1
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Cross EM, Akbari N, Ghassabian H, Hoad M, Pavan S, Ariawan D, Donnelly CM, Lavezzo E, Petersen GF, Forwood JK, Alvisi G. A functional and structural comparative analysis of large tumor antigens reveals evolution of different importin α-dependent nuclear localization signals. Protein Sci 2024; 33:e4876. [PMID: 38108201 PMCID: PMC10807245 DOI: 10.1002/pro.4876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 12/12/2023] [Accepted: 12/13/2023] [Indexed: 12/19/2023]
Abstract
Nucleocytoplasmic transport regulates the passage of proteins between the nucleus and cytoplasm. In the best characterized pathway, importin (IMP) α bridges cargoes bearing basic, classical nuclear localization signals (cNLSs) to IMPβ1, which mediates transport through the nuclear pore complex. IMPα recognizes three types of cNLSs via two binding sites: the major binding site accommodates monopartite cNLSs, the minor binding site recognizes atypical cNLSs, while bipartite cNLSs simultaneously interact with both major and minor sites. Despite the growing knowledge regarding IMPα-cNLS interactions, our understanding of the evolution of cNLSs is limited. We combined bioinformatic, biochemical, functional, and structural approaches to study this phenomenon, using polyomaviruses (PyVs) large tumor antigens (LTAs) as a model. We characterized functional cNLSs from all human (H)PyV LTAs, located between the LXCXE motif and origin binding domain. Surprisingly, the prototypical SV40 monopartite NLS is not well conserved; HPyV LTA NLSs are extremely heterogenous in terms of structural organization, IMPα isoform binding, and nuclear targeting abilities, thus influencing the nuclear accumulation properties of full-length proteins. While several LTAs possess bipartite cNLSs, merkel cell PyV contains a hybrid bipartite cNLS whose upstream stretch of basic amino acids can function as an atypical cNLS, specifically binding to the IMPα minor site upon deletion of the downstream amino acids after viral integration in the host genome. Therefore, duplication of a monopartite cNLS and subsequent accumulation of point mutations, optimizing interaction with distinct IMPα binding sites, led to the evolution of bipartite and atypical NLSs binding at the minor site.
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Affiliation(s)
- Emily M. Cross
- School of Dentistry and Medical SciencesCharles Sturt UniversityWagga WaggaAustralia
- Diamond Light SourceHarwell Science and Innovation CampusDidcotUnited Kingdom
| | - Nasim Akbari
- Department of Molecular MedicineUniversity of PadovaPadovaItaly
| | | | - Mikayla Hoad
- School of Dentistry and Medical SciencesCharles Sturt UniversityWagga WaggaAustralia
| | - Silvia Pavan
- Department of Molecular MedicineUniversity of PadovaPadovaItaly
| | - Daryl Ariawan
- Dementia Research CentreMacquarie UniversitySydneyAustralia
| | - Camilla M. Donnelly
- School of Dentistry and Medical SciencesCharles Sturt UniversityWagga WaggaAustralia
| | - Enrico Lavezzo
- Department of Molecular MedicineUniversity of PadovaPadovaItaly
| | | | - Jade K. Forwood
- School of Dentistry and Medical SciencesCharles Sturt UniversityWagga WaggaAustralia
- Gulbali InstituteCharles Sturt UniversityWagga WaggaAustralia
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2
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Bernabè G, Brun P, Pietra GD, Zatta V, Asad S, Meneghello S, Cordioli G, Lavezzo E, Valente E, Mietto S, Besutti V, Castagliuolo I. Prevalence and virulence potential of Aeromonas spp. isolated from human diarrheal samples in North East Italy. Microbiol Spectr 2023; 11:e0080723. [PMID: 37855641 PMCID: PMC10715124 DOI: 10.1128/spectrum.00807-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 09/08/2023] [Indexed: 10/20/2023] Open
Abstract
IMPORTANCE In this work, we demonstrate the epidemiologic relevance of the Aeromonas genus as the cause of infective diarrhea in North East Italy, both in children and adult subjects, with the significative presence of highly pathogenic strains. Aeromonas strains possess a heterogeneous armamentarium of pathogenicity factors that allows the microbe to affect a wide range of human intestinal epithelial cell processes that justify the ability to induce diarrhea through different mechanisms and cause diseases of variable severity, as observed for other gastrointestinal pathogens. However, it remains to be determined whether specific genotype(s) are associated with clinical pictures of different severity to implement the diagnostic and therapeutic approaches for this relevant enteric pathogen.
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Affiliation(s)
- Giulia Bernabè
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Paola Brun
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | | | - Veronica Zatta
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Shirin Asad
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Silvia Meneghello
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | | | - Enrico Lavezzo
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Elisabetta Valente
- Department of Molecular Medicine, University of Padova, Padova, Italy
- Microbiology Unit of Padua University Hospital, Padova, Italy
| | - Sofia Mietto
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Valeria Besutti
- Microbiology Unit of Padua University Hospital, Padova, Italy
| | - Ignazio Castagliuolo
- Department of Molecular Medicine, University of Padova, Padova, Italy
- Microbiology Unit of Padua University Hospital, Padova, Italy
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3
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Bianca F, Ispano E, Gazzola E, Lavezzo E, Fontana P, Toppo S. FunTaxIS-lite: a simple and light solution to investigate protein functions in all living organisms. Bioinformatics 2023; 39:btad549. [PMID: 37672040 PMCID: PMC10500080 DOI: 10.1093/bioinformatics/btad549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 07/27/2023] [Accepted: 09/05/2023] [Indexed: 09/07/2023] Open
Abstract
MOTIVATION Defining the full domain of protein functions belonging to an organism is a complex challenge that is due to the huge heterogeneity of the taxonomy, where single or small groups of species can bear unique functional characteristics. FunTaxIS-lite provides a solution to this challenge by determining taxon-based constraints on Gene Ontology (GO) terms, which specify the functions that an organism can or cannot perform. The tool employs a set of rules to generate and spread the constraints across both the taxon hierarchy and the GO graph. RESULTS The taxon-based constraints produced by FunTaxIS-lite extend those provided by the Gene Ontology Consortium by an average of 300%. The implementation of these rules significantly reduces errors in function predictions made by automatic algorithms and can assist in correcting inconsistent protein annotations in databases. AVAILABILITY AND IMPLEMENTATION FunTaxIS-lite is available on https://www.medcomp.medicina.unipd.it/funtaxis-lite and from https://github.com/MedCompUnipd/FunTaxIS-lite.
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Affiliation(s)
- Federico Bianca
- Computational Medicine Group (MedComp), Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Emilio Ispano
- Computational Medicine Group (MedComp), Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Ermanno Gazzola
- Computational Medicine Group (MedComp), Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Enrico Lavezzo
- Computational Medicine Group (MedComp), Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Paolo Fontana
- Research and Innovation Center, Edmund Mach Foundation, San Michele all'Adige, Trento, Italy
| | - Stefano Toppo
- Computational Medicine Group (MedComp), Department of Molecular Medicine, University of Padova, Padova, Italy
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4
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Baruzzo G, Serafini A, Finotello F, Sanavia T, Cioetto-Mazzabò L, Boldrin F, Lavezzo E, Barzon L, Toppo S, Provvedi R, Manganelli R, Di Camillo B. Role of the Extracytoplasmic Function Sigma Factor SigE in the Stringent Response of Mycobacterium tuberculosis. Microbiol Spectr 2023; 11:e0294422. [PMID: 36946740 PMCID: PMC10100808 DOI: 10.1128/spectrum.02944-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Accepted: 02/15/2023] [Indexed: 03/23/2023] Open
Abstract
Bacteria respond to nutrient starvation implementing the stringent response, a stress signaling system resulting in metabolic remodeling leading to decreased growth rate and energy requirements. A well-characterized model of stringent response in Mycobacterium tuberculosis is the one induced by growth in low phosphate. The extracytoplasmic function (ECF) sigma factor SigE was previously suggested as having a key role in the activation of stringent response. In this study, we challenge this hypothesis by analyzing the temporal dynamics of the transcriptional response of a sigE mutant and its wild-type parental strain to low phosphate using RNA sequencing. We found that both strains responded to low phosphate with a typical stringent response trait, including the downregulation of genes encoding ribosomal proteins and RNA polymerase. We also observed transcriptional changes that support the occurring of an energetics imbalance, compensated by a reduced activity of the electron transport chain, decreased export of protons, and a remodeling of central metabolism. The most striking difference between the two strains was the induction in the sigE mutant of several stress-related genes, in particular, the genes encoding the ECF sigma factor SigH and the transcriptional regulator WhiB6. Since both proteins respond to redox unbalances, their induction suggests that the sigE mutant is not able to maintain redox homeostasis in response to the energetics imbalance induced by low phosphate. In conclusion, our data suggest that SigE is not directly involved in initiating stringent response but in protecting the cell from stress consequent to the low phosphate exposure and activation of stringent response. IMPORTANCE Mycobacterium tuberculosis can enter a dormant state enabling it to establish latent infections and to become tolerant to antibacterial drugs. Dormant bacteria's physiology and the mechanism(s) used by bacteria to enter dormancy during infection are still unknown due to the lack of reliable animal models. However, several in vitro models, mimicking conditions encountered during infection, can reproduce different aspects of dormancy (growth arrest, metabolic slowdown, drug tolerance). The stringent response, a stress response program enabling bacteria to cope with nutrient starvation, is one of them. In this study, we provide evidence suggesting that the sigma factor SigE is not directly involved in the activation of stringent response as previously hypothesized, but it is important to help the bacteria to handle the metabolic stress related to the adaptation to low phosphate and activation of stringent response, thus giving an important contribution to our understanding of the mechanism behind stringent response development.
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Affiliation(s)
- Giacomo Baruzzo
- Department of Information Engineering, University of Padova, Padua, Italy
| | - Agnese Serafini
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | | | - Tiziana Sanavia
- Department of Information Engineering, University of Padova, Padua, Italy
| | | | - Francesca Boldrin
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | - Enrico Lavezzo
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | - Luisa Barzon
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | - Stefano Toppo
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | | | | | - Barbara Di Camillo
- Department of Information Engineering, University of Padova, Padua, Italy
- Department of Comparative Biomedicine and Food Science, University of Padova, Padua, Italy
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5
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Del Vecchio C, Cracknell Daniels B, Brancaccio G, Brazzale AR, Lavezzo E, Ciavarella C, Onelia F, Franchin E, Manuto L, Bianca F, Cianci V, Cattelan AM, Dorigatti I, Toppo S, Crisanti A. Impact of antigen test target failure and testing strategies on the transmission of SARS-CoV-2 variants. Nat Commun 2022; 13:5870. [PMID: 36198689 PMCID: PMC9533294 DOI: 10.1038/s41467-022-33460-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 09/15/2022] [Indexed: 11/09/2022] Open
Abstract
Population testing remains central to COVID-19 control and surveillance, with countries increasingly using antigen tests rather than molecular tests. Here we describe a SARS-CoV-2 variant that escapes N antigen tests due to multiple disruptive amino-acid substitutions in the N protein. By fitting a multistrain compartmental model to genomic and epidemiological data, we show that widespread antigen testing in the Italian region of Veneto favored the undetected spread of the antigen-escape variant compared to the rest of Italy. We highlight novel limitations of widespread antigen testing in the absence of molecular testing for diagnostic or confirmatory purposes. Notably, we find that genomic surveillance systems which rely on antigen population testing to identify samples for sequencing will bias detection of escape antigen test variants. Together, these findings highlight the importance of retaining molecular testing for surveillance purposes, including in contexts where the use of antigen tests is widespread.
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Affiliation(s)
- Claudia Del Vecchio
- Department of Molecular Medicine, University of Padua, Via Gabelli, 63, Padua, 35121, Italy
| | - Bethan Cracknell Daniels
- MRC Centre for Global Infectious Disease Analysis and Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Giuseppina Brancaccio
- Department of Molecular Medicine, University of Padua, Via Gabelli, 63, Padua, 35121, Italy
| | | | - Enrico Lavezzo
- Department of Molecular Medicine, University of Padua, Via Gabelli, 63, Padua, 35121, Italy
| | - Constanze Ciavarella
- MRC Centre for Global Infectious Disease Analysis and Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Francesco Onelia
- Microbiology and Virology Diagnostic Unit, Padua University Hospital, Via Giustiniani 2, Padua, 35128, Italy
| | - Elisa Franchin
- Microbiology and Virology Diagnostic Unit, Padua University Hospital, Via Giustiniani 2, Padua, 35128, Italy
| | - Laura Manuto
- Department of Molecular Medicine, University of Padua, Via Gabelli, 63, Padua, 35121, Italy
| | - Federico Bianca
- Department of Molecular Medicine, University of Padua, Via Gabelli, 63, Padua, 35121, Italy
| | - Vito Cianci
- ER Unit, Emergency-Urgency Department, Padua University Hospital, Via Giustiniani 2, Padua, 35128, Italy
| | - Anna Maria Cattelan
- Infectious and Tropical Diseases Unit, Padua University Hospital, Via Giustiniani 2, Padua, 35128, Italy
| | - Ilaria Dorigatti
- MRC Centre for Global Infectious Disease Analysis and Jameel Institute, School of Public Health, Imperial College London, London, UK.
| | - Stefano Toppo
- Department of Molecular Medicine, University of Padua, Via Gabelli, 63, Padua, 35121, Italy. .,CRIBI Biotech Center, University of Padua, V.le G. Colombo, 3, Padua, 35131, Italy.
| | - Andrea Crisanti
- Department of Molecular Medicine, University of Padua, Via Gabelli, 63, Padua, 35121, Italy. .,Microbiology and Virology Diagnostic Unit, Padua University Hospital, Via Giustiniani 2, Padua, 35128, Italy. .,Department of Life Science, Imperial College London, South Kensington Campus, Imperial College Road, SW7 AZ, London, UK.
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6
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Ruggiero E, Lavezzo E, Grazioli M, Zanin I, Marušič M, Plavec J, Richter SN, Toppo S. Human Virus Genomes Are Enriched in Conserved Adenine/Thymine/Uracil Multiple Tracts That Pause Polymerase Progression. Front Microbiol 2022; 13:915069. [PMID: 35722311 PMCID: PMC9198555 DOI: 10.3389/fmicb.2022.915069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 05/02/2022] [Indexed: 11/13/2022] Open
Abstract
The DNA secondary structures that deviate from the classic Watson and Crick base pairing are increasingly being reported to form transiently in the cell and regulate specific cellular mechanisms. Human viruses are cell parasites that have evolved mechanisms shared with the host cell to support their own replication and spreading. Contrary to human host cells, viruses display a diverse array of nucleic acid types, which include DNA or RNA in single-stranded or double-stranded conformations. This heterogeneity improves the possible occurrence of non-canonical nucleic acid structures. We have previously shown that human virus genomes are enriched in G-rich sequences that fold in four-stranded nucleic acid secondary structures, the G-quadruplexes.Here, by extensive bioinformatics analysis on all available genomes, we showed that human viruses are enriched in highly conserved multiple A (and T or U) tracts, with such an array that they could in principle form quadruplex structures. By circular dichroism, NMR, and Taq polymerase stop assays, we proved that, while A/T/U-quadruplexes do not form, these tracts still display biological significance, as they invariably trigger polymerase pausing within two bases from the A/T/U tract. “A” bases display the strongest effect. Most of the identified A-tracts are in the coding strand, both at the DNA and RNA levels, suggesting their possible relevance during viral translation. This study expands on the presence and mechanism of nucleic acid secondary structures in human viruses and provides a new direction for antiviral research.
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Affiliation(s)
| | - Enrico Lavezzo
- Department of Molecular Medicine, University of Padua, Padua, Italy
| | - Marco Grazioli
- Department of Molecular Medicine, University of Padua, Padua, Italy
| | - Irene Zanin
- Department of Molecular Medicine, University of Padua, Padua, Italy
| | - Maja Marušič
- Slovenian NMR Centre, National Institute of Chemistry, Ljubljana, Slovenia
| | - Janez Plavec
- Slovenian NMR Centre, National Institute of Chemistry, Ljubljana, Slovenia
| | - Sara N Richter
- Department of Molecular Medicine, University of Padua, Padua, Italy
| | - Stefano Toppo
- Department of Molecular Medicine, University of Padua, Padua, Italy.,CRIBI Biotechnology Center, University of Padua, Padua, Italy
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7
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Gittelman RM, Lavezzo E, Snyder TM, Zahid HJ, Carty CL, Elyanow R, Dalai S, Kirsch I, Baldo L, Manuto L, Franchin E, Del Vecchio C, Pacenti M, Boldrin C, Cattai M, Saluzzo F, Padoan A, Plebani M, Simeoni F, Bordini J, Lorè NI, Lazarević D, Cirillo DM, Ghia P, Toppo S, Carlson JM, Robins HS, Crisanti A, Tonon G. Longitudinal analysis of T cell receptor repertoires reveals shared patterns of antigen-specific response to SARS-CoV-2 infection. JCI Insight 2022; 7:e151849. [PMID: 35439174 PMCID: PMC9220833 DOI: 10.1172/jci.insight.151849] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Accepted: 04/13/2022] [Indexed: 11/22/2022] Open
Abstract
T cells play a prominent role in orchestrating the immune response to viral diseases, but their role in the clinical presentation and subsequent immunity to SARS-CoV-2 infection remains poorly understood. As part of a population-based survey of the municipality of Vo', Italy, conducted after the initial SARS-CoV-2 outbreak, we sampled the T cell receptor (TCR) repertoires of the population 2 months after the initial PCR survey and followed up positive cases 9 and 15 months later. At 2 months, we found that 97.0% (98 of 101) of cases had elevated levels of TCRs associated with SARS-CoV-2. T cell frequency (depth) was increased in individuals with more severe disease. Both depth and diversity (breadth) of the TCR repertoire were positively associated with neutralizing antibody titers, driven mostly by CD4+ T cells directed against spike protein. At the later time points, detection of these TCRs remained high, with 90.7% (78 of 96) and 86.2% (25 of 29) of individuals having detectable signal at 9 and 15 months, respectively. Forty-three individuals were vaccinated by month 15 and showed a significant increase in TCRs directed against spike protein. Taken together, these results demonstrate the central role of T cells in mounting an immune defense against SARS-CoV-2 that persists out to 15 months.
