitoe, Ian, Prajwal Bhat, Nepusz, Tamás, Romero, Alfonso E., Sasidharan, Rajkumar, Haixuan Yang, Paccanaro, Alberto, Gillis, Jesse, Sedeño-Cortés, Adriana E., Pavlidis, Paul, Feng, Shou, Cejuela, Juan M., Goldberg, Tatyana, Hamp, Tobias, Richter, Lothar, Salamov, Asaf, Gabaldon, Toni, Marcet-Houben, Marina, Supek, Fran, Qingtian Gong, Ning, Wei, Yuanpeng Zhou, Weidong Tian, Falda, Marco, Fontana, Paolo, Lavezzo, Enrico, Toppo, Stefano, Ferrari, Carlo, Giollo, Manuel, Piovesan, Damiano, Tosatto, Silvio C.E., Pozo, Angela Del, Fernández, José M., Maietta, Paolo, Valencia, Alfonso, Tress, Michael L., Benso, Alfredo, Carlo, Stefano Di, Politano, Gianfranco, Savino, Alessandro, Hafeez Ur Rehman, Re, Matteo, Mesiti, Marco, Valentini, Giorgio, Bargsten, Joachim W., Dijk, Aalt D. J. Van, Gemovic, Branislava, Glisic, Sanja, Vladmir Perovic, Veljkovic, Veljko, Veljkovic, Nevena, Danillo C. Almeida-E-Silva, Vencio, Ricardo Z. N., Malvika Sharan, Vogel, Jörg, Lakesh Kansakar, Shanshan Zhang, Vucetic, Slobodan, Wang, Zheng, Sternberg, Michael J. E., Wass, Mark N., Huntley, Rachael P., Martin, Maria J., O’Donovan, Claire, Robinson, Peter N., Moreau, Yves, Tramontano, Anna, Babbitt, Patricia C., Brenner, Steven E., Linial, Michal, Orengo, Christine A., Rost, Burkhard, Greene, Casey S., Mooney, Sean D., Friedberg, Iddo, and Radivojac, Predrag

Abstract

A document containing a subset of CAFA2 analyses that are equivalent to those provided about the CAFA1 experiment in the CAFA1 supplement. (PDF 11100 kb)

Published
2016
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11. A large-scale evaluation of computational protein function prediction

Author

Radivojac, Predrag, Clark, Wyatt T, Oron, Tal Ronnen, Schnoes, Alexandra M, Wittkop, Tobias, Sokolov, Artem, Graim, Kiley, Funk, Christopher, Verspoor, Karin, Ben-Hur, Asa, Pandey, Gaurav, Yunes, Jeffrey M, Talwalkar, Ameet S, Repo, Susanna, Souza, Michael L, Piovesan, Damiano, Casadio, Rita, Wang, Zheng, Cheng, Jianlin, Fang, Hai, Gough, Julian, Koskinen, Patrik, Törönen, Petri, Nokso-Koivisto, Jussi, Holm, Liisa, Cozzetto, Domenico, Buchan, Daniel WA, Bryson, Kevin, Jones, David T, Limaye, Bhakti, Inamdar, Harshal, Datta, Avik, Manjari, Sunitha K, Joshi, Rajendra, Chitale, Meghana, Kihara, Daisuke, Lisewski, Andreas M, Erdin, Serkan, Venner, Eric, Lichtarge, Olivier, Rentzsch, Robert, Yang, Haixuan, Romero, Alfonso E, Bhat, Prajwal, Paccanaro, Alberto, Hamp, Tobias, Kaßner, Rebecca, Seemayer, Stefan, Vicedo, Esmeralda, Schaefer, Christian, Achten, Dominik, Auer, Florian, Boehm, Ariane, Braun, Tatjana, Hecht, Maximilian, Heron, Mark, Hönigschmid, Peter, Hopf, Thomas A, Kaufmann, Stefanie, Kiening, Michael, Krompass, Denis, Landerer, Cedric, Mahlich, Yannick, Roos, Manfred, Björne, Jari, Salakoski, Tapio, Wong, Andrew, Shatkay, Hagit, Gatzmann, Fanny, Sommer, Ingolf, Wass, Mark N, Sternberg, Michael JE, Škunca, Nives, Supek, Fran, Bošnjak, Matko, Panov, Panče, Džeroski, Sašo, Šmuc, Tomislav, Kourmpetis, Yiannis AI, van Dijk, Aalt DJ, ter Braak, Cajo JF, Zhou, Yuanpeng, Gong, Qingtian, Dong, Xinran, Tian, Weidong, Falda, Marco, Fontana, Paolo, Lavezzo, Enrico, Di Camillo, Barbara, Toppo, Stefano, Lan, Liang, Djuric, Nemanja, Guo, Yuhong, Vucetic, Slobodan, Bairoch, Amos, Linial, Michal, Babbitt, Patricia C, Brenner, Steven E, Orengo, Christine, and Rost, Burkhard