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Affiliation(s)
| | - Enrico Lavezzo
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | | | | | | | | | - Sudeb Dalai
- Adaptive Biotechnologies, Seattle, Washington, USA
- Division of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Ilan Kirsch
- Adaptive Biotechnologies, Seattle, Washington, USA
| | - Lance Baldo
- Adaptive Biotechnologies, Seattle, Washington, USA
| | - Laura Manuto
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | - Elisa Franchin
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | | | - Monia Pacenti
- Azienda Ospedale Padova, Microbiology and Virology Unit, Padua, Italy
| | - Caterina Boldrin
- Azienda Ospedale Padova, Microbiology and Virology Unit, Padua, Italy
| | - Margherita Cattai
- Azienda Ospedale Padova, Microbiology and Virology Unit, Padua, Italy
| | - Francesca Saluzzo
- Division of Immunology, Transplantation and Infectious Disease, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Andrea Padoan
- Department of Medicine, University of Padova, Padua, Italy
| | - Mario Plebani
- Department of Medicine, University of Padova, Padua, Italy
| | | | - Jessica Bordini
- Division of Experimental Oncology, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Nicola I. Lorè
- Division of Immunology, Transplantation and Infectious Disease, IRCCS Ospedale San Raffaele, Milan, Italy
| | | | - Daniela M. Cirillo
- Division of Immunology, Transplantation and Infectious Disease, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Paolo Ghia
- Division of Experimental Oncology, IRCCS Ospedale San Raffaele, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Stefano Toppo
- Department of Molecular Medicine, University of Padova, Padua, Italy
- CRIBI Biotech Center, University of Padova, Padua, Italy
| | | | | | - Andrea Crisanti
- Department of Molecular Medicine, University of Padova, Padua, Italy
- Department of Life Sciences, Imperial College London, London, United Kingdom
| | - Giovanni Tonon
- Center for Omics Sciences and
- Division of Experimental Oncology, IRCCS Ospedale San Raffaele, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
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8
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Pattaro C, Barbieri G, Foco L, Weichenberger CX, Biasiotto R, De Grandi A, Fuchsberger C, Egger C, Amon VSC, Hicks AA, Mian M, Mahlknecht A, Lombardo S, Meier H, Weiss H, Rainer R, Dejaco C, Weiss G, Lavezzo E, Crisanti A, Pizzato M, Domingues FS, Mascalzoni D, Gögele M, Melotti R, Pramstaller PP. Prospective epidemiological, molecular, and genetic characterization of a novel coronavirus disease in the Val Venosta/Vinschgau: the CHRIS COVID-19 study protocol. Pathog Glob Health 2021; 116:128-136. [PMID: 34637685 PMCID: PMC8515786 DOI: 10.1080/20477724.2021.1978225] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
The COVID-19 pandemic has been threatening the healthcare and socioeconomic systems of entire nations. While population-based surveys to assess the distribution of SARS-CoV-2 infection have become a priority, pre-existing longitudinal studies are ideally suited to assess the determinants of COVID-19 onset and severity.The Cooperative Health Research In South Tyrol (CHRIS) study completed the baseline recruitment of 13,393 adults from the Venosta/Vinschgau rural district in 2018, collecting extensive phenotypic and biomarker data, metabolomic data, densely imputed genotype and whole-exome sequencing data.Based on CHRIS, we designed a prospective study, called CHRIS COVID-19, aimed at: 1) estimating the incidence of SARS-CoV-2 infections; 2) screening for and investigating the determinants of incident infection among CHRIS participants and their household members; 3) monitoring the immune response of infected participants prospectively.An online screening questionnaire was sent to all CHRIS participants and their household members. A random sample of 1450 participants representative of the district population was invited to assess active (nasopharyngeal swab) or past (serum antibody test) infections. We prospectively invited for complete SARS-CoV-2 testing all questionnaire completers gauged as possible cases of past infection and their household members. In positive tested individuals, antibody response is monitored quarterly for one year. Untested and negative participants receive the screening questionnaire every four weeks until gauged as possible incident cases or till the study end.Originated from a collaboration between researchers and community stakeholders, the CHRIS COVID-19 study aims at generating knowledge about the epidemiological, molecular, and genetic characterization of COVID-19 and its long-term sequelae.
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Affiliation(s)
- Cristian Pattaro
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
| | - Giulia Barbieri
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
| | - Luisa Foco
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
| | - Christian X Weichenberger
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
| | - Roberta Biasiotto
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
| | - Alessandro De Grandi
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
| | - Christian Fuchsberger
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
| | - Clemens Egger
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
| | - Vera S C Amon
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
| | - Andrew A Hicks
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
| | - Michael Mian
- Department of Haematology, Hospital of Bolzano SABES-ASDAA, Bolzano, Italy.,College of Health-Care Professions, Claudiana, Bolzano, Italy
| | - Angelika Mahlknecht
- Institute of General Medicine, Provincial School of Health (Claudiana), Bolzano, Italy.,Institute of General Practice, Family Medicine and Preventive Medicine, Paracelsus Medical University, Salzburg, Austria
| | - Stefano Lombardo
- Provincial Institute of Statistics (ASTAT), Administration of the Autonomous Province of Bolzano, Italy
| | - Horand Meier
- Clinical Governance Unit, Administration of the Autonomous Province of Bolzano, Italy
| | - Helmuth Weiss
- Hospital of Silandro, Healthcare System of the Autonomous Province of Bolzano, Italy
| | - Robert Rainer
- Hospital of Silandro, Healthcare System of the Autonomous Province of Bolzano, Italy
| | - Christian Dejaco
- Department of Rheumatology, Medical University Graz, Austria.,Department of Rheumatology, Hospital of Bruneck (SABES-ASDAA), Italy
| | - Günter Weiss
- Department of Internal Medicine II, Medical University of Innsbruck, Innsbruck, Austria
| | - Enrico Lavezzo
- Department of Molecular Medicine, University of Padova, Italy
| | - Andrea Crisanti
- Department of Molecular Medicine, University of Padova, Italy
| | - Massimo Pizzato
- Laboratory of Virus-Cell Interaction, Centre for Integrative Biology, University of Trento, Italy
| | - Francisco S Domingues
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
| | - Deborah Mascalzoni
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy.,Center for Research Ethics and Bioethics, Department of Public Health and Caring Sciences, Uppsala University, Uppsala Sweden
| | - Martin Gögele
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
| | - Roberto Melotti
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
| | - Peter P Pramstaller
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
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9
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Cocconcelli E, Castelli G, Onelia F, Lavezzo E, Giraudo C, Bernardinello N, Fichera G, Leoni D, Trevenzoli M, Saetta M, Cattelan A, Crisanti A, Spagnolo P, Balestro E. Disease Severity and Prognosis of SARS-CoV-2 Infection in Hospitalized Patients Is Not Associated With Viral Load in Nasopharyngeal Swab. Front Med (Lausanne) 2021; 8:714221. [PMID: 34568371 PMCID: PMC8460755 DOI: 10.3389/fmed.2021.714221] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Accepted: 08/16/2021] [Indexed: 01/10/2023] Open
Abstract
Background: The impact of viral burden on severity and prognosis of patients hospitalized for Coronavirus Disease 2019 (COVID-19) is still a matter of debate due to controversial results. Herein, we sought to assess viral load in the nasopharyngeal swab and its association with severity score indexes and prognostic parameters. Methods: We included 127 symptomatic patients and 21 asymptomatic subjects with a diagnosis of SARS-CoV-2 infection obtained by reverse transcription polymerase chain reaction and presence of cycle threshold. According to the level of care needed during hospitalization, the population was categorized as high-intensity (HIMC, n = 76) or low intensity medical care setting (LIMC, n = 51). Results: Viral load did not differ among asymptomatic, LIMC, and HIMC SARS-CoV-2 positive patients [4.4 (2.9-5.3) vs. 4.8 (3.6-6.1) vs. 4.6 (3.9-5.7) log10 copies/ml, respectively; p = 0.31]. Similar results were observed when asymptomatic individuals were compared to hospitalized patients [4.4 (2.9-5.3) vs. 4.68 (3.8-5.9) log10 copies/ml; p = 0.13]. When the study population was divided in High (HVL, n = 64) and Low Viral Load (LVL, n = 63) group no differences were observed in disease severity at diagnosis. Furthermore, LVL and HVL groups did not differ with regard to duration of hospital stay, number of bacterial co-infections, need for high-intensity medical care and number of deaths. The viral load was not an independent risk factor for HIMC in an adjusted multivariate regression model (OR: 1.59; 95% CI: 0.46-5.55, p = 0.46). Conclusions: Viral load at diagnosis is similar in asymptomatic and hospitalized patients and is not associated with either worse outcomes during hospitalization. SARS CoV-2 viral load might not be the right tool to assist clinicians in risk-stratifying hospitalized patients.
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Affiliation(s)
- Elisabetta Cocconcelli
- Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova and Padova City Hospital, Padova, Italy
| | - Gioele Castelli
- Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova and Padova City Hospital, Padova, Italy
| | - Francesco Onelia
- Department of Molecular Medicine, University of Padova and Padova City Hospital, Padova, Italy
| | - Enrico Lavezzo
- Department of Molecular Medicine, University of Padova and Padova City Hospital, Padova, Italy
| | - Chiara Giraudo
- Department of Medicine, Institute of Radiology, University of Padova and Padova City Hospital, Padova, Italy
| | - Nicol Bernardinello
- Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova and Padova City Hospital, Padova, Italy
| | - Giulia Fichera
- Department of Medicine, Institute of Radiology, University of Padova and Padova City Hospital, Padova, Italy
| | - Davide Leoni
- Division of Infectious and Tropical Diseases, University of Padova and Padova City Hospital, Padova, Italy
| | - Marco Trevenzoli
- Division of Infectious and Tropical Diseases, University of Padova and Padova City Hospital, Padova, Italy
| | - Marina Saetta
- Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova and Padova City Hospital, Padova, Italy
| | - Annamaria Cattelan
- Division of Infectious and Tropical Diseases, University of Padova and Padova City Hospital, Padova, Italy
| | - Andrea Crisanti
- Department of Molecular Medicine, University of Padova and Padova City Hospital, Padova, Italy
| | - Paolo Spagnolo
- Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova and Padova City Hospital, Padova, Italy
| | - Elisabetta Balestro
- Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova and Padova City Hospital, Padova, Italy
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10
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Dorigatti I, Lavezzo E, Manuto L, Ciavarella C, Pacenti M, Boldrin C, Cattai M, Saluzzo F, Franchin E, Del Vecchio C, Caldart F, Castelli G, Nicoletti M, Nieddu E, Salvadoretti E, Labella B, Fava L, Guglielmo S, Fascina M, Grazioli M, Alvisi G, Vanuzzo MC, Zupo T, Calandrin R, Lisi V, Rossi L, Castagliuolo I, Merigliano S, Unwin HJT, Plebani M, Padoan A, Brazzale AR, Toppo S, Ferguson NM, Donnelly CA, Crisanti A. SARS-CoV-2 antibody dynamics and transmission from community-wide serological testing in the Italian municipality of Vo'. Nat Commun 2021; 12:4383. [PMID: 34282139 PMCID: PMC8289856 DOI: 10.1038/s41467-021-24622-7] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Accepted: 06/21/2021] [Indexed: 01/04/2023] Open
Abstract
In February and March 2020, two mass swab testing campaigns were conducted in Vo', Italy. In May 2020, we tested 86% of the Vo' population with three immuno-assays detecting antibodies against the spike and nucleocapsid antigens, a neutralisation assay and Polymerase Chain Reaction (PCR). Subjects testing positive to PCR in February/March or a serological assay in May were tested again in November. Here we report on the results of the analysis of the May and November surveys. We estimate a seroprevalence of 3.5% (95% Credible Interval (CrI): 2.8-4.3%) in May. In November, 98.8% (95% Confidence Interval (CI): 93.7-100.0%) of sera which tested positive in May still reacted against at least one antigen; 18.6% (95% CI: 11.0-28.5%) showed an increase of antibody or neutralisation reactivity from May. Analysis of the serostatus of the members of 1,118 households indicates a 26.0% (95% CrI: 17.2-36.9%) Susceptible-Infectious Transmission Probability. Contact tracing had limited impact on epidemic suppression.
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Affiliation(s)
- Ilaria Dorigatti
- MRC Centre for Global Infectious Disease Analysis and the Abdul Latif Jameel Institute for Disease and Emergency Analytics, School of Public Health, Imperial College London, London, UK.
| | - Enrico Lavezzo
- Department of Molecular Medicine, University of Padova, Padova, Italy.
| | - Laura Manuto
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Constanze Ciavarella
- MRC Centre for Global Infectious Disease Analysis and the Abdul Latif Jameel Institute for Disease and Emergency Analytics, School of Public Health, Imperial College London, London, UK
| | | | | | | | - Francesca Saluzzo
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Elisa Franchin
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | | | - Federico Caldart
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Gioele Castelli
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Michele Nicoletti
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Eleonora Nieddu
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | | | - Beatrice Labella
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Ludovico Fava
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Simone Guglielmo
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | | | - Marco Grazioli
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Gualtiero Alvisi
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | | | | | | | | | | | | | - Stefano Merigliano
- Department of Surgery, Oncology and Gastroenterology, University of Padova, Padova, Italy
| | - H Juliette T Unwin
- MRC Centre for Global Infectious Disease Analysis and the Abdul Latif Jameel Institute for Disease and Emergency Analytics, School of Public Health, Imperial College London, London, UK
| | - Mario Plebani
- Department of Medicine, University of Padova, Padova, Italy
| | - Andrea Padoan
- Department of Medicine, University of Padova, Padova, Italy
| | | | - Stefano Toppo
- Department of Molecular Medicine, University of Padova, Padova, Italy
- CRIBI Biotech Centre, University of Padova, Padova, Italy
| | - Neil M Ferguson
- MRC Centre for Global Infectious Disease Analysis and the Abdul Latif Jameel Institute for Disease and Emergency Analytics, School of Public Health, Imperial College London, London, UK
| | - Christl A Donnelly
- MRC Centre for Global Infectious Disease Analysis and the Abdul Latif Jameel Institute for Disease and Emergency Analytics, School of Public Health, Imperial College London, London, UK
- Department of Statistics, University of Oxford, Oxford, UK
| | - Andrea Crisanti
- Department of Molecular Medicine, University of Padova, Padova, Italy.
- Azienda Ospedale Padova, Padova, Italy.
- Department of Life Science Imperial College London, Exhibition Road, London, UK.
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11
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Tangaro M, Defazio G, Fosso B, Licciulli VF, Grillo G, Donvito G, Lavezzo E, Baruzzo G, Pesole G, Santamaria M. ITSoneWB: profiling global taxonomic diversity of eukaryotic communities on Galaxy. Bioinformatics 2021; 37:4253-4254. [PMID: 34117876 PMCID: PMC9502156 DOI: 10.1093/bioinformatics/btab431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 06/03/2021] [Accepted: 06/11/2021] [Indexed: 12/05/2022] Open
Abstract
Summary ITSoneWB (ITSone WorkBench) is a Galaxy-based bioinformatic environment where comprehensive and high-quality reference data are connected with established pipelines and new tools in an automated and easy-to-use service targeted at global taxonomic analysis of eukaryotic communities based on Internal Transcribed Spacer 1 variants high-throughput sequencing. Availability and implementation ITSoneWB has been deployed on the INFN-Bari ReCaS cloud facility and is freely available on the web at http://itsonewb.cloud.ba.infn.it/galaxy. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Marco Tangaro
- Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council, Bari 70126, Italy
| | - Giuseppe Defazio
- Department of Biosciences, Biotechnology and Biopharmaceutics, University of Bari 'A. Moro', Bari 70126, Italy
| | - Bruno Fosso
- Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council, Bari 70126, Italy
| | - Vito Flavio Licciulli
- Institute of Biomedical Technologies, National Research Council, Bari Unit, 70126 Bari, Italy
| | - Giorgio Grillo
- Institute of Biomedical Technologies, National Research Council, Bari Unit, 70126 Bari, Italy
| | - Giacinto Donvito
- National Institute for Nuclear Physics (INFN), Section of Bari, Bari 70126, Italy
| | - Enrico Lavezzo
- Department of Molecular Medicine, University of Padova, Padova 35131, Italy
| | - Giacomo Baruzzo
- Department of Information Engineering, University of Padova, Padova, 35131, Italy
| | - Graziano Pesole
- Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council, Bari 70126, Italy.,Department of Biosciences, Biotechnology and Biopharmaceutics, University of Bari 'A. Moro', Bari 70126, Italy
| | - Monica Santamaria
- Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council, Bari 70126, Italy
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12
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Lavezzo E, Franchin E, Ciavarella C, Cuomo-Dannenburg G, Barzon L, Del Vecchio C, Rossi L, Manganelli R, Loregian A, Navarin N, Abate D, Sciro M, Merigliano S, De Canale E, Vanuzzo MC, Besutti V, Saluzzo F, Onelia F, Pacenti M, Parisi SG, Carretta G, Donato D, Flor L, Cocchio S, Masi G, Sperduti A, Cattarino L, Salvador R, Nicoletti M, Caldart F, Castelli G, Nieddu E, Labella B, Fava L, Drigo M, Gaythorpe KAM, Brazzale AR, Toppo S, Trevisan M, Baldo V, Donnelly CA, Ferguson NM, Dorigatti I, Crisanti A. Author Correction: Suppression of a SARS-CoV-2 outbreak in the Italian municipality of Vo'. Nature 2021; 590:E11. [PMID: 33452443 PMCID: PMC7810098 DOI: 10.1038/s41586-020-2956-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Affiliation(s)
- Enrico Lavezzo
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | - Elisa Franchin
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | - Constanze Ciavarella
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Gina Cuomo-Dannenburg
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Luisa Barzon
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | | | | | | | - Arianna Loregian
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | - Nicolò Navarin
- Department of Mathematics "Tullio Levi-Civita", University of Padova, Padua, Italy
- CRIBI Biotech Center, University of Padova, Padua, Italy
| | - Davide Abate
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | | | - Stefano Merigliano
- Department of Surgery, Oncology and Gastroenterology, University of Padova, Padua, Italy
| | | | | | | | - Francesca Saluzzo
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | - Francesco Onelia
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | | | - Saverio G Parisi
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | | | | | | | - Silvia Cocchio
- Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Padua, Italy
| | - Giulia Masi
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | - Alessandro Sperduti
- Department of Mathematics "Tullio Levi-Civita", University of Padova, Padua, Italy
- CRIBI Biotech Center, University of Padova, Padua, Italy
| | - Lorenzo Cattarino
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Renato Salvador
- Department of Surgery, Oncology and Gastroenterology, University of Padova, Padua, Italy
| | | | | | | | | | | | - Ludovico Fava
- School of Medicine, University of Padova, Padua, Italy
| | - Matteo Drigo
- School of Medicine, University of Padova, Padua, Italy
| | - Katy A M Gaythorpe
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | | | - Stefano Toppo
- Department of Molecular Medicine, University of Padova, Padua, Italy
- CRIBI Biotech Center, University of Padova, Padua, Italy
| | - Marta Trevisan
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | - Vincenzo Baldo
- Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Padua, Italy
| | - Christl A Donnelly
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
- Department of Statistics, University of Oxford, Oxford, UK
| | - Neil M Ferguson
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Ilaria Dorigatti
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK.
| | - Andrea Crisanti
- Department of Molecular Medicine, University of Padova, Padua, Italy.
- Department of Life Sciences, Imperial College London, London, UK.
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13
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Berselli M, Lavezzo E, Toppo S. QPARSE: searching for long-looped or multimeric G-quadruplexes potentially distinctive and druggable. Bioinformatics 2020; 36:393-399. [PMID: 31328780 DOI: 10.1093/bioinformatics/btz569] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2019] [Revised: 06/04/2019] [Accepted: 07/16/2019] [Indexed: 11/14/2022] Open
Abstract
MOTIVATION G-quadruplexes (G4s) are non-canonical nucleic acid conformations that are widespread in all kingdoms of life and are emerging as important regulators both in RNA and DNA. Recently, two new higher-order architectures have been reported: adjacent interacting G4s and G4s with stable long loops forming stem-loop structures. As there are no specialized tools to identify these conformations, we developed QPARSE. RESULTS QPARSE can exhaustively search for degenerate potential quadruplex-forming sequences (PQSs) containing bulges and/or mismatches at genomic level, as well as either multimeric or long-looped PQS (MPQS and LLPQS, respectively). While its assessment versus known reference datasets is comparable with the state-of-the-art, what is more interesting is its performance in the identification of MPQS and LLPQS that present algorithms are not designed to search for. We report a comprehensive analysis of MPQS in human gene promoters and the analysis of LLPQS on three experimentally validated case studies from HIV-1, BCL2 and hTERT. AVAILABILITY AND IMPLEMENTATION QPARSE is freely accessible on the web at http://www.medcomp.medicina.unipd.it/qparse/index or downloadable from github as a python 2.7 program https://github.com/B3rse/qparse. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Michele Berselli
- Department of Molecular Medicine, University of Padova, Padova I-35131, Italy
| | - Enrico Lavezzo
- Department of Molecular Medicine, University of Padova, Padova I-35131, Italy
| | - Stefano Toppo
- Department of Molecular Medicine, University of Padova, Padova I-35131, Italy.,CRIBI Biotech Centre, University of Padova, Padova I-35131, Italy
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14
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Lavezzo E, Franchin E, Ciavarella C, Cuomo-Dannenburg G, Barzon L, Del Vecchio C, Rossi L, Manganelli R, Loregian A, Navarin N, Abate D, Sciro M, Merigliano S, De Canale E, Vanuzzo MC, Besutti V, Saluzzo F, Onelia F, Pacenti M, Parisi SG, Carretta G, Donato D, Flor L, Cocchio S, Masi G, Sperduti A, Cattarino L, Salvador R, Nicoletti M, Caldart F, Castelli G, Nieddu E, Labella B, Fava L, Drigo M, Gaythorpe KAM, Brazzale AR, Toppo S, Trevisan M, Baldo V, Donnelly CA, Ferguson NM, Dorigatti I, Crisanti A. Suppression of a SARS-CoV-2 outbreak in the Italian municipality of Vo'. Nature 2020; 584:425-429. [PMID: 32604404 DOI: 10.1038/s41586-020-2488-1] [Citation(s) in RCA: 623] [Impact Index Per Article: 155.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Accepted: 06/23/2020] [Indexed: 01/12/2023]
Abstract
On 21 February 2020, a resident of the municipality of Vo', a small town near Padua (Italy), died of pneumonia due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection1. This was the first coronavirus disease 19 (COVID-19)-related death detected in Italy since the detection of SARS-CoV-2 in the Chinese city of Wuhan, Hubei province2. In response, the regional authorities imposed the lockdown of the whole municipality for 14 days3. Here we collected information on the demography, clinical presentation, hospitalization, contact network and the presence of SARS-CoV-2 infection in nasopharyngeal swabs for 85.9% and 71.5% of the population of Vo' at two consecutive time points. From the first survey, which was conducted around the time the town lockdown started, we found a prevalence of infection of 2.6% (95% confidence interval (CI): 2.1-3.3%). From the second survey, which was conducted at the end of the lockdown, we found a prevalence of 1.2% (95% CI: 0.8-1.8%). Notably, 42.5% (95% CI: 31.5-54.6%) of the confirmed SARS-CoV-2 infections detected across the two surveys were asymptomatic (that is, did not have symptoms at the time of swab testing and did not develop symptoms afterwards). The mean serial interval was 7.2 days (95% CI: 5.9-9.6). We found no statistically significant difference in the viral load of symptomatic versus asymptomatic infections (P = 0.62 and 0.74 for E and RdRp genes, respectively, exact Wilcoxon-Mann-Whitney test). This study sheds light on the frequency of asymptomatic SARS-CoV-2 infection, their infectivity (as measured by the viral load) and provides insights into its transmission dynamics and the efficacy of the implemented control measures.
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Affiliation(s)
- Enrico Lavezzo
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | - Elisa Franchin
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | - Constanze Ciavarella
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Gina Cuomo-Dannenburg
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Luisa Barzon
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | | | | | | | - Arianna Loregian
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | - Nicolò Navarin
- Department of Mathematics "Tullio Levi-Civita", University of Padova, Padua, Italy
- CRIBI Biotech Center, University of Padova, Padua, Italy
| | - Davide Abate
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | | | - Stefano Merigliano
- Department of Surgery, Oncology and Gastroenterology, University of Padova, Padua, Italy
| | | | | | | | - Francesca Saluzzo
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | - Francesco Onelia
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | | | - Saverio G Parisi
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | | | | | | | - Silvia Cocchio
- Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Padua, Italy
| | - Giulia Masi
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | - Alessandro Sperduti
- Department of Mathematics "Tullio Levi-Civita", University of Padova, Padua, Italy
- CRIBI Biotech Center, University of Padova, Padua, Italy
| | - Lorenzo Cattarino
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Renato Salvador
- Department of Surgery, Oncology and Gastroenterology, University of Padova, Padua, Italy
| | | | | | | | | | | | - Ludovico Fava
- School of Medicine, University of Padova, Padua, Italy
| | - Matteo Drigo
- School of Medicine, University of Padova, Padua, Italy
| | - Katy A M Gaythorpe
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | | | | | - Stefano Toppo
- Department of Molecular Medicine, University of Padova, Padua, Italy
- CRIBI Biotech Center, University of Padova, Padua, Italy
| | - Marta Trevisan
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | - Vincenzo Baldo
- Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Padua, Italy
| | - Christl A Donnelly
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
- Department of Statistics, University of Oxford, Oxford, UK
| | - Neil M Ferguson
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Ilaria Dorigatti
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK.
| | - Andrea Crisanti
- Department of Molecular Medicine, University of Padova, Padua, Italy.
- Department of Life Sciences, Imperial College London, London, UK.
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15
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Lavezzo E, Franchin E, Ciavarella C, Cuomo-Dannenburg G, Barzon L, Del Vecchio C, Rossi L, Manganelli R, Loregian A, Navarin N, Abate D, Sciro M, Merigliano S, De Canale E, Vanuzzo MC, Besutti V, Saluzzo F, Onelia F, Pacenti M, Parisi SG, Carretta G, Donato D, Flor L, Cocchio S, Masi G, Sperduti A, Cattarino L, Salvador R, Nicoletti M, Caldart F, Castelli G, Nieddu E, Labella B, Fava L, Drigo M, Gaythorpe KAM, Brazzale AR, Toppo S, Trevisan M, Baldo V, Donnelly CA, Ferguson NM, Dorigatti I, Crisanti A. Suppression of a SARS-CoV-2 outbreak in the Italian municipality of Vo'. Nature 2020. [PMID: 32604404 DOI: 10.1101/2020.04.17.20053157] [Citation(s) in RCA: 78] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
On 21 February 2020, a resident of the municipality of Vo', a small town near Padua (Italy), died of pneumonia due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection1. This was the first coronavirus disease 19 (COVID-19)-related death detected in Italy since the detection of SARS-CoV-2 in the Chinese city of Wuhan, Hubei province2. In response, the regional authorities imposed the lockdown of the whole municipality for 14 days3. Here we collected information on the demography, clinical presentation, hospitalization, contact network and the presence of SARS-CoV-2 infection in nasopharyngeal swabs for 85.9% and 71.5% of the population of Vo' at two consecutive time points. From the first survey, which was conducted around the time the town lockdown started, we found a prevalence of infection of 2.6% (95% confidence interval (CI): 2.1-3.3%). From the second survey, which was conducted at the end of the lockdown, we found a prevalence of 1.2% (95% CI: 0.8-1.8%). Notably, 42.5% (95% CI: 31.5-54.6%) of the confirmed SARS-CoV-2 infections detected across the two surveys were asymptomatic (that is, did not have symptoms at the time of swab testing and did not develop symptoms afterwards). The mean serial interval was 7.2 days (95% CI: 5.9-9.6). We found no statistically significant difference in the viral load of symptomatic versus asymptomatic infections (P = 0.62 and 0.74 for E and RdRp genes, respectively, exact Wilcoxon-Mann-Whitney test). This study sheds light on the frequency of asymptomatic SARS-CoV-2 infection, their infectivity (as measured by the viral load) and provides insights into its transmission dynamics and the efficacy of the implemented control measures.
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Affiliation(s)
- Enrico Lavezzo
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | - Elisa Franchin
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | - Constanze Ciavarella
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Gina Cuomo-Dannenburg
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Luisa Barzon
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | | | | | | | - Arianna Loregian
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | - Nicolò Navarin
- Department of Mathematics "Tullio Levi-Civita", University of Padova, Padua, Italy
- CRIBI Biotech Center, University of Padova, Padua, Italy
| | - Davide Abate
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | | | - Stefano Merigliano
- Department of Surgery, Oncology and Gastroenterology, University of Padova, Padua, Italy
| | | | | | | | - Francesca Saluzzo
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | - Francesco Onelia
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | | | - Saverio G Parisi
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | | | | | | | - Silvia Cocchio
- Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Padua, Italy
| | - Giulia Masi
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | - Alessandro Sperduti
- Department of Mathematics "Tullio Levi-Civita", University of Padova, Padua, Italy
- CRIBI Biotech Center, University of Padova, Padua, Italy
| | - Lorenzo Cattarino
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Renato Salvador
- Department of Surgery, Oncology and Gastroenterology, University of Padova, Padua, Italy
| | | | | | | | | | | | - Ludovico Fava
- School of Medicine, University of Padova, Padua, Italy
| | - Matteo Drigo
- School of Medicine, University of Padova, Padua, Italy
| | - Katy A M Gaythorpe
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | | | - Stefano Toppo
- Department of Molecular Medicine, University of Padova, Padua, Italy
- CRIBI Biotech Center, University of Padova, Padua, Italy
| | - Marta Trevisan
- Department of Molecular Medicine, University of Padova, Padua, Italy
| | - Vincenzo Baldo
- Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Padua, Italy
| | - Christl A Donnelly
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
- Department of Statistics, University of Oxford, Oxford, UK
| | - Neil M Ferguson
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Ilaria Dorigatti
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK.
| | - Andrea Crisanti
- Department of Molecular Medicine, University of Padova, Padua, Italy.
- Department of Life Sciences, Imperial College London, London, UK.
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16
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Pacenti M, Sinigaglia A, Franchin E, Pagni S, Lavezzo E, Montarsi F, Capelli G, Barzon L. Human West Nile Virus Lineage 2 Infection: Epidemiological, Clinical, and Virological Findings. Viruses 2020; 12:v12040458. [PMID: 32325716 PMCID: PMC7232435 DOI: 10.3390/v12040458] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2020] [Revised: 04/08/2020] [Accepted: 04/16/2020] [Indexed: 11/30/2022] Open
Abstract
West Nile virus (WNV) lineage 2 is expanding and causing large outbreaks in Europe. In this study, we analyzed the epidemiological, clinical, and virological features of WNV lineage 2 infection during the large outbreak that occurred in northern Italy in 2018. The study population included 86 patients with neuroinvasive disease (WNND), 307 with fever (WNF), and 34 blood donors. Phylogenetic analysis of WNV full genome sequences from patients’ samples showed that the virus belonged to the widespread central/southern European clade of WNV lineage 2 and was circulating in the area at least since 2014. The incidence of WNND and WNF progressively increased with age and was higher in males than in females. Among WNND patients, the case fatality rate was 22%. About 70% of blood donors reported symptoms during follow-up. Within the first week after symptom onset, WNV RNA was detectable in the blood or urine of 80% of patients, while 20% and 40% of WNND and WNF patients, respectively, were WNV IgM-seronegative. In CSF samples of WNND patients, WNV RNA was typically detectable when WNV IgM antibodies were absent. Blunted or no WNV IgM response and high WNV IgG levels were observed in seven patients with previous flavivirus immunity.
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Affiliation(s)
- Monia Pacenti
- Microbiology and Virology Unit, Padova University Hospital, I-35128 Padova, Italy; (M.P.); (E.F.); (S.P.)
| | - Alessandro Sinigaglia
- Department of Molecular Medicine, University of Padova, I-35121 Padova, Italy; (A.S.); (E.L.)
| | - Elisa Franchin
- Microbiology and Virology Unit, Padova University Hospital, I-35128 Padova, Italy; (M.P.); (E.F.); (S.P.)
- Department of Molecular Medicine, University of Padova, I-35121 Padova, Italy; (A.S.); (E.L.)
| | - Silvana Pagni
- Microbiology and Virology Unit, Padova University Hospital, I-35128 Padova, Italy; (M.P.); (E.F.); (S.P.)
- Department of Molecular Medicine, University of Padova, I-35121 Padova, Italy; (A.S.); (E.L.)
| | - Enrico Lavezzo
- Department of Molecular Medicine, University of Padova, I-35121 Padova, Italy; (A.S.); (E.L.)
| | - Fabrizio Montarsi
- Istituto Zooprofilattico Sperimentale delle Venezie, I-35020 Legnaro PD, Italy; (F.M.); (G.C.)
| | - Gioia Capelli
- Istituto Zooprofilattico Sperimentale delle Venezie, I-35020 Legnaro PD, Italy; (F.M.); (G.C.)
| | - Luisa Barzon
- Microbiology and Virology Unit, Padova University Hospital, I-35128 Padova, Italy; (M.P.); (E.F.); (S.P.)
- Department of Molecular Medicine, University of Padova, I-35121 Padova, Italy; (A.S.); (E.L.)
- Correspondence: ; Tel.: +39-049-8218946
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17
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Pacenti M, Maione N, Lavezzo E, Franchin E, Dal Bello F, Gottardello L, Barzon L. Measles Virus Infection and Immunity in a Suboptimal Vaccination Coverage Setting. Vaccines (Basel) 2019; 7:vaccines7040199. [PMID: 31795157 PMCID: PMC6963570 DOI: 10.3390/vaccines7040199] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2019] [Revised: 11/23/2019] [Accepted: 11/26/2019] [Indexed: 11/24/2022] Open
Abstract
Despite efforts to improve surveillance and vaccination coverage, measles virus (MeV) continues to cause outbreaks also in high-income countries. As the reference laboratory of the Veneto Region, Italy, we analyzed changes in population immunity, described measles outbreaks, investigated MeV genetic diversity, and evaluated cross-protection of measles vaccination against MeV epidemic strains. Like most European areas, the Veneto Region has suboptimal measles vaccination coverage and is facing a growing public mistrust of vaccination. A progressive decline of measles vaccine uptake was observed during the last decade in the Veneto Region, leading to immunity gaps in children and young adults. Measles outbreaks were caused by the same MeV genotype B3, D4, and D8 strains that were circulating in other European countries. Eleven cases of measles were observed in immunized subjects. These cases were not associated with particular MeV genotypes nor with mutations in epitopes recognized by neutralizing antibodies. Accordingly, sera from fully vaccinated subjects cross-neutralized epidemic MeV strains, including the genotypes B3, D4, and D8, with the same high efficiency demonstrated against the vaccine strain. In fully vaccinated subjects, high MeV IgG antibody titers persisted up to 30 years following vaccination. These results support the use of the current measles-containing vaccines and strategies to strengthen vaccination.
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Affiliation(s)
- Monia Pacenti
- Microbiology and Virology Unit, Padova University Hospital, 35128 Padova, Italy; (M.P.); (E.F.); (F.D.B.)
| | - Nataskya Maione
- Department of Molecular Medicine, University of Padova, 35121 Padova, Italy; (N.M.); (E.L.)
| | - Enrico Lavezzo
- Department of Molecular Medicine, University of Padova, 35121 Padova, Italy; (N.M.); (E.L.)
| | - Elisa Franchin
- Microbiology and Virology Unit, Padova University Hospital, 35128 Padova, Italy; (M.P.); (E.F.); (F.D.B.)
- Department of Molecular Medicine, University of Padova, 35121 Padova, Italy; (N.M.); (E.L.)
| | - Federico Dal Bello
- Microbiology and Virology Unit, Padova University Hospital, 35128 Padova, Italy; (M.P.); (E.F.); (F.D.B.)
- Department of Molecular Medicine, University of Padova, 35121 Padova, Italy; (N.M.); (E.L.)
| | - Lorena Gottardello
- Department of Hygiene and Public Health, Azienda ULSS 6 Euganea, 35131 Padova, Italy;
| | - Luisa Barzon
- Microbiology and Virology Unit, Padova University Hospital, 35128 Padova, Italy; (M.P.); (E.F.); (F.D.B.)
- Department of Molecular Medicine, University of Padova, 35121 Padova, Italy; (N.M.); (E.L.)
- Correspondence: ; Tel.: +39-049-821-8946
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18
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Zhou N, Jiang Y, Bergquist TR, Lee AJ, Kacsoh BZ, Crocker AW, Lewis KA, Georghiou G, Nguyen HN, Hamid MN, Davis L, Dogan T, Atalay V, Rifaioglu AS, Dalkıran A, Cetin Atalay R, Zhang C, Hurto RL, Freddolino PL, Zhang Y, Bhat P, Supek F, Fernández JM, Gemovic B, Perovic VR, Davidović RS, Sumonja N, Veljkovic N, Asgari E, Mofrad MRK, Profiti G, Savojardo C, Martelli PL, Casadio R, Boecker F, Schoof H, Kahanda I, Thurlby N, McHardy AC, Renaux A, Saidi R, Gough J, Freitas AA, Antczak M, Fabris F, Wass MN, Hou J, Cheng J, Wang Z, Romero AE, Paccanaro A, Yang H, Goldberg T, Zhao C, Holm L, Törönen P, Medlar AJ, Zosa E, Borukhov I, Novikov I, Wilkins A, Lichtarge O, Chi PH, Tseng WC, Linial M, Rose PW, Dessimoz C, Vidulin V, Dzeroski S, Sillitoe I, Das S, Lees JG, Jones DT, Wan C, Cozzetto D, Fa R, Torres M, Warwick Vesztrocy A, Rodriguez JM, Tress ML, Frasca M, Notaro M, Grossi G, Petrini A, Re M, Valentini G, Mesiti M, Roche DB, Reeb J, Ritchie DW, Aridhi S, Alborzi SZ, Devignes MD, Koo DCE, Bonneau R, Gligorijević V, Barot M, Fang H, Toppo S, Lavezzo E, Falda M, Berselli M, Tosatto SCE, Carraro M, Piovesan D, Ur Rehman H, Mao Q, Zhang S, Vucetic S, Black GS, Jo D, Suh E, Dayton JB, Larsen DJ, Omdahl AR, McGuffin LJ, Brackenridge DA, Babbitt PC, Yunes JM, Fontana P, Zhang F, Zhu S, You R, Zhang Z, Dai S, Yao S, Tian W, Cao R, Chandler C, Amezola M, Johnson D, Chang JM, Liao WH, Liu YW, Pascarelli S, Frank Y, Hoehndorf R, Kulmanov M, Boudellioua I, Politano G, Di Carlo S, Benso A, Hakala K, Ginter F, Mehryary F, Kaewphan S, Björne J, Moen H, Tolvanen MEE, Salakoski T, Kihara D, Jain A, Šmuc T, Altenhoff A, Ben-Hur A, Rost B, Brenner SE, Orengo CA, Jeffery CJ, Bosco G, Hogan DA, Martin MJ, O'Donovan C, Mooney SD, Greene CS, Radivojac P, Friedberg I. The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens. Genome Biol 2019; 20:244. [PMID: 31744546 PMCID: PMC6864930 DOI: 10.1186/s13059-019-1835-8] [Citation(s) in RCA: 166] [Impact Index Per Article: 33.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2019] [Accepted: 09/24/2019] [Indexed: 12/23/2022] Open
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.