Subjects
Technology, Protein, Proteins, Computational Biology, Molecular Sequence Annotation, Biological Sciences, Medical and Health Sciences, Databases, Species Specificity, Exoribonucleases, Animals, Humans, Generic health relevance, Molecular Biology, Algorithms, Forecasting, Developmental Biology
Abstract

Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is crucial that the accuracy of these methods be high. Here we report the results from the first large-scale community-based critical assessment of protein function annotation (CAFA) experiment. Fifty-four methods representing the state of the art for protein function prediction were evaluated on a target set of 866 proteins from 11 organisms. Two findings stand out: (i) today's best protein function prediction algorithms substantially outperform widely used first-generation methods, with large gains on all types of targets; and (ii) although the top methods perform well enough to guide experiments, there is considerable need for improvement of currently available tools.

Published
2013

17. [Untitled]

Author

Perrone, Rosalba, Lavezzo, Enrico, Palù, Giorgio, and Richter, Sara N.

Subjects
0301 basic medicine, Sp1 Transcription Factor, Science, LTR, viruses, Human immunodeficiency virus (HIV), medicine.disease_cause, G-quadruplex, Article, Human immuunodeficiency virus, 03 medical and health sciences, lentivirus, Transcription (biology), medicine, Animals, Humans, Position-Specific Scoring Matrices, Binding site, Promoter Regions, Genetic, Conserved Sequence, Phylogeny, Polymerase, HIV Long Terminal Repeat, Genetics, Binding Sites, promoter, Multidisciplinary, Base Sequence, biology, Terminal Repeat Sequences, HIV, biology.organism_classification, Long terminal repeat, SP1, G-Quadruplexes, 030104 developmental biology, Lentivirus, HIV-1, Nucleic acid, biology.protein, Medicine, G-quadruplex, HIV, Human immuunodeficiency virus, lentivirus, LTR, promoter, SP1, Protein Binding
Abstract

G-quadruplexes (G4s) are secondary structures of nucleic acids that epigenetically regulate cellular processes. In the human immunodeficiency lentivirus 1 (HIV-1), dynamic G4s are located in the unique viral LTR promoter. Folding of HIV-1 LTR G4s inhibits viral transcription; stabilization by G4 ligands intensifies this effect. Cellular proteins modulate viral transcription by inducing/unfolding LTR G4s. We here expanded our investigation on the presence of LTR G4s to all lentiviruses. G4s in the 5′-LTR U3 region were completely conserved in primate lentiviruses. A G4 was also present in a cattle-infecting lentivirus. All other non-primate lentiviruses displayed hints of less stable G4s. In primate lentiviruses, the possibility to fold into G4s was highly conserved among strains. LTR G4 sequences were very similar among phylogenetically related primate viruses, while they increasingly differed in viruses that diverged early from a common ancestor. A strong correlation between primate lentivirus LTR G4s and Sp1/NFκB binding sites was found. All LTR G4s folded: their complexity was assessed by polymerase stop assay. Our data support a role of the lentiviruses 5′-LTR G4 region as control centre of viral transcription, where folding/unfolding of G4s and multiple recruitment of factors based on both sequence and structure may take place.

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