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Affiliation(s)
- Naihui Zhou
- Veterinary Microbiology and Preventive Medicine, Iowa State University, Ames, IA, USA.,Program in Bioinformatics and Computational Biology, Ames, IA, USA
| | - Yuxiang Jiang
- Indiana University Bloomington, Bloomington, Indiana, USA
| | - Timothy R Bergquist
- Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA
| | - Alexandra J Lee
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, PA, USA
| | - Balint Z Kacsoh
- Geisel School of Medicine at Dartmouth, Hanover, NH, USA.,Department of Molecular and Systems Biology, Hanover, NH, USA
| | - Alex W Crocker
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA
| | - Kimberley A Lewis
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA
| | - George Georghiou
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, United Kingdom
| | - Huy N Nguyen
- Veterinary Microbiology and Preventive Medicine, Iowa State University, Ames, IA, USA.,Program in Computer Science, Ames, IA, USA
| | - Md Nafiz Hamid
- Veterinary Microbiology and Preventive Medicine, Iowa State University, Ames, IA, USA.,Program in Bioinformatics and Computational Biology, Ames, IA, USA
| | - Larry Davis
- Program in Bioinformatics and Computational Biology, Ames, IA, USA
| | - Tunca Dogan
- Department of Computer Engineering, Hacettepe University, Ankara, Turkey.,European Molecular Biolo gy Labora tory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK
| | - Volkan Atalay
- Department of Computer Engineering, Middle East Technical University (METU), Ankara, Turkey
| | - Ahmet S Rifaioglu
- Department of Computer Engineering, Middle East Technical University (METU), Ankara, Turkey.,Department of Computer Engineering, Iskenderun Technical University, Hatay, Turkey
| | - Alperen Dalkıran
- Department of Computer Engineering, Middle East Technical University (METU), Ankara, Turkey
| | - Rengul Cetin Atalay
- CanSyL, Graduate School of Informatics, Middle East Technical University, Ankara, Turkey
| | - Chengxin Zhang
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Rebecca L Hurto
- Department of Biological Chemistry, University of Michigan, Ann Arbor, MI, USA
| | - Peter L Freddolino
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.,Department of Biological Chemistry, University of Michigan, Ann Arbor, MI, USA
| | - Yang Zhang
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.,Department of Biological Chemistry, University of Michigan, Ann Arbor, MI, USA
| | | | - Fran Supek
- Institute for Research in Biomedicine (IRB Barcelona), Barcelona, Spain.,Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - José M Fernández
- INB Coordination Unit, Life Sciences Department, Barcelona Supercomputing Center, Barcelona, Catalonia, Spain.,(former) INB GN2, Structural and Computational Biology Programme, Spanish National Cancer Research Centre, Barcelona, Catalonia, Spain
| | - Branislava Gemovic
- Laboratory for Bioinformatics and Computational Chemistry, Institute of Nuclear Sciences VINCA, University of Belgrade, Belgrade, Serbia
| | - Vladimir R Perovic
- Laboratory for Bioinformatics and Computational Chemistry, Institute of Nuclear Sciences VINCA, University of Belgrade, Belgrade, Serbia
| | - Radoslav S Davidović
- Laboratory for Bioinformatics and Computational Chemistry, Institute of Nuclear Sciences VINCA, University of Belgrade, Belgrade, Serbia
| | - Neven Sumonja
- Laboratory for Bioinformatics and Computational Chemistry, Institute of Nuclear Sciences VINCA, University of Belgrade, Belgrade, Serbia
| | - Nevena Veljkovic
- Laboratory for Bioinformatics and Computational Chemistry, Institute of Nuclear Sciences VINCA, University of Belgrade, Belgrade, Serbia
| | - Ehsaneddin Asgari
- Molecular Cell Biomechanics Laboratory, Departments of Bioengineering, University of California Berkeley, Berkeley, CA, USA.,Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Berkeley, CA, USA
| | | | - Giuseppe Profiti
- Bologna Biocomputing Group, Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy.,National Research Council, IBIOM, Bologna, Italy
| | - Castrense Savojardo
- Bologna Biocomputing Group, Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy
| | - Pier Luigi Martelli
- Bologna Biocomputing Group, Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy
| | - Rita Casadio
- Bologna Biocomputing Group, Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy
| | - Florian Boecker
- University of Bonn: INRES Crop Bioinformatics, Bonn, North Rhine-Westphalia, Germany
| | - Heiko Schoof
- INRES Crop Bioinformatics, University of Bonn, Bonn, Germany
| | - Indika Kahanda
- Gianforte School of Computing, Montana State University, Bozeman, Montana, USA
| | - Natalie Thurlby
- University of Bristol, Computer Science, Bristol, Bristol, United Kingdom
| | - Alice C McHardy
- Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Brunswick, Germany.,RESIST, DFG Cluster of Excellence 2155, Brunswick, Germany
| | - Alexandre Renaux
- Interuniversity Institute of Bioinformatics in Brussels, Université libre de Bruxelles - Vrije Universiteit Brussel, Brussels, Belgium.,Machine Learning Group, Université libre de Bruxelles, Brussels, Belgium.,Artificial Intelligence lab, Vrije Universiteit Brussel, Brussels, Belgium
| | - Rabie Saidi
- European Molecular Biolo gy Labora tory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK
| | - Julian Gough
- MRC Laboratory of Molecular Biology, Cambridge, United Kingdom
| | - Alex A Freitas
- University of Kent, School of Computing, Canterbury, United Kingdom
| | - Magdalena Antczak
- School of Biosciences, University of Kent, Canterbury, Kent, United Kingdom
| | - Fabio Fabris
- University of Kent, School of Computing, Canterbury, United Kingdom
| | - Mark N Wass
- School of Biosciences, University of Kent, Canterbury, Kent, United Kingdom
| | - Jie Hou
- University of Missouri, Computer Science, Columbia, Missouri, USA.,Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA
| | - Jianlin Cheng
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA
| | - Zheng Wang
- University of Miami, Coral Gables, Florida, USA
| | - Alfonso E Romero
- Centre for Systems and Synthetic Biology, Department of Computer Science, Royal Holloway, University of London, Egham, Surrey, United Kingdom
| | - Alberto Paccanaro
- Centre for Systems and Synthetic Biology, Department of Computer Science, Royal Holloway, University of London, Egham, Surrey, United Kingdom
| | - Haixuan Yang
- School of Mathematics, Statistics and Applied Mathematics, National University of Ireland, Galway, Galway, Ireland.,Technical University of Munich, Garching, Germany
| | - Tatyana Goldberg
- Department of Informatics, Bioinformatics & Computational Biology-i12, Technische Universitat Munchen, Munich, Germany
| | - Chenguang Zhao
- Faculty for Informatics, Garching, Germany.,Department for Bioinformatics and Computational Biology, Garching, Germany.,School of Computing Sciences and Computer Engineering, Hattiesburg, Mississippi, USA
| | - Liisa Holm
- Institute of Biotechnology, Helsinki Institute of Life Sciences, University of Helsinki, Finland, Helsinki, Finland
| | - Petri Törönen
- Institute of Biotechnology, Helsinki Institute of Life Sciences, University of Helsinki, Finland, Helsinki, Finland
| | - Alan J Medlar
- Institute of Biotechnology, Helsinki Institute of Life Sciences, University of Helsinki, Finland, Helsinki, Finland
| | - Elaine Zosa
- Institute of Biotechnology, University of Helsinki, Helsinki, Finland
| | | | - Ilya Novikov
- Baylor College of Medicine, Department of Biochemistry and Molecular Biology, Houston, TX, USA
| | - Angela Wilkins
- Baylor College of Medicine, Department of Molecular and Human Genetics, Houston, TX, USA
| | - Olivier Lichtarge
- Baylor College of Medicine, Department of Molecular and Human Genetics, Houston, TX, USA
| | - Po-Han Chi
- National TsingHua University, Hsinchu, Taiwan
| | - Wei-Cheng Tseng
- Department of Electrical Engineering in National Tsing Hua University, Hsinchu City, Taiwan
| | - Michal Linial
- The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Peter W Rose
- University of California San Diego, San Diego Supercomputer Center, La Jolla, California, USA
| | - Christophe Dessimoz
- Department of Computational Biology and Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland.,Department of Genetics, Evolution & Environment, and Department of Computer Science, University College London, London, UK.,Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Vedrana Vidulin
- Department of Knowledge Technologies, Jozef Stefan Institute, Ljubljana, Slovenia
| | - Saso Dzeroski
- Jozef Stefan Institute, Ljubljana, Slovenia.,Jozef Stefan International Postgraduate School, Ljubljana, Slovenia
| | - Ian Sillitoe
- Research Department of Structural and Molecular Biology, University College London, London, England
| | - Sayoni Das
- Research Department of Structural and Molecular Biology, University College London, London, United Kingdom
| | - Jonathan Gill Lees
- Research Department of Structural and Molecular Biology, University College London, London, United Kingdom.,Department of Health and Life Sciences, Oxford Brookes University, London, UK
| | - David T Jones
- The Francis Crick Institute, Biomedical Data Science Laboratory, London, United Kingdom.,Department of Genetics, Evolution and Environment, University College London, Gower Street, London, WC1E 6BT, United Kingdom
| | - Cen Wan
- Department of Computer Science, University College London, London, United Kingdom.,The Francis Crick Institute, Biomedical Data Science Laboratory, London, United Kingdom
| | - Domenico Cozzetto
- Department of Computer Science, University College London, London, United Kingdom.,The Francis Crick Institute, Biomedical Data Science Laboratory, London, United Kingdom
| | - Rui Fa
- Department of Computer Science, University College London, London, United Kingdom.,The Francis Crick Institute, Biomedical Data Science Laboratory, London, United Kingdom
| | - Mateo Torres
- Centre for Systems and Synthetic Biology, Department of Computer Science, Royal Holloway, University of London, Egham, Surrey, United Kingdom
| | - Alex Warwick Vesztrocy
- Department of Genetics, Evolution and Environment, University College London, Gower Street, London, WC1E 6BT, United Kingdom.,SIB Swiss Institute of Bioinformatics, Lausanne, 1015, Switzerland
| | - Jose Manuel Rodriguez
- Cardiovascular Proteomics Laboratory, Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain
| | - Michael L Tress
- Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Marco Frasca
- Università degli Studi di Milano - Computer Science Department - AnacletoLab, Milan, Milan, Italy
| | - Marco Notaro
- Università degli Studi di Milano - Computer Science Department - AnacletoLab, Milan, Milan, Italy
| | - Giuliano Grossi
- Università degli Studi di Milano - Computer Science Department - AnacletoLab, Milan, Milan, Italy
| | - Alessandro Petrini
- Università degli Studi di Milano - Computer Science Department - AnacletoLab, Milan, Milan, Italy
| | - Matteo Re
- Università degli Studi di Milano - Computer Science Department - AnacletoLab, Milan, Milan, Italy
| | - Giorgio Valentini
- Università degli Studi di Milano - Computer Science Department - AnacletoLab, Milan, Milan, Italy
| | - Marco Mesiti
- Università degli Studi di Milano - Computer Science Department - AnacletoLab, Milan, Milan, Italy.,Institut de Biologie Computationnelle, LIRMM, CNRS-UMR 5506, Universite de Montpellier, Montpellier, France
| | - Daniel B Roche
- Department of Informatics, Bioinformatics and Computational Biology-i12, Technische Universitat Munchen, Munich, Germany
| | - Jonas Reeb
- Department of Informatics, Bioinformatics and Computational Biology-i12, Technische Universitat Munchen, Munich, Germany
| | - David W Ritchie
- University of Lorraine, CNRS, Inria, LORIA, Nancy, 54000, France
| | - Sabeur Aridhi
- University of Lorraine, CNRS, Inria, LORIA, Nancy, 54000, France
| | | | - Marie-Dominique Devignes
- University of Lorraine, CNRS, Inria, LORIA, Nancy, 54000, France.,University of Lorraine, Nancy, Lorraine, France.,Inria, Nancy, France
| | | | - Richard Bonneau
- NYU Center for Data Science, New York, 10010, NY, USA.,Flatiron Institute, CCB, New York, 10010, NY, USA
| | - Vladimir Gligorijević
- Center for Computational Biology (CCB), Flatiron Institute, Simons Foundation, New York, New York, USA
| | - Meet Barot
- Center for Data Science, New York University, New York, 10011, NY, USA
| | - Hai Fang
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Stefano Toppo
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Enrico Lavezzo
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Marco Falda
- Department of Biology, University of Padova, Padova, Italy
| | - Michele Berselli
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Silvio C E Tosatto
- CNR Institute of Neuroscience, Padova, Italy.,Department of Biomedical Sciences, University of Padua, Padova, Italy
| | - Marco Carraro
- Department of Biomedical Sciences, University of Padua, Padova, Italy
| | - Damiano Piovesan
- Department of Biomedical Sciences, University of Padua, Padova, Italy
| | - Hafeez Ur Rehman
- Department of Computer Science, National University of Computer and Emerging Sciences, Peshawar, Khyber Pakhtoonkhwa, Pakistan
| | - Qizhong Mao
- Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA.,University of California, Riverside, Philadelphia, PA, USA
| | - Shanshan Zhang
- Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA
| | - Slobodan Vucetic
- Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA
| | - Gage S Black
- Department of Biology, Brigham Young University, Provo, UT, USA.,Bioinformatics Research Group, Provo, UT, USA
| | - Dane Jo
- Department of Biology, Brigham Young University, Provo, UT, USA.,Bioinformatics Research Group, Provo, UT, USA
| | - Erica Suh
- Department of Biology, Brigham Young University, Provo, UT, USA
| | - Jonathan B Dayton
- Department of Biology, Brigham Young University, Provo, UT, USA.,Bioinformatics Research Group, Provo, UT, USA
| | - Dallas J Larsen
- Department of Biology, Brigham Young University, Provo, UT, USA.,Bioinformatics Research Group, Provo, UT, USA
| | - Ashton R Omdahl
- Department of Biology, Brigham Young University, Provo, UT, USA.,Bioinformatics Research Group, Provo, UT, USA
| | - Liam J McGuffin
- School of Biological Sciences, University of Reading, Reading, England, United Kingdom
| | | | - Patricia C Babbitt
- Department of Pharmaceutical Chemistry, San Francisco, CA, USA.,Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, 94158, CA, USA
| | - Jeffrey M Yunes
- UC Berkeley - UCSF Graduate Program in Bioengineering, University of California, San Francisco, 94158, CA, USA.,Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, 94158, CA, USA
| | - Paolo Fontana
- Research and Innovation Center, Edmund Mach Foundation, San Michele all'Adige, Italy
| | - Feng Zhang
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, Shanghai, China.,Department of Biostatistics and Computational Biology, School of Life Sciences, Fudan University, Shanghai, Shanghai, China
| | - Shanfeng Zhu
- School of Computer Science and Shanghai Key Lab of Intelligent Information Processing, Fudan University, Shanghai, China.,Institute of Science and Technology for Brain-Inspired Intelligence and Shanghai Institute of Artificial Intelligence Algorithms, Fudan University, Shanghai, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Ronghui You
- School of Computer Science and Shanghai Key Lab of Intelligent Information Processing, Fudan University, Shanghai, China.,Institute of Science and Technology for Brain-Inspired Intelligence and Shanghai Institute of Artificial Intelligence Algorithms, Fudan University, Shanghai, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Zihan Zhang
- School of Computer Science and Shanghai Key Lab of Intelligent Information Processing, Fudan University, Shanghai, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Suyang Dai
- School of Computer Science and Shanghai Key Lab of Intelligent Information Processing, Fudan University, Shanghai, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Shuwei Yao
- School of Computer Science and Shanghai Key Lab of Intelligent Information Processing, Fudan University, Shanghai, China.,Institute of Science and Technology for Brain-Inspired Intelligence and Shanghai Institute of Artificial Intelligence Algorithms, Fudan University, Shanghai, China
| | - Weidong Tian
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, Department of Biostatistics and Computational Biology, School of Life Sciences, Fudan University, Shanghai, Shanghai, China.,Department of Pediatrics, Brain Tumor Center, Division of Experimental Hematology and Cancer Biology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Renzhi Cao
- Department of Computer Science, Pacific Lutheran University, Tacoma, WA, USA
| | - Caleb Chandler
- Department of Computer Science, Pacific Lutheran University, Tacoma, WA, USA
| | - Miguel Amezola
- Department of Computer Science, Pacific Lutheran University, Tacoma, WA, USA
| | - Devon Johnson
- Department of Computer Science, Pacific Lutheran University, Tacoma, WA, USA
| | - Jia-Ming Chang
- Department of Computer Science, National Chengchi University, Taipei, Taiwan
| | - Wen-Hung Liao
- Department of Computer Science, National Chengchi University, Taipei, Taiwan
| | - Yi-Wei Liu
- Department of Computer Science, National Chengchi University, Taipei, Taiwan
| | | | | | - Robert Hoehndorf
- Computer, Electrical and Mathematical Sciences & Engineering Division, Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal, Jeddah, Saudi Arabia
| | - Maxat Kulmanov
- Computer, Electrical and Mathematical Sciences & Engineering Division, Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal, Jeddah, Saudi Arabia
| | - Imane Boudellioua
- Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.,Computer, Electrical and Mathematical Sciences Engineering Division (CEMSE), King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Gianfranco Politano
- Control and Computer Engineering Department, Politecnico di Torino, Torino, TO, Italy
| | - Stefano Di Carlo
- Control and Computer Engineering Department, Politecnico di Torino, Torino, TO, Italy
| | - Alfredo Benso
- Control and Computer Engineering Department, Politecnico di Torino, Torino, TO, Italy
| | - Kai Hakala
- Department of Future Technologies, Turku NLP Group, University of Turku, Turku, Finland.,University of Turku Graduate School (UTUGS), Turku, Finland
| | - Filip Ginter
- Department of Future Technologies, Turku NLP Group, University of Turku, Turku, Finland.,University of Turku, Turku, Finland
| | - Farrokh Mehryary
- Department of Future Technologies, Turku NLP Group, University of Turku, Turku, Finland.,University of Turku Graduate School (UTUGS), Turku, Finland
| | - Suwisa Kaewphan
- Department of Future Technologies, Turku NLP Group, University of Turku, Turku, Finland.,University of Turku Graduate School (UTUGS), Turku, Finland.,Turku Centre for Computer Science (TUCS), Turku, Finland
| | - Jari Björne
- Department of Future Technologies, Faculty of Science and Engineering, University of Turku, Turku, FI-20014, Finland.,Turku Centre for Computer Science (TUCS), Agora, Vesilinnantie 3, Turku, FI-20500, Finland
| | | | | | - Tapio Salakoski
- Department of Future Technologies, Faculty of Science and Engineering, University of Turku, Turku, FI-20014, Finland.,Turku Centre for Computer Science (TUCS), Agora, Vesilinnantie 3, Turku, FI-20500, Finland
| | - Daisuke Kihara
- Department of Biological Sciences, Department of Computer Science, Purdue University, 47907, IN, USA.,Department of Pediatrics, University of Cincinnati, Cincinnati, 45229, OH, USA
| | - Aashish Jain
- Department of Computer Science, Purdue University, West Lafayette, IN, USA
| | - Tomislav Šmuc
- Division of Electronics, Rudjer Boskovic Institute, Zagreb, Croatia
| | - Adrian Altenhoff
- Department of Computer Science, ETH Zurich, Zurich, Switzerland.,SIB Swiss Institute of Bioinformatics, Zurich, Switzerland
| | - Asa Ben-Hur
- Department of Computer Science, Colorado State University, Fort Collins, CO, USA
| | - Burkhard Rost
- Department of Informatics, Bioinformatics & Computational Biology-i12, Technische Universitat Munchen, Munich, Germany.,Institute for Food and Plant Sciences WZW, Technische Universität München, Freising, Germany
| | | | - Christine A Orengo
- Research Department of Structural and Molecular Biology, University College London, London, United Kingdom
| | - Constance J Jeffery
- Biological Sciences, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Giovanni Bosco
- Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA
| | - Deborah A Hogan
- Geisel School of Medicine at Dartmouth, Hanover, NH, USA.,Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA
| | - Maria J Martin
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, United Kingdom
| | - Claire O'Donovan
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, United Kingdom
| | - Sean D Mooney
- Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA
| | - Casey S Greene
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Childhood Cancer Data Lab, Alex's Lemonade Stand Foundation, Philadelphia, Pennsylvania, USA
| | - Predrag Radivojac
- Khoury College of Computer Sciences, Northeastern University, Boston, MA, USA.
| | - Iddo Friedberg
- Veterinary Microbiology and Preventive Medicine, Iowa State University, Ames, IA, USA.
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19
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Lavezzo E, Berselli M, Frasson I, Perrone R, Palù G, Brazzale AR, Richter SN, Toppo S. G-quadruplex forming sequences in the genome of all known human viruses: A comprehensive guide. PLoS Comput Biol 2018; 14:e1006675. [PMID: 30543627 PMCID: PMC6307822 DOI: 10.1371/journal.pcbi.1006675] [Citation(s) in RCA: 80] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2018] [Revised: 12/27/2018] [Accepted: 11/27/2018] [Indexed: 12/21/2022] Open
Abstract
G-quadruplexes are non-canonical nucleic-acid structures that control transcription, replication, and recombination in organisms. G-quadruplexes are present in eukaryotes, prokaryotes, and viruses. In the latter, mounting evidence indicates their key biological activity. Since data on viruses are scattered, we here present a comprehensive analysis of potential quadruplex-forming sequences (PQS) in the genome of all known viruses that can infect humans. We show that occurrence and location of PQSs are features characteristic of each virus class and family. Our statistical analysis proves that their presence within the viral genome is orderly arranged, as indicated by the possibility to correctly assign up to two-thirds of viruses to their exact class based on the PQS classification. For each virus we provide: i) the list of all PQS present in the genome (positive and negative strands), ii) their position in the viral genome, iii) the degree of conservation among strains of each PQS in its genome context, iv) the statistical significance of PQS abundance. This information is accessible from a database to allow the easy navigation of the results: http://www.medcomp.medicina.unipd.it/main_site/doku.php?id=g4virus. The availability of these data will greatly expedite research on G-quadruplex in viruses, with the possibility to accelerate finding therapeutic opportunities to numerous and some fearsome human diseases.
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Affiliation(s)
- Enrico Lavezzo
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Michele Berselli
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Ilaria Frasson
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Rosalba Perrone
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Giorgio Palù
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | | | - Sara N. Richter
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Stefano Toppo
- Department of Molecular Medicine, University of Padova, Padova, Italy
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20
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Drzewnioková P, Barzon L, Franchin E, Lavezzo E, Bakonyi T, Pistl J, Csank T. The complete genome sequence analysis of West Nile virus strains isolated in Slovakia (central Europe). Arch Virol 2018; 164:273-277. [PMID: 30284630 DOI: 10.1007/s00705-018-4056-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2018] [Accepted: 09/20/2018] [Indexed: 11/29/2022]
Abstract
The present study reports the first complete genome sequence analysis of West Nile virus (WNV) strains isolated from brain samples from raptors. The results prove the circulation of closely related WNV lineage II strains in central Europe and genetic analysis revealed seven amino acid substitutions in structural (PrM3, E159 and E231) and in non-structural (NS1109, NS5259, NS5310 and NS5600) proteins. Observed amino acid substitutions Phe3 and Ser231 were common only within the lineage VII Koutango strain isolated from Rhipicephalus guilhoni tick in Senegal. Further research could reveal whether these substitutions influence the biological properties of WNV, including virulence and neuroinvasiveness.
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Affiliation(s)
- Petra Drzewnioková
- Department of Microbiology and Immunology, University of Veterinary Medicine and Pharmacy in Košice, Košice, Slovakia
| | - Luisa Barzon
- Department of Molecular Medicine, University of Padova, Padova, Italy.,Microbiology and Virology Unit, Padova University Hospital, Padova, Italy
| | - Elisa Franchin
- Department of Molecular Medicine, University of Padova, Padova, Italy.,Microbiology and Virology Unit, Padova University Hospital, Padova, Italy
| | - Enrico Lavezzo
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Tamás Bakonyi
- Institute of Virology, University of Veterinary Medicine Vienna, Vienna, Austria.,Department of Microbiology and Infectious Diseases, University of Veterinary Medicine, Budapest, Hungary
| | - Juraj Pistl
- Department of Microbiology and Immunology, University of Veterinary Medicine and Pharmacy in Košice, Košice, Slovakia
| | - Tomáš Csank
- Department of Microbiology and Immunology, University of Veterinary Medicine and Pharmacy in Košice, Košice, Slovakia.
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21
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Sambo F, Finotello F, Lavezzo E, Baruzzo G, Masi G, Peta E, Falda M, Toppo S, Barzon L, Di Camillo B. Optimizing PCR primers targeting the bacterial 16S ribosomal RNA gene. BMC Bioinformatics 2018; 19:343. [PMID: 30268091 PMCID: PMC6162885 DOI: 10.1186/s12859-018-2360-6] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2017] [Accepted: 09/09/2018] [Indexed: 02/01/2023] Open
Abstract
BACKGROUND Targeted amplicon sequencing of the 16S ribosomal RNA gene is one of the key tools for studying microbial diversity. The accuracy of this approach strongly depends on the choice of primer pairs and, in particular, on the balance between efficiency, specificity and sensitivity in the amplification of the different bacterial 16S sequences contained in a sample. There is thus the need for computational methods to design optimal bacterial 16S primers able to take into account the knowledge provided by the new sequencing technologies. RESULTS We propose here a computational method for optimizing the choice of primer sets, based on multi-objective optimization, which simultaneously: 1) maximizes efficiency and specificity of target amplification; 2) maximizes the number of different bacterial 16S sequences matched by at least one primer; 3) minimizes the differences in the number of primers matching each bacterial 16S sequence. Our algorithm can be applied to any desired amplicon length without affecting computational performance. The source code of the developed algorithm is released as the mopo16S software tool (Multi-Objective Primer Optimization for 16S experiments) under the GNU General Public License and is available at http://sysbiobig.dei.unipd.it/?q=Software#mopo16S . CONCLUSIONS Results show that our strategy is able to find better primer pairs than the ones available in the literature according to all three optimization criteria. We also experimentally validated three of the primer pairs identified by our method on multiple bacterial species, belonging to different genera and phyla. Results confirm the predicted efficiency and the ability to maximize the number of different bacterial 16S sequences matched by primers.
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Affiliation(s)
- Francesco Sambo
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Francesca Finotello
- Biocenter, Division of Bioinformatics, Medical University of Innsbruck, Innsbruck, Austria
| | - Enrico Lavezzo
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Giacomo Baruzzo
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Giulia Masi
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Elektra Peta
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Marco Falda
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Stefano Toppo
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Luisa Barzon
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Barbara Di Camillo
- Department of Information Engineering, University of Padova, Padova, Italy
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22
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Bianco L, Riccadonna S, Lavezzo E, Falda M, Formentin E, Cavalieri D, Toppo S, Fontana P. Pathway Inspector: a pathway based web application for RNAseq analysis of model and non-model organisms. Bioinformatics 2018; 33:453-455. [PMID: 28158604 PMCID: PMC5408796 DOI: 10.1093/bioinformatics/btw636] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2016] [Revised: 08/26/2016] [Accepted: 09/30/2016] [Indexed: 12/04/2022] Open
Abstract
Summary Pathway Inspector is an easy-to-use web application helping researchers to find patterns of expression in complex RNAseq experiments. The tool combines two standard approaches for RNAseq analysis: the identification of differentially expressed genes and a topology-based analysis of enriched pathways. Pathway Inspector is equipped with ad hoc interactive graphical interfaces simplifying the discovery of modulated pathways and the integration of the differentially expressed genes in the corresponding pathway topology. Availability and Implementation Pathway Inspector is available at the website http://admiral.fmach.it/PI and has been developed in Python, making use of the Django Web Framework.
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Affiliation(s)
- Luca Bianco
- Research and Innovation Center, Edmund Mach Foundation, 38010 S. Michele all'Adige, Italy
| | - Samantha Riccadonna
- Research and Innovation Center, Edmund Mach Foundation, 38010 S. Michele all'Adige, Italy
| | | | | | - Elide Formentin
- Department of Biology, University of Padova, 35131 Padova, Italy
| | - Duccio Cavalieri
- Research and Innovation Center, Edmund Mach Foundation, 38010 S. Michele all'Adige, Italy
| | | | - Paolo Fontana
- Research and Innovation Center, Edmund Mach Foundation, 38010 S. Michele all'Adige, Italy
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23
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Affiliation(s)
- Michele Berselli
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Enrico Lavezzo
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Stefano Toppo
- Department of Molecular Medicine, University of Padova, Padova, Italy
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24
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Formentin E, Sudiro C, Perin G, Riccadonna S, Barizza E, Baldoni E, Lavezzo E, Stevanato P, Sacchi GA, Fontana P, Toppo S, Morosinotto T, Zottini M, Lo Schiavo F. Transcriptome and Cell Physiological Analyses in Different Rice Cultivars Provide New Insights Into Adaptive and Salinity Stress Responses. Front Plant Sci 2018; 9:204. [PMID: 29556243 PMCID: PMC5844958 DOI: 10.3389/fpls.2018.00204] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2017] [Accepted: 02/02/2018] [Indexed: 05/20/2023]
Abstract
Salinity tolerance has been extensively investigated in recent years due to its agricultural importance. Several features, such as the regulation of ionic transporters and metabolic adjustments, have been identified as salt tolerance hallmarks. Nevertheless, due to the complexity of the trait, the results achieved to date have met with limited success in improving the salt tolerance of rice plants when tested in the field, thus suggesting that a better understanding of the tolerance mechanisms is still required. In this work, differences between two varieties of rice with contrasting salt sensitivities were revealed by the imaging of photosynthetic parameters, ion content analysis and a transcriptomic approach. The transcriptomic analysis conducted on tolerant plants supported the setting up of an adaptive program consisting of sodium distribution preferentially limited to the roots and older leaves, and in the activation of regulatory mechanisms of photosynthesis in the new leaves. As a result, plants resumed grow even under prolonged saline stress. In contrast, in the sensitive variety, RNA-seq analysis revealed a misleading response, ending in senescence and cell death. The physiological response at the cellular level was investigated by measuring the intracellular profile of H2O2 in the roots, using a fluorescent probe. In the roots of tolerant plants, a quick response was observed with an increase in H2O2 production within 5 min after salt treatment. The expression analysis of some of the genes involved in perception, signal transduction and salt stress response confirmed their early induction in the roots of tolerant plants compared to sensitive ones. By inhibiting the synthesis of apoplastic H2O2, a reduction in the expression of these genes was detected. Our results indicate that quick H2O2 signaling in the roots is part of a coordinated response that leads to adaptation instead of senescence in salt-treated rice plants.
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Affiliation(s)
- Elide Formentin
- Department of Biology, University of Padova, Padova, Italy
- *Correspondence: Elide Formentin,
| | | | - Giorgio Perin
- Department of Biology, University of Padova, Padova, Italy
| | - Samantha Riccadonna
- Research and Innovation Centre, Edmund Mach Foundation, San Michele all’Adige, Italy
| | | | - Elena Baldoni
- Department of Agricultural and Environmental Sciences - Production, Landscape, Agroenergy, University of Milan, Milan, Italy
| | - Enrico Lavezzo
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Piergiorgio Stevanato
- Department of Agronomy, Food, Natural Resources, Animals and the Environment, University of Padova, Padova, Italy
| | - Gian Attilio Sacchi
- Department of Agricultural and Environmental Sciences - Production, Landscape, Agroenergy, University of Milan, Milan, Italy
| | - Paolo Fontana
- Research and Innovation Centre, Edmund Mach Foundation, San Michele all’Adige, Italy
| | - Stefano Toppo
- Department of Molecular Medicine, University of Padova, Padova, Italy
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25
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Perrone R, Lavezzo E, Riello E, Manganelli R, Palù G, Toppo S, Provvedi R, Richter SN. Mapping and characterization of G-quadruplexes in Mycobacterium tuberculosis gene promoter regions. Sci Rep 2017; 7:5743. [PMID: 28720801 PMCID: PMC5515968 DOI: 10.1038/s41598-017-05867-z] [Citation(s) in RCA: 61] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2017] [Accepted: 06/02/2017] [Indexed: 12/04/2022] Open
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.
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Affiliation(s)
- Rosalba Perrone
- Department of Molecular Medicine, University of Padua, via Gabelli 63, 35121, Padua, Italy
| | - Enrico Lavezzo
- Department of Molecular Medicine, University of Padua, via Gabelli 63, 35121, Padua, Italy
| | - Erika Riello
- Department of Molecular Medicine, University of Padua, via Gabelli 63, 35121, Padua, Italy
| | - Riccardo Manganelli
- Department of Molecular Medicine, University of Padua, via Gabelli 63, 35121, Padua, Italy
| | - Giorgio Palù
- Department of Molecular Medicine, University of Padua, via Gabelli 63, 35121, Padua, Italy
| | - Stefano Toppo
- Department of Molecular Medicine, University of Padua, via Gabelli 63, 35121, Padua, Italy.
| | - Roberta Provvedi
- Department of Biology, University of Padua, via Ugo Bassi 58/b, 35121, Padua, Italy.
| | - Sara N Richter
- Department of Molecular Medicine, University of Padua, via Gabelli 63, 35121, Padua, Italy.
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26
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Zehender G, Veo C, Ebranati E, Carta V, Rovida F, Percivalle E, Moreno A, Lelli D, Calzolari M, Lavazza A, Chiapponi C, Baioni L, Capelli G, Ravagnan S, Da Rold G, Lavezzo E, Palù G, Baldanti F, Barzon L, Galli M. Reconstructing the recent West Nile virus lineage 2 epidemic in Europe and Italy using discrete and continuous phylogeography. PLoS One 2017; 12:e0179679. [PMID: 28678837 PMCID: PMC5497961 DOI: 10.1371/journal.pone.0179679] [Citation(s) in RCA: 42] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2017] [Accepted: 06/04/2017] [Indexed: 11/24/2022] Open
Abstract
West Nile virus lineage 2 (WNV-2) was mainly confined to sub-Saharan Africa until the early 2000s, when it was identified for the first time in Central Europe causing outbreaks of human and animal infection. The aim of this study was to reconstruct the origin and dispersion of WNV-2 in Central Europe and Italy on a phylodynamic and phylogeographical basis. To this aim, discrete and continuous space phylogeographical models were applied to a total of 33 newly characterised full-length viral genomes obtained from mosquitoes, birds and humans in Northern Italy in the years 2013–2015 aligned with 64 complete sequences isolated mainly in Europe. The European isolates segregated into two highly significant clades: a small one including three sequences and a large clade including the majority of isolates obtained in Central Europe since 2004. Discrete phylogeographical analysis showed that the most probable location of the root of the largest European clade was in Hungary a mean 12.78 years ago. The European clade bifurcated into two highly supported subclades: one including most of the Central/East European isolates and the other encompassing all of the isolates obtained in Greece. The continuous space phylogeographical analysis of the Italian clade showed that WNV-2 entered Italy in about 2008, probably by crossing the Adriatic sea and reaching a central area of the Po Valley. The epidemic then spread simultaneously eastward, to reach the region of the Po delta in 2013, and westward to the border area between Lombardy and Piedmont in 2014; later, the western strain changed direction southward, and reached the central area of the Po valley once again in 2015. Over a period of about seven years, the virus spread all over an area of northern Italy by following the Po river and its main tributaries.
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Affiliation(s)
- Gianguglielmo Zehender
- Department of Biomedical and Clinical Sciences "L.Sacco", University of Milan, Milano, Italy
- CRC-Coordinated Research Center “EpiSoMI”, University of Milan, Milano, Italy
- * E-mail:
| | - Carla Veo
- Department of Biomedical and Clinical Sciences "L.Sacco", University of Milan, Milano, Italy
- CRC-Coordinated Research Center “EpiSoMI”, University of Milan, Milano, Italy
| | - Erika Ebranati
- Department of Biomedical and Clinical Sciences "L.Sacco", University of Milan, Milano, Italy
- CRC-Coordinated Research Center “EpiSoMI”, University of Milan, Milano, Italy
| | - Valentina Carta
- Department of Biomedical and Clinical Sciences "L.Sacco", University of Milan, Milano, Italy
- CRC-Coordinated Research Center “EpiSoMI”, University of Milan, Milano, Italy
| | - Francesca Rovida
- Molecular Virology Unit, Microbiology and Virology Department, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Elena Percivalle
- Molecular Virology Unit, Microbiology and Virology Department, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Ana Moreno
- Experimental Zooprophylactic Institute of Lombardy and Emilia-Romagna (IZSLER), Brescia, Italy
| | - Davide Lelli
- Experimental Zooprophylactic Institute of Lombardy and Emilia-Romagna (IZSLER), Brescia, Italy
| | - Mattia Calzolari
- Experimental Zooprophylactic Institute of Lombardy and Emilia-Romagna (IZSLER), Reggio Emilia, Italy
| | - Antonio Lavazza
- Experimental Zooprophylactic Institute of Lombardy and Emilia-Romagna (IZSLER), Brescia, Italy
| | - Chiara Chiapponi
- Experimental Zooprophylactic Institute of Lombardy and Emilia-Romagna (IZSLER), Parma, Italy
| | - Laura Baioni
- Experimental Zooprophylactic Institute of Lombardy and Emilia-Romagna (IZSLER), Parma, Italy
| | - Gioia Capelli
- Experimental Zooprophylactic Institute of Venice, Legnaro, Padua, Italy
| | - Silvia Ravagnan
- Experimental Zooprophylactic Institute of Venice, Legnaro, Padua, Italy
| | - Graziana Da Rold
- Experimental Zooprophylactic Institute of Venice, Legnaro, Padua, Italy
| | - Enrico Lavezzo
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Giorgio Palù
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Fausto Baldanti
- Molecular Virology Unit, Microbiology and Virology Department, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Luisa Barzon
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Massimo Galli
- Department of Biomedical and Clinical Sciences "L.Sacco", University of Milan, Milano, Italy
- CRC-Coordinated Research Center “EpiSoMI”, University of Milan, Milano, Italy
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Barzon L, Pacenti M, Franchin E, Lavezzo E, Trevisan M, Sgarabotto D, Palù G. Infection dynamics in a traveller with persistent shedding of Zika virus RNA in semen for six months after returning from Haiti to Italy, January 2016. ACTA ACUST UNITED AC 2017; 21:30316. [PMID: 27542178 PMCID: PMC4998504 DOI: 10.2807/1560-7917.es.2016.21.32.30316] [Citation(s) in RCA: 112] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2016] [Accepted: 08/11/2016] [Indexed: 11/21/2022]
Abstract
We describe the dynamics of Zika virus (ZIKV) infection in a man in his early 40s who developed fever and rash after returning from Haiti to Italy, in January 2016. Follow-up laboratory testing demonstrated detectable ZIKV RNA in plasma up to day 9 after symptom onset and in urine and saliva up to days 15 and 47, respectively. Notably, persistent shedding of ZIKV RNA was demonstrated in semen, still detectable at 181 days after onset.
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Affiliation(s)
- Luisa Barzon
- Department of Molecular Medicine, University of Padova, Padova, Italy
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Baymakova M, Trifonova I, Panayotova E, Dakova S, Pacenti M, Barzon L, Lavezzo E, Hristov Y, Ramshev K, Plochev K, Palu G, Christova I. Fatal Case of West Nile Neuroinvasive Disease in Bulgaria. Emerg Infect Dis 2016; 22:2203-2204. [PMID: 27392134 PMCID: PMC5189127 DOI: 10.3201/eid2212.151968] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
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Jiang Y, Oron TR, Clark WT, Bankapur AR, D'Andrea D, Lepore R, Funk CS, Kahanda I, Verspoor KM, Ben-Hur A, Koo DCE, Penfold-Brown D, Shasha D, Youngs N, Bonneau R, Lin A, Sahraeian SME, Martelli PL, Profiti G, Casadio R, Cao R, Zhong Z, Cheng J, Altenhoff A, Skunca N, Dessimoz C, Dogan T, Hakala K, Kaewphan S, Mehryary F, Salakoski T, Ginter F, Fang H, Smithers B, Oates M, Gough J, Törönen P, Koskinen P, Holm L, Chen CT, Hsu WL, Bryson K, Cozzetto D, Minneci F, Jones DT, Chapman S, Bkc D, Khan IK, Kihara D, Ofer D, Rappoport N, Stern A, Cibrian-Uhalte E, Denny P, Foulger RE, Hieta R, Legge D, Lovering RC, Magrane M, Melidoni AN, Mutowo-Meullenet P, Pichler K, Shypitsyna A, Li B, Zakeri P, ElShal S, Tranchevent LC, Das S, Dawson NL, Lee D, Lees JG, Sillitoe I, Bhat P, Nepusz T, Romero AE, Sasidharan R, Yang H, Paccanaro A, Gillis J, Sedeño-Cortés AE, Pavlidis P, Feng S, Cejuela JM, Goldberg T, Hamp T, Richter L, Salamov A, Gabaldon T, Marcet-Houben M, Supek F, Gong Q, Ning W, Zhou Y, Tian W, Falda M, Fontana P, Lavezzo E, Toppo S, Ferrari C, Giollo M, Piovesan D, Tosatto SCE, Del Pozo A, Fernández JM, Maietta P, Valencia A, Tress ML, Benso A, Di Carlo S, Politano G, Savino A, Rehman HU, Re M, Mesiti M, Valentini G, Bargsten JW, van Dijk ADJ, Gemovic B, Glisic S, Perovic V, Veljkovic V, Veljkovic N, Almeida-E-Silva DC, Vencio RZN, Sharan M, Vogel J, Kansakar L, Zhang S, Vucetic S, Wang Z, Sternberg MJE, Wass MN, Huntley RP, Martin MJ, O'Donovan C, Robinson PN, Moreau Y, Tramontano A, Babbitt PC, Brenner SE, Linial M, Orengo CA, Rost B, Greene CS, Mooney SD, Friedberg I, Radivojac P. An expanded evaluation of protein function prediction methods shows an improvement in accuracy. Genome Biol 2016; 17:184. [PMID: 27604469 PMCID: PMC5015320 DOI: 10.1186/s13059-016-1037-6] [Citation(s) in RCA: 252] [Impact Index Per Article: 31.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2015] [Accepted: 08/04/2016] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND A 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. RESULTS We 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. CONCLUSIONS The 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.
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Affiliation(s)
- Yuxiang Jiang
- Department of Computer Science and Informatics, Indiana University, Bloomington, IN, USA
| | | | - Wyatt T Clark
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Asma R Bankapur
- Department of Microbiology, Miami University, Oxford, OH, USA
| | | | | | - Christopher S Funk
- Computational Bioscience Program, University of Colorado School of Medicine, Aurora, CO, USA
| | - Indika Kahanda
- Department of Computer Science, Colorado State University, Fort Collins, CO, USA
| | - Karin M Verspoor
- Department of Computing and Information Systems, University of Melbourne, Parkville, Victoria, Australia
- Health and Biomedical Informatics Centre, University of Melbourne, Parkville, Victoria, Australia
| | - Asa Ben-Hur
- Department of Computer Science, Colorado State University, Fort Collins, CO, USA
| | | | - Duncan Penfold-Brown
- Social Media and Political Participation Lab, New York University, New York, NY, USA
- CY Data Science, New York, NY, USA
| | - Dennis Shasha
- Department of Computer Science, New York University, New York, NY, USA
| | - Noah Youngs
- CY Data Science, New York, NY, USA
- Department of Computer Science, New York University, New York, NY, USA
- Simons Center for Data Analysis, New York, NY, USA
| | - Richard Bonneau
- Department of Computer Science, New York University, New York, NY, USA
- Simons Center for Data Analysis, New York, NY, USA
- Center for Genomics and Systems Biology, Department of Biology, New York University, New York, NY, USA
| | - Alexandra Lin
- Department of Electrical Engineering and Computer Sciences, University of California Berkeley, Berkeley, CA, USA
| | - Sayed M E Sahraeian
- Department of Plant and Microbial Biology, University of California Berkeley, Berkeley, CA, USA
| | | | - Giuseppe Profiti
- Biocomputing Group, BiGeA, University of Bologna, Bologna, Italy
| | - Rita Casadio
- Biocomputing Group, BiGeA, University of Bologna, Bologna, Italy
| | - Renzhi Cao
- Computer Science Department, University of Missouri, Columbia, MO, USA
| | - Zhaolong Zhong
- Computer Science Department, University of Missouri, Columbia, MO, USA
| | - Jianlin Cheng
- Computer Science Department, University of Missouri, Columbia, MO, USA
| | - Adrian Altenhoff
- ETH Zurich, Zurich, Switzerland
- Swiss Institute of Bioinformatics, Zurich, Switzerland
| | - Nives Skunca
- ETH Zurich, Zurich, Switzerland
- Swiss Institute of Bioinformatics, Zurich, Switzerland
| | - Christophe Dessimoz
- Bioinformatics Group, Department of Computer Science, University College London, London, UK
- University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Tunca Dogan
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Kai Hakala
- Department of Information Technology, University of Turku, Turku, Finland
- University of Turku Graduate School, University of Turku, Turku, Finland
| | - Suwisa Kaewphan
- Department of Information Technology, University of Turku, Turku, Finland
- University of Turku Graduate School, University of Turku, Turku, Finland
- Turku Centre for Computer Science, Turku, Finland
| | - Farrokh Mehryary
- Department of Information Technology, University of Turku, Turku, Finland
- University of Turku Graduate School, University of Turku, Turku, Finland
| | - Tapio Salakoski
- Department of Information Technology, University of Turku, Turku, Finland
- Turku Centre for Computer Science, Turku, Finland
| | - Filip Ginter
- Department of Information Technology, University of Turku, Turku, Finland
| | - Hai Fang
- University of Bristol, Bristol, UK
| | | | | | | | - Petri Törönen
- Institute of Biotechnology, University of Helsinki, Helsinki, Finland
| | - Patrik Koskinen
- Institute of Biotechnology, University of Helsinki, Helsinki, Finland
| | - Liisa Holm
- Institute of Biotechnology, University of Helsinki, Helsinki, Finland
- Department of Biological and Environmental Sciences, Universitity of Helsinki, Helsinki, Finland
| | - Ching-Tai Chen
- Institute of Information Science, Academia Sinica, Taipei, Taiwan
| | - Wen-Lian Hsu
- Institute of Information Science, Academia Sinica, Taipei, Taiwan
| | - Kevin Bryson
- Bioinformatics Group, Department of Computer Science, University College London, London, UK
| | - Domenico Cozzetto
- Bioinformatics Group, Department of Computer Science, University College London, London, UK
| | - Federico Minneci
- Bioinformatics Group, Department of Computer Science, University College London, London, UK
| | - David T Jones
- Bioinformatics Group, Department of Computer Science, University College London, London, UK
| | - Samuel Chapman
- Department of Computational Science and Engineering, North Carolina A&T State University, Greensboro, NC, USA
| | - Dukka Bkc
- Department of Computational Science and Engineering, North Carolina A&T State University, Greensboro, NC, USA
| | - Ishita K Khan
- Department of Computer Science, Purdue University, West Lafayette, IN, USA
| | - Daisuke Kihara
- Department of Computer Science, Purdue University, West Lafayette, IN, USA
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA
| | - Dan Ofer
- Department of Biological Chemistry, Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Nadav Rappoport
- Department of Biological Chemistry, Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Amos Stern
- Department of Biological Chemistry, Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Elena Cibrian-Uhalte
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Paul Denny
- Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, London, UK
| | - Rebecca E Foulger
- Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, London, UK
| | - Reija Hieta
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Duncan Legge
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Ruth C Lovering
- Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, London, UK
| | - Michele Magrane
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Anna N Melidoni
- Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, London, UK
| | | | - Klemens Pichler
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Aleksandra Shypitsyna
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Biao Li
- Buck Institute for Research on Aging, Novato, CA, USA
| | - Pooya Zakeri
- Department of Electrical Engineering, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Leuven, Belgium
- iMinds Department Medical Information Technologies, Leuven, Belgium
| | - Sarah ElShal
- Department of Electrical Engineering, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Leuven, Belgium
- iMinds Department Medical Information Technologies, Leuven, Belgium
| | - Léon-Charles Tranchevent
- Inserm UMR-S1052, CNRS UMR5286, Cancer Research Centre of Lyon, Lyon, France
- Université de Lyon 1, Villeurbanne, France
- Centre Léon Bérard, Lyon, France
| | - Sayoni Das
- Institute of Structural and Molecular Biology, University College London, London, UK
| | - Natalie L Dawson
- Institute of Structural and Molecular Biology, University College London, London, UK
| | - David Lee
- Institute of Structural and Molecular Biology, University College London, London, UK
| | - Jonathan G Lees
- Institute of Structural and Molecular Biology, University College London, London, UK
| | - Ian Sillitoe
- Institute of Structural and Molecular Biology, University College London, London, UK
| | | | | | - Alfonso E Romero
- Department of Computer Science, Centre for Systems and Synthetic Biology, Royal Holloway University of London, Egham, UK
| | - Rajkumar Sasidharan
- Department of Molecular, Cell and Developmental Biology, University of California at Los Angeles, Los Angeles, CA, USA
| | - Haixuan Yang
- School of Mathematics, Statistics and Applied Mathematics, National University of Ireland, Galway, Ireland
| | - Alberto Paccanaro
- Department of Computer Science, Centre for Systems and Synthetic Biology, Royal Holloway University of London, Egham, UK
| | - Jesse Gillis
- Stanley Institute for Cognitive Genomics Cold Spring Harbor Laboratory, New York, NY, USA
| | | | - Paul Pavlidis
- Department of Psychiatry and Michael Smith Laboratories, University of British Columbia, Vancouver, Canada
| | - Shou Feng
- Department of Computer Science and Informatics, Indiana University, Bloomington, IN, USA
| | - Juan M Cejuela
- Department for Bioinformatics and Computational Biology-I12, Technische Universität München, Garching, Germany
| | - Tatyana Goldberg
- Department for Bioinformatics and Computational Biology-I12, Technische Universität München, Garching, Germany
| | - Tobias Hamp
- Department for Bioinformatics and Computational Biology-I12, Technische Universität München, Garching, Germany
| | - Lothar Richter
- Department for Bioinformatics and Computational Biology-I12, Technische Universität München, Garching, Germany
| | - Asaf Salamov
- DOE Joint Genome Institute, Walnut Creek, CA, USA
| | - Toni Gabaldon
- Bioinformatics and Genomics, Centre for Genomic Regulation, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain
| | - Marina Marcet-Houben
- Bioinformatics and Genomics, Centre for Genomic Regulation, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
| | - Fran Supek
- Universitat Pompeu Fabra, Barcelona, Spain
- Division of Electronics, Rudjer Boskovic Institute, Zagreb, Croatia
- EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation, Barcelona, Spain
| | - Qingtian Gong
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center of Genetics and Development, Department of Biostatistics and Computational Biology, School of Life Science, Fudan University, Shanghai, China
- Children's Hospital of Fudan University, Shanghai, China
| | - Wei Ning
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center of Genetics and Development, Department of Biostatistics and Computational Biology, School of Life Science, Fudan University, Shanghai, China
- Children's Hospital of Fudan University, Shanghai, China
| | - Yuanpeng Zhou
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center of Genetics and Development, Department of Biostatistics and Computational Biology, School of Life Science, Fudan University, Shanghai, China
- Children's Hospital of Fudan University, Shanghai, China
| | - Weidong Tian
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center of Genetics and Development, Department of Biostatistics and Computational Biology, School of Life Science, Fudan University, Shanghai, China
- Children's Hospital of Fudan University, Shanghai, China
| | - Marco Falda
- Department of Molecular Medicine, University of Padua, Padua, Italy
| | - Paolo Fontana
- Research and Innovation Center, Edmund Mach Foundation, San Michele all'Adige, Italy
| | - Enrico Lavezzo
- Department of Molecular Medicine, University of Padua, Padua, Italy
| | - Stefano Toppo
- Department of Molecular Medicine, University of Padua, Padua, Italy
| | - Carlo Ferrari
- Department of Information Engineering, University of Padua, Padova, Italy
| | - Manuel Giollo
- Department of Information Engineering, University of Padua, Padova, Italy
- Department of Biomedical Sciences, University of Padua, Padova, Italy
| | - Damiano Piovesan
- Department of Information Engineering, University of Padua, Padova, Italy
| | - Silvio C E Tosatto
- Department of Information Engineering, University of Padua, Padova, Italy
| | - Angela Del Pozo
- Instituto De Genetica Medica y Molecular, Hospital Universitario de La Paz, Madrid, Spain
| | - José M Fernández
- Spanish National Bioinformatics Institute, Spanish National Cancer Research Institute, Madrid, Spain
| | - Paolo Maietta
- Structural and Computational Biology Programme, Spanish National Cancer Research Institute, Madrid, Spain
| | - Alfonso Valencia
- Structural and Computational Biology Programme, Spanish National Cancer Research Institute, Madrid, Spain
| | - Michael L Tress
- Structural and Computational Biology Programme, Spanish National Cancer Research Institute, Madrid, Spain
| | - Alfredo Benso
- Control and Computer Engineering Department, Politecnico di Torino, Torino, Italy
| | - Stefano Di Carlo
- Control and Computer Engineering Department, Politecnico di Torino, Torino, Italy
| | - Gianfranco Politano
- Control and Computer Engineering Department, Politecnico di Torino, Torino, Italy
| | - Alessandro Savino
- Control and Computer Engineering Department, Politecnico di Torino, Torino, Italy
| | - Hafeez Ur Rehman
- National University of Computer & Emerging Sciences, Islamabad, Pakistan
| | - Matteo Re
- Anacleto Lab, Dipartimento di informatica, Università degli Studi di Milano, Milan, Italy
| | - Marco Mesiti
- Anacleto Lab, Dipartimento di informatica, Università degli Studi di Milano, Milan, Italy
| | - Giorgio Valentini
- Anacleto Lab, Dipartimento di informatica, Università degli Studi di Milano, Milan, Italy
| | - Joachim W Bargsten
- Applied Bioinformatics, Bioscience, Wageningen University and Research Centre, Wageningen, Netherlands
| | - Aalt D J van Dijk
- Applied Bioinformatics, Bioscience, Wageningen University and Research Centre, Wageningen, Netherlands
- Biometris, Wageningen University, Wageningen, Netherlands
| | - Branislava Gemovic
- Center for Multidisciplinary Research, Institute of Nuclear Sciences Vinca, University of Belgrade, Belgrade, Serbia
| | - Sanja Glisic
- Center for Multidisciplinary Research, Institute of Nuclear Sciences Vinca, University of Belgrade, Belgrade, Serbia
| | - Vladmir Perovic
- Center for Multidisciplinary Research, Institute of Nuclear Sciences Vinca, University of Belgrade, Belgrade, Serbia
| | - Veljko Veljkovic
- Center for Multidisciplinary Research, Institute of Nuclear Sciences Vinca, University of Belgrade, Belgrade, Serbia
| | - Nevena Veljkovic
- Center for Multidisciplinary Research, Institute of Nuclear Sciences Vinca, University of Belgrade, Belgrade, Serbia
| | | | - Ricardo Z N Vencio
- Department of Computing and Mathematics FFCLRP-USP, University of Sao Paulo, Ribeirao Preto, Brazil
| | - Malvika Sharan
- Institute for Molecular Infection Biology, University of Würzburg, Würzburg, Germany
| | - Jörg Vogel
- Institute for Molecular Infection Biology, University of Würzburg, Würzburg, Germany
| | - Lakesh Kansakar
- Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA
| | - Shanshan Zhang
- Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA
| | - Slobodan Vucetic
- Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA
| | - Zheng Wang
- University of Southern Mississippi, Hattiesburg, MS, USA
| | - Michael J E Sternberg
- Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London, UK
| | - Mark N Wass
- School of Biosciences, University of Kent, Canterbury, Kent, UK
| | - Rachael P Huntley
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Maria J Martin
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Claire O'Donovan
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Peter N Robinson
- Institut für Medizinische Genetik und Humangenetik, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Yves Moreau
- Department of Electrical Engineering ESAT-SCD and IBBT-KU Leuven Future Health Department, Katholieke Universiteit Leuven, Leuven, Belgium
| | | | - Patricia C Babbitt
- California Institute for Quantitative Biosciences, University of California San Francisco, San Francisco, CA, USA
| | - Steven E Brenner
- Department of Plant and Microbial Biology, University of California Berkeley, Berkeley, CA, USA
| | - Michal Linial
- Department of Chemical Biology, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Christine A Orengo
- Institute of Structural and Molecular Biology, University College London, London, UK
| | - Burkhard Rost
- Department for Bioinformatics and Computational Biology-I12, Technische Universität München, Garching, Germany
| | - Casey S Greene
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, PA, USA
| | - Sean D Mooney
- Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA
| | - Iddo Friedberg
- Department of Microbiology, Miami University, Oxford, OH, USA.
- Department of Computer Science, Miami University, Oxford, OH, USA.
| | - Predrag Radivojac
- Department of Computer Science and Informatics, Indiana University, Bloomington, IN, USA.
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Barzon L, Pacenti M, Berto A, Sinigaglia A, Franchin E, Lavezzo E, Brugnaro P, Palù G. Isolation of infectious Zika virus from saliva and prolonged viral RNA shedding in a traveller returning from the Dominican Republic to Italy, January 2016. ACTA ACUST UNITED AC 2016; 21:30159. [PMID: 26987769 DOI: 10.2807/1560-7917.es.2016.21.10.30159] [Citation(s) in RCA: 128] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2016] [Accepted: 03/10/2016] [Indexed: 11/20/2022]
Abstract
We report the isolation of infectious Zika virus (ZIKV) in cell culture from the saliva of a patient who developed a febrile illness after returning from the Dominican Republic to Italy, in January 2016. The patient had prolonged shedding of viral RNA in saliva and urine, at higher load than in blood, for up to 29 days after symptom onset. Sequencing of ZIKV genome showed relatedness with strains from Latin America.
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Affiliation(s)
- Luisa Barzon
- Department of Molecular Medicine, University of Padova, Padova, Italy
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Abstract
Zika virus is a mosquito-borne flavivirus discovered in Uganda in 1947. The virus has emerged in recent years and spread in the Pacific Area and the Americas, where it has caused large human outbreaks. The factors involved in the virus's emergence are still unknown, but probably include its introduction in naïve environments characterised by the presence of high densities of competent Aedes spp. mosquitoes and susceptible human hosts in urban areas. Unique features of Zika virus infection are sexual and transplacental transmission and associated neurological morbidities, i.e. Guillain-Barré syndrome and fetal microcephaly. Diagnosis relies on the detection of viral nucleic acids in biological samples, while detection of a specific antibody response may be inconclusive because of the broad cross-reactivity of antibodies among flaviviruses. Experimental studies have clarified some mechanisms of Zika virus pathogenesis and have identified potential targets for antiviral drugs. In animal models, the virus can infect and efficiently replicate in the placenta and in the brain, and induce fetal demise or neural damage, recapitulating human diseases. These animal models have been used to evaluate candidate vaccines and promising results have been obtained.
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Affiliation(s)
- Luisa Barzon
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Marta Trevisan
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | | | - Enrico Lavezzo
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Giorgio Palù
- Department of Molecular Medicine, University of Padova, Padova, Italy
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Falda M, Lavezzo E, Fontana P, Bianco L, Berselli M, Formentin E, Toppo S. Eliciting the Functional Taxonomy from protein annotations and taxa. Sci Rep 2016; 6:31971. [PMID: 27534507 PMCID: PMC4989186 DOI: 10.1038/srep31971] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2016] [Accepted: 08/01/2016] [Indexed: 11/30/2022] Open
Abstract
The advances of omics technologies have triggered the production of an enormous volume of data coming from thousands of species. Meanwhile, joint international efforts like the Gene Ontology (GO) consortium have worked to provide functional information for a vast amount of proteins. With these data available, we have developed FunTaxIS, a tool that is the first attempt to infer functional taxonomy (i.e. how functions are distributed over taxa) combining functional and taxonomic information. FunTaxIS is able to define a taxon specific functional space by exploiting annotation frequencies in order to establish if a function can or cannot be used to annotate a certain species. The tool generates constraints between GO terms and taxa and then propagates these relations over the taxonomic tree and the GO graph. Since these constraints nearly cover the whole taxonomy, it is possible to obtain the mapping of a function over the taxonomy. FunTaxIS can be used to make functional comparative analyses among taxa, to detect improper associations between taxa and functions, and to discover how functional knowledge is either distributed or missing. A benchmark test set based on six different model species has been devised to get useful insights on the generated taxonomic rules.
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Affiliation(s)
- Marco Falda
- Department of Molecular Medicine, University of Padova, Padova, 35131, Italy
| | - Enrico Lavezzo
- Department of Molecular Medicine, University of Padova, Padova, 35131, Italy
| | - Paolo Fontana
- Istituto Agrario San Michele all'Adige Research and Innovation Centre, Foundation Edmund Mach, Trento, 38010, Italy
| | - Luca Bianco
- Istituto Agrario San Michele all'Adige Research and Innovation Centre, Foundation Edmund Mach, Trento, 38010, Italy
| | - Michele Berselli
- Department of Molecular Medicine, University of Padova, Padova, 35131, Italy
| | - Elide Formentin
- Department of Biology, University of Padova, Padova, 35131, Italy
| | - Stefano Toppo
- Department of Molecular Medicine, University of Padova, Padova, 35131, Italy
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Lavezzo E, Barzon L, Toppo S, Palù G. Third generation sequencing technologies applied to diagnostic microbiology: benefits and challenges in applications and data analysis. Expert Rev Mol Diagn 2016; 16:1011-23. [PMID: 27453996 DOI: 10.1080/14737159.2016.1217158] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
INTRODUCTION The diagnosis of infectious diseases is among the most successful areas of application of new generation sequencing technologies. The field has seen the development of numerous experimental and analytical approaches for the detection and the fine description of pathogenic and non-pathogenic microorganisms. AREAS COVERED Without claiming to be exhaustive with respect to all applications and methods developed over the years, this review focuses on the advantages and the issues brought by the new technologies, with an eye in particular to third generation sequencing methods. Both experimental procedures and algorithmic strategies are presented, following the most relevant publications which have led to progress in our ability of detecting infectious agents. Expert commentary: The technical advance brought by third generation sequencing platforms has the potential to significantly expand the range of diagnostic tools that will be available to clinicians. Nonetheless, the implementation of these technologies in clinical practice is still far from being actionable and will temporally follow the path undertaken by second generation methods, which still require the setup of standardized pipelines in both wet and dry laboratory procedures.
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Affiliation(s)
- Enrico Lavezzo
- a Department of Molecular Medicine , University of Padova , Padova , Italy
| | - Luisa Barzon
- a Department of Molecular Medicine , University of Padova , Padova , Italy
| | - Stefano Toppo
- a Department of Molecular Medicine , University of Padova , Padova , Italy
| | - Giorgio Palù
- a Department of Molecular Medicine , University of Padova , Padova , Italy
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Piccirillo A, Lavezzo E, Niero G, Moreno A, Massi P, Franchin E, Toppo S, Salata C, Palù G. Full Genome Sequence-Based Comparative Study of Wild-Type and Vaccine Strains of Infectious Laryngotracheitis Virus from Italy. PLoS One 2016; 11:e0149529. [PMID: 26890525 PMCID: PMC4758665 DOI: 10.1371/journal.pone.0149529] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2015] [Accepted: 02/02/2016] [Indexed: 02/07/2023] Open
Abstract
Infectious laryngotracheitis (ILT) is an acute and highly contagious respiratory disease of chickens caused by an alphaherpesvirus, infectious laryngotracheitis virus (ILTV). Recently, full genome sequences of wild-type and vaccine strains have been determined worldwide, but none was from Europe. The aim of this study was to determine and analyse the complete genome sequences of five ILTV strains. Sequences were also compared to reveal the similarity of strains across time and to discriminate between wild-type and vaccine strains. Genomes of three ILTV field isolates from outbreaks occurred in Italy in 1980, 2007 and 2011, and two commercial chicken embryo origin (CEO) vaccines were sequenced using the 454 Life Sciences technology. The comparison with the Serva genome showed that 35 open reading frames (ORFs) differed across the five genomes. Overall, 54 single nucleotide polymorphisms (SNPs) and 27 amino acid differences in 19 ORFs and two insertions in the UL52 and ORFC genes were identified. Similarity among the field strains and between the field and the vaccine strains ranged from 99.96% to 99.99%. Phylogenetic analysis revealed a close relationship among them, as well. This study generated data on genomic variation among Italian ILTV strains revealing that, even though the genetic variability of the genome is well conserved across time and between wild-type and vaccine strains, some mutations may help in differentiating among them and may be involved in ILTV virulence/attenuation. The results of this study can contribute to the understanding of the molecular bases of ILTV pathogenicity and provide genetic markers to differentiate between wild-type and vaccine strains.
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Affiliation(s)
- Alessandra Piccirillo
- Department of Comparative Biomedicine and Food Science (BCA), University of Padua, Legnaro (Padua), Italy
- * E-mail:
| | - Enrico Lavezzo
- Department of Molecular Medicine, University of Padua (DMM), Padua, Italy
| | - Giulia Niero
- Department of Comparative Biomedicine and Food Science (BCA), University of Padua, Legnaro (Padua), Italy
| | - Ana Moreno
- Department of Virology, Istituto Zooprofilattico Sperimentale della Lombardia e dell’Emilia Romagna (IZSLER), Brescia, Italy
| | - Paola Massi
- Department of Diagnostics, Istituto Zooprofilattico Sperimentale della Lombardia e dell’Emilia Romagna (IZSLER), Forlì, Italy
| | - Elisa Franchin
- Department of Molecular Medicine, University of Padua (DMM), Padua, Italy
| | - Stefano Toppo
- Department of Molecular Medicine, University of Padua (DMM), Padua, Italy
| | - Cristiano Salata
- Department of Molecular Medicine, University of Padua (DMM), Padua, Italy
| | - Giorgio Palù
- Department of Molecular Medicine, University of Padua (DMM), Padua, Italy
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Lavezzo E, Falda M, Fontana P, Bianco L, Toppo S. Enhancing protein function prediction with taxonomic constraints--The Argot2.5 web server. Methods 2015; 93:15-23. [PMID: 26318087 DOI: 10.1016/j.ymeth.2015.08.021] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2015] [Revised: 08/14/2015] [Accepted: 08/25/2015] [Indexed: 10/23/2022] Open
Abstract
Argot2.5 (Annotation Retrieval of Gene Ontology Terms) is a web server designed to predict protein function. It is an updated version of the previous Argot2 enriched with new features in order to enhance its usability and its overall performance. The algorithmic strategy exploits the grouping of Gene Ontology terms by means of semantic similarity to infer protein function. The tool has been challenged over two independent benchmarks and compared to Argot2, PANNZER, and a baseline method relying on BLAST, proving to obtain a better performance thanks to the contribution of some key interventions in critical steps of the working pipeline. The most effective changes regard: (a) the selection of the input data from sequence similarity searches performed against a clustered version of UniProt databank and a remodeling of the weights given to Pfam hits, (b) the application of taxonomic constraints to filter out annotations that cannot be applied to proteins belonging to the species under investigation. The taxonomic rules are derived from our in-house developed tool, FunTaxIS, that extends those provided by the Gene Ontology consortium. The web server is free for academic users and is available online at http://www.medcomp.medicina.unipd.it/Argot2-5/.
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Affiliation(s)
- Enrico Lavezzo
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Marco Falda
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Paolo Fontana
- Istituto Agrario San Michele all'Adige Research and Innovation Centre, Foundation Edmund Mach, Trento, Italy
| | - Luca Bianco
- Istituto Agrario San Michele all'Adige Research and Innovation Centre, Foundation Edmund Mach, Trento, Italy
| | - Stefano Toppo
- Department of Molecular Medicine, University of Padova, Padova, Italy.
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Barzon L, Papa A, Lavezzo E, Franchin E, Pacenti M, Sinigaglia A, Masi G, Trevisan M, Squarzon L, Toppo S, Papadopoulou E, Nowotny N, Ulbert S, Piralla A, Rovida F, Baldanti F, Percivalle E, Palù G. Phylogenetic characterization of Central/Southern European lineage 2 West Nile virus: analysis of human outbreaks in Italy and Greece, 2013-2014. Clin Microbiol Infect 2015; 21:1122.e1-10. [PMID: 26235197 DOI: 10.1016/j.cmi.2015.07.018] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2015] [Revised: 06/29/2015] [Accepted: 07/23/2015] [Indexed: 01/10/2023]
Abstract
In recent years, West Nile virus (WNV) lineage 2 has been spreading and causing disease outbreaks in humans and animals in Europe. In order to characterize viral diversity, we performed full-length genome sequencing of WNV lineage 2 from human samples collected during outbreaks in Italy and Greece in 2013 and 2014. Phylogenetic analysis showed that these WNV lineage 2 genomes belonged to a monophyletic clade derived from a single introduction into Europe of the prototype Hungarian strain. Correlation of phylogenetic data with geospatial information showed geographical clustering of WNV genome sequences both in Italy and in Greece, indicating that the virus had evolved and diverged during its dispersal in Europe, leading to the emergence of novel genotypes, as it adapted to local ecological niches. These genotypes carried divergent conserved amino acid substitutions, which might have been relevant for viral adaptation, as suggested by selection pressure analysis and in silico and experimental modelling of sequence changes. In conclusion, the results of this study provide further information on WNV lineage 2 transmission dynamics in Europe, and emphasize the need for WNV surveillance activities to monitor viral evolution and diversity.
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Affiliation(s)
- L Barzon
- Department of Molecular Medicine, University of Padova, Padova, Italy; Microbiology and Virology Unit, Padova University Hospital, Padova, Italy.
| | - A Papa
- National Reference Centre for Arboviruses, Department of Microbiology, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - E Lavezzo
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - E Franchin
- Department of Molecular Medicine, University of Padova, Padova, Italy; Microbiology and Virology Unit, Padova University Hospital, Padova, Italy
| | - M Pacenti
- Microbiology and Virology Unit, Padova University Hospital, Padova, Italy
| | - A Sinigaglia
- IRCCS-IOV Istituto Oncologico Veneto, Padova, Italy
| | - G Masi
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - M Trevisan
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - L Squarzon
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - S Toppo
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - E Papadopoulou
- National Reference Centre for Arboviruses, Department of Microbiology, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - N Nowotny
- Institute of Virology, University of Veterinary Medicine, Vienna, Austria; Department of Microbiology and Immunology, College of Medicine and Health Sciences, Sultan Qaboos University, Muscat, Oman
| | - S Ulbert
- Department of Immunology, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany
| | - A Piralla
- Molecular Virology Unit, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - F Rovida
- Molecular Virology Unit, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - F Baldanti
- Molecular Virology Unit, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy; Department of Clinical Sciences, Surgery, Diagnostics and Paediatrics, University of Pavia, Pavia, Italy
| | - E Percivalle
- Molecular Virology Unit, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - G Palù
- Department of Molecular Medicine, University of Padova, Padova, Italy; Microbiology and Virology Unit, Padova University Hospital, Padova, Italy
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Sinigaglia A, Lavezzo E, Trevisan M, Sanavia T, Di Camillo B, Peta E, Scarpa M, Castagliuolo I, Guido M, Sarcognato S, Cappellesso R, Fassina A, Cardin R, Farinati F, Palù G, Barzon L. Changes in microRNA expression during disease progression in patients with chronic viral hepatitis. Liver Int 2015; 35:1324-33. [PMID: 25417901 DOI: 10.1111/liv.12737] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/05/2014] [Accepted: 11/10/2014] [Indexed: 12/16/2022]
Abstract
BACKGROUND & AIMS MicroRNAs (miRNAs) have been involved in hepatocarcinogenesis, but little is known on their role in the progression of chronic viral hepatitis. Aim of this study was to identify miRNA signatures associated with stages of disease progression in patients with chronic viral hepatitis. METHODS MiRNA expression profile was investigated in liver biopsies from patients with chronic viral hepatitis and correlated with clinical, virological and histopathological features. Relevant miRNAs were further investigated. RESULTS Most of the significant changes in miRNA expression were associated with liver fibrosis stages and included the significant up-regulation of a group of miRNAs that were demonstrated to target the master regulators of epithelial-mesenchymal transition ZEB1 and ZEB2 and involved in the preservation of epithelial cell differentiation, but also in cell proliferation and fibrogenesis. In agreement with miRNA data, immunostaining of liver biopsies showed that expression of the epithelial marker E-cadherin was maintained in severe fibrosis/cirrhosis while expression of ZEBs and other markers of epithelial-mesenchymal transition were low or absent. Severe liver fibrosis was also significantly associated with the down-regulation of miRNAs with antiproliferative and tumour suppressor activity. Similar changes in miRNA and target gene expression were demonstrated along with disease progression in a mouse model of carbon tetrachloride (CCl4)-induced liver fibrosis, suggesting that they might represent a general response to liver injury. CONCLUSION Chronic viral hepatitis progression is associated with the activation of miRNA pathways that promote cell proliferation and fibrogenesis, but preserve the differentiated hepatocyte phenotype.
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Affiliation(s)
- Alessandro Sinigaglia
- Department of Molecular Medicine, University of Padova, Padova, Italy; IOV Istituto Oncologico Veneto, Padova, Italy
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Cardin R, Piciocchi M, Sinigaglia A, Lavezzo E, Bortolami M, Kotsafti A, Cillo U, Zanus G, Mescoli C, Rugge M, Farinati F. Erratum to: Oxidative DNA damage correlates with cell immortalization and mir-92 expression in hepatocellular carcinoma. BMC Cancer 2014. [PMCID: PMC3999349 DOI: 10.1186/1471-2407-14-284] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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Fallico L, Couvin D, Peracchi M, Pascarella M, Franchin E, Lavezzo E, Rassu M, Manganelli R, Rastogi N, Palù G. Four year longitudinal study of Mycobacterium tuberculosis complex isolates in a region of North-Eastern Italy. Infection, Genetics and Evolution 2014; 26:58-64. [DOI: 10.1016/j.meegid.2014.05.004] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2014] [Revised: 04/30/2014] [Accepted: 05/04/2014] [Indexed: 01/31/2023]
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Falda M, Fontana P, Barzon L, Toppo S, Lavezzo E. keeSeek: searching distant non-existing words in genomes for PCR-based applications. ACTA ACUST UNITED AC 2014; 30:2662-4. [PMID: 24867942 DOI: 10.1093/bioinformatics/btu312] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
UNLABELLED The search for short words that are absent in the genome of one or more organisms (neverwords, also known as nullomers) is attracting growing interest because of the impact they may have in recent molecular biology applications. keeSeek is able to find absent sequences with primer-like features, which can be used as unique labels for exogenously inserted DNA fragments to recover their exact position into the genome using PCR techniques. The main differences with respect to previously developed tools for neverwords generation are (i) calculation of the distance from the reference genome, in terms of number of mismatches, and selection of the most distant sequences that will have a low probability to anneal unspecifically; (ii) application of a series of filters to discard candidates not suitable to be used as PCR primers. KeeSeek has been implemented in C++ and CUDA (Compute Unified Device Architecture) to work in a General-Purpose Computing on Graphics Processing Units (GPGPU) environment. AVAILABILITY AND IMPLEMENTATION Freely available under the Q Public License at http://www.medcomp.medicina.unipd.it/main_site/doku.php?id=keeseek.
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Affiliation(s)
- Marco Falda
- Department of Molecular Medicine, University of Padova, Padova, I-35131, Italy and Department of Computational Biology, Edmund Mach Foundation, S. Michele All'Adige, I-38010 (TN), Italy
| | - Paolo Fontana
- Department of Molecular Medicine, University of Padova, Padova, I-35131, Italy and Department of Computational Biology, Edmund Mach Foundation, S. Michele All'Adige, I-38010 (TN), Italy
| | - Luisa Barzon
- Department of Molecular Medicine, University of Padova, Padova, I-35131, Italy and Department of Computational Biology, Edmund Mach Foundation, S. Michele All'Adige, I-38010 (TN), Italy
| | - Stefano Toppo
- Department of Molecular Medicine, University of Padova, Padova, I-35131, Italy and Department of Computational Biology, Edmund Mach Foundation, S. Michele All'Adige, I-38010 (TN), Italy
| | - Enrico Lavezzo
- Department of Molecular Medicine, University of Padova, Padova, I-35131, Italy and Department of Computational Biology, Edmund Mach Foundation, S. Michele All'Adige, I-38010 (TN), Italy
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Cardin R, Piciocchi M, Bortolami M, Kotsafti A, Barzon L, Lavezzo E, Sinigaglia A, Rodriguez-Castro KI, Rugge M, Farinati F. Oxidative damage in the progression of chronic liver disease to hepatocellular carcinoma: An intricate pathway. World J Gastroenterol 2014; 20:3078-3086. [PMID: 24696595 PMCID: PMC3964380 DOI: 10.3748/wjg.v20.i12.3078] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2013] [Revised: 11/13/2013] [Accepted: 01/06/2014] [Indexed: 02/06/2023] Open
Abstract
The histo-pathologic and molecular mechanisms leading to initiation and progression of hepatocellular carcinoma (HCC) are still ill-defined; however, there is increasing evidence that the gradual accumulation of mutations, genetic and epigenetic changes which occur in preneoplastic hepatocytes results in the development of dysplastic foci, nodules, and finally, overt HCC. As well as many other neoplasias, liver cancer is considered an “inflammatory cancer”, arising from a context of inflammation, and characterized by inflammation-related mechanisms that favor tumor cell survival, proliferation, and invasion. Molecular mechanisms that link inflammation and neoplasia have been widely investigated, and it has been well established that inflammatory cells recruited at these sites with ongoing inflammatory activity release chemokines that enhance the production of reactive oxygen species. The latter, in turn, probably have a major pathogenic role in the continuum starting from hepatitis followed by chronic inflammation, and ultimately leading to cancer. The relationship amongst chronic liver injury, free radical production, and development of HCC is explored in the present review, particularly in the light of the complex network that involves oxidative DNA damage, cytokine synthesis, telomere dysfunction, and microRNA regulation.
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Finotello F, Lavezzo E, Bianco L, Barzon L, Mazzon P, Fontana P, Toppo S, Di Camillo B. Reducing bias in RNA sequencing data: a novel approach to compute counts. BMC Bioinformatics 2014; 15 Suppl 1:S7. [PMID: 24564404 PMCID: PMC4016203 DOI: 10.1186/1471-2105-15-s1-s7] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Background In the last decade, Next-Generation Sequencing technologies have been extensively applied to quantitative transcriptomics, making RNA sequencing a valuable alternative to microarrays for measuring and comparing gene transcription levels. Although several methods have been proposed to provide an unbiased estimate of transcript abundances through data normalization, all of them are based on an initial count of the total number of reads mapping on each transcript. This procedure, in principle robust to random noise, is actually error-prone if reads are not uniformly distributed along sequences, as happens indeed due to sequencing errors and ambiguity in read mapping. Here we propose a new approach, called maxcounts, to quantify the expression assigned to an exon as the maximum of its per-base counts, and we assess its performance in comparison with the standard approach described above, which considers the total number of reads aligned to an exon. The two measures are compared using multiple data sets and considering several evaluation criteria: independence from gene-specific covariates, such as exon length and GC-content, accuracy and precision in the quantification of true concentrations and robustness of measurements to variations of alignments quality. Results Both measures show high accuracy and low dependency on GC-content. However, maxcounts expression quantification is less biased towards long exons with respect to the standard approach. Moreover, it shows lower technical variability at low expressions and is more robust to variations in the quality of alignments. Conclusions In summary, we confirm that counts computed with the standard approach depend on the length of the feature they are summarized on, and are sensitive to the non-uniform distribution of reads along transcripts. On the opposite, maxcounts are robust to biases due to the non-uniformity distribution of reads and are characterized by a lower technical variability. Hence, we propose maxcounts as an alternative approach for quantitative RNA-sequencing applications.
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Barzon L, Pacenti M, Franchin E, Pagni S, Lavezzo E, Squarzon L, Martello T, Russo F, Nicoletti L, Rezza G, Castilletti C, Capobianchi MR, Salcuni P, Cattai M, Cusinato R, Palù G. Large human outbreak of West Nile virus infection in north-eastern Italy in 2012. Viruses 2013; 5:2825-39. [PMID: 24284876 PMCID: PMC3856417 DOI: 10.3390/v5112825] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2013] [Revised: 11/20/2013] [Accepted: 11/20/2013] [Indexed: 11/16/2022] Open
Abstract
Human cases of West Nile virus (WNV) disease have been reported in Italy since 2008. So far, most cases have been identified in north-eastern Italy, where, in 2012, the largest outbreak of WNV infection ever recorded in Italy occurred. Most cases of the 2012 outbreak were identified in the Veneto region, where a special surveillance plan for West Nile fever was in place. In this outbreak, 25 cases of West Nile neuroinvasive disease and 17 cases of fever were confirmed. In addition, 14 WNV RNA-positive blood donors were identified by screening of blood and organ donations and two cases of asymptomatic infection were diagnosed by active surveillance of subjects at risk of WNV exposure. Two cases of death due to WNND were reported. Molecular testing demonstrated the presence of WNV lineage 1 in all WNV RNA-positive patients and, in 15 cases, infection by the novel Livenza strain was ascertained. Surveillance in other Italian regions notified one case of neuroinvasive disease in the south of Italy and two cases in Sardinia. Integrated surveillance for WNV infection remains a public health priority in Italy and vector control activities have been strengthened in areas of WNV circulation.
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Affiliation(s)
- Luisa Barzon
- Department of Molecular Medicine, University of Padova, Padova I-35121, Italy; E-Mails: (E.F.); (S.P.); (E.L.); (L.S.); (T.M.)
- Regional Reference Laboratory for Infectious Diseases, Microbiology and Virology Unit, Padova University Hospital, Padova I-35128, Italy; E-Mails: (M.P.); (M.C.); (R.C.)
- Authors to whom correspondence should be addressed; E-Mails: (L.B.); (G.P.); Tel.: +39-049-821-8946 (L.B.); Fax: +39-049-827-2355 (L.B.); Tel.: +39-049-827-2350 (G.P.); Fax: +39-049-827-2355 (G.P.)
| | - Monia Pacenti
- Regional Reference Laboratory for Infectious Diseases, Microbiology and Virology Unit, Padova University Hospital, Padova I-35128, Italy; E-Mails: (M.P.); (M.C.); (R.C.)
| | - Elisa Franchin
- Department of Molecular Medicine, University of Padova, Padova I-35121, Italy; E-Mails: (E.F.); (S.P.); (E.L.); (L.S.); (T.M.)
- Regional Reference Laboratory for Infectious Diseases, Microbiology and Virology Unit, Padova University Hospital, Padova I-35128, Italy; E-Mails: (M.P.); (M.C.); (R.C.)
| | - Silvana Pagni
- Department of Molecular Medicine, University of Padova, Padova I-35121, Italy; E-Mails: (E.F.); (S.P.); (E.L.); (L.S.); (T.M.)
- Regional Reference Laboratory for Infectious Diseases, Microbiology and Virology Unit, Padova University Hospital, Padova I-35128, Italy; E-Mails: (M.P.); (M.C.); (R.C.)
| | - Enrico Lavezzo
- Department of Molecular Medicine, University of Padova, Padova I-35121, Italy; E-Mails: (E.F.); (S.P.); (E.L.); (L.S.); (T.M.)
| | - Laura Squarzon
- Department of Molecular Medicine, University of Padova, Padova I-35121, Italy; E-Mails: (E.F.); (S.P.); (E.L.); (L.S.); (T.M.)
| | - Thomas Martello
- Department of Molecular Medicine, University of Padova, Padova I-35121, Italy; E-Mails: (E.F.); (S.P.); (E.L.); (L.S.); (T.M.)
| | - Francesca Russo
- Department of Public Health and Screening, Veneto Region, Venice I-30123, Italy; E-Mail:
| | - Loredana Nicoletti
- Department of Infectious, Parasitic and Immune-mediated Diseases, National Institute of Health (Istituto Superiore di Sanità, ISS), Rome I-00161, Italy; E-Mails: (L.N.); (G.R.)
| | - Giovanni Rezza
- Department of Infectious, Parasitic and Immune-mediated Diseases, National Institute of Health (Istituto Superiore di Sanità, ISS), Rome I-00161, Italy; E-Mails: (L.N.); (G.R.)
| | - Concetta Castilletti
- National Institute for Infectious Diseases (INMI) “L. Spallanzani”, Rome I-00149, Italy; E-Mails: (C.C.); (M.R.C.)
| | - Maria Rosaria Capobianchi
- National Institute for Infectious Diseases (INMI) “L. Spallanzani”, Rome I-00149, Italy; E-Mails: (C.C.); (M.R.C.)
| | - Pasquale Salcuni
- Department of Prevention and Communication, Ministry of Health, Rome I-00144, Italy; E-Mail:
| | - Margherita Cattai
- Regional Reference Laboratory for Infectious Diseases, Microbiology and Virology Unit, Padova University Hospital, Padova I-35128, Italy; E-Mails: (M.P.); (M.C.); (R.C.)
| | - Riccardo Cusinato
- Regional Reference Laboratory for Infectious Diseases, Microbiology and Virology Unit, Padova University Hospital, Padova I-35128, Italy; E-Mails: (M.P.); (M.C.); (R.C.)
| | - Giorgio Palù
- Department of Molecular Medicine, University of Padova, Padova I-35121, Italy; E-Mails: (E.F.); (S.P.); (E.L.); (L.S.); (T.M.)
- Regional Reference Laboratory for Infectious Diseases, Microbiology and Virology Unit, Padova University Hospital, Padova I-35128, Italy; E-Mails: (M.P.); (M.C.); (R.C.)
- Authors to whom correspondence should be addressed; E-Mails: (L.B.); (G.P.); Tel.: +39-049-821-8946 (L.B.); Fax: +39-049-827-2355 (L.B.); Tel.: +39-049-827-2350 (G.P.); Fax: +39-049-827-2355 (G.P.)
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Lavezzo E, Toppo S, Franchin E, Di Camillo B, Finotello F, Falda M, Manganelli R, Palù G, Barzon L. Genomic comparative analysis and gene function prediction in infectious diseases: application to the investigation of a meningitis outbreak. BMC Infect Dis 2013; 13:554. [PMID: 24252229 PMCID: PMC4225559 DOI: 10.1186/1471-2334-13-554] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2013] [Accepted: 11/13/2013] [Indexed: 11/26/2022] Open
Abstract
Background Next generation sequencing (NGS) is being increasingly used for the detection and characterization of pathogens during outbreaks. This technology allows rapid sequencing of pathogen full genomes, useful not only for accurate genotyping and molecular epidemiology, but also for identification of drug resistance and virulence traits. Methods In this study, an approach based on whole genome sequencing by NGS, comparative genomics, and gene function prediction was set up and retrospectively applied for the investigation of two N. meningitidis serogroup C isolates collected from a cluster of meningococcal disease, characterized by a high fatality rate. Results According to conventional molecular typing methods, all the isolates had the same typing results and were classified as outbreak isolates within the same N. meningitidis sequence type ST-11, while full genome sequencing demonstrated subtle genetic differences between the isolates. Looking for these specific regions by means of 9 PCR and cycle sequencing assays in other 7 isolates allowed distinguishing outbreak cases from unrelated cases. Comparative genomics and gene function prediction analyses between outbreak isolates and a set of reference N. meningitidis genomes led to the identification of differences in gene content that could be relevant for pathogenesis. Most genetic changes occurred in the capsule locus and were consistent with recombination and horizontal acquisition of a set of genes involved in capsule biosynthesis. Conclusions This study showed the added value given by whole genome sequencing by NGS over conventional sequence-based typing methods in the investigation of an outbreak. Routine application of this technology in clinical microbiology will significantly improve methods for molecular epidemiology and surveillance of infectious disease and provide a bulk of data useful to improve our understanding of pathogens biology.
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Affiliation(s)
- Enrico Lavezzo
- Department of Molecular Medicine, University of Padova, Padova, Italy.
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Militello V, Lavezzo E, Costanzi G, Franchin E, Di Camillo B, Toppo S, Palù G, Barzon L. Accurate human papillomavirus genotyping by 454 pyrosequencing. Clin Microbiol Infect 2013; 19:E428-34. [DOI: 10.1111/1469-0691.12219] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2012] [Revised: 02/13/2013] [Accepted: 03/05/2013] [Indexed: 11/28/2022]
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Barzon L, Papa A, Pacenti M, Franchin E, Lavezzo E, Squarzon L, Masi G, Martello T, Testa T, Cusinato R, Palù G. Genome sequencing of West Nile Virus from human cases in Greece, 2012. Viruses 2013; 5:2311-9. [PMID: 24064795 PMCID: PMC3798904 DOI: 10.3390/v5092311] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2013] [Revised: 09/18/2013] [Accepted: 09/20/2013] [Indexed: 01/14/2023] Open
Abstract
A West Nile Virus (WNV) lineage 2 strain, named Nea Santa-Greece-2010, has been demonstrated to be responsible for the large outbreaks of neuroinvasive disease (WNND) that have been occurring in Greece since 2010, based on sequence similarities of viral isolates identified between 2010–2012. However, knowledge on the evolution of this strain is scarce because only partial WNV genome sequences are available from Greece. The aim of this study was to get the complete genome sequence of WNV from patients with infection. To this aim, plasma and urine samples collected during the 2012 Greek outbreak were retrospectively investigated. Full WNV genome sequence was obtained from a patient with WNND. The genome had 99.7% sequence identity to Nea Santa, higher than to other related WNV lineage 2 strains, and five amino acid changes apparently not relevant for viral pathogenicity or fitness. In addition, infection by WNV lineage 2 was confirmed in additional nine patients with WNND; in three of them the infection with WNV Nea Santa was demonstrated by sequencing. In conclusion, this study characterized for the first time a WNV full genome from a patient with WNND from Greece, demonstrated the persistence of the Nea Santa strain, and suggested that the virus might have locally evolved.
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Affiliation(s)
- Luisa Barzon
- Department of Molecular Medicine, University of Padova, 35122 Padova, Italy; E-Mails: (L.B.); (E.F.); (E.L.); (L.S.); (G.M.); (T.M.)
- Microbiology and Virology Unit, Padova University Hospital, 35122 Padova, Italy; E-Mails: (M.P.); (R.C.)
- Authors to whom correspondence should be addressed; E-Mails: (L.B.); (G.P.); Tel.: +39-049-821-8946 (L.B.); +39-049-827-2350 (G.P.); Fax: +39-049-827-2355 (L.B.); +39-049-827-2355 (G.P.)
| | - Anna Papa
- Department of Microbiology, Medical School, Aristotle University of Thessaloniki, Thessaloniki 54621, Greece; E-Mails: (A.P.); (T.T.)
| | - Monia Pacenti
- Microbiology and Virology Unit, Padova University Hospital, 35122 Padova, Italy; E-Mails: (M.P.); (R.C.)
| | - Elisa Franchin
- Department of Molecular Medicine, University of Padova, 35122 Padova, Italy; E-Mails: (L.B.); (E.F.); (E.L.); (L.S.); (G.M.); (T.M.)
- Microbiology and Virology Unit, Padova University Hospital, 35122 Padova, Italy; E-Mails: (M.P.); (R.C.)
| | - Enrico Lavezzo
- Department of Molecular Medicine, University of Padova, 35122 Padova, Italy; E-Mails: (L.B.); (E.F.); (E.L.); (L.S.); (G.M.); (T.M.)
| | - Laura Squarzon
- Department of Molecular Medicine, University of Padova, 35122 Padova, Italy; E-Mails: (L.B.); (E.F.); (E.L.); (L.S.); (G.M.); (T.M.)
| | - Giulia Masi
- Department of Molecular Medicine, University of Padova, 35122 Padova, Italy; E-Mails: (L.B.); (E.F.); (E.L.); (L.S.); (G.M.); (T.M.)
| | - Thomas Martello
- Department of Molecular Medicine, University of Padova, 35122 Padova, Italy; E-Mails: (L.B.); (E.F.); (E.L.); (L.S.); (G.M.); (T.M.)
| | - Theodolinta Testa
- Department of Microbiology, Medical School, Aristotle University of Thessaloniki, Thessaloniki 54621, Greece; E-Mails: (A.P.); (T.T.)
| | - Riccardo Cusinato
- Microbiology and Virology Unit, Padova University Hospital, 35122 Padova, Italy; E-Mails: (M.P.); (R.C.)
| | - Giorgio Palù
- Department of Molecular Medicine, University of Padova, 35122 Padova, Italy; E-Mails: (L.B.); (E.F.); (E.L.); (L.S.); (G.M.); (T.M.)
- Microbiology and Virology Unit, Padova University Hospital, 35122 Padova, Italy; E-Mails: (M.P.); (R.C.)
- Authors to whom correspondence should be addressed; E-Mails: (L.B.); (G.P.); Tel.: +39-049-821-8946 (L.B.); +39-049-827-2350 (G.P.); Fax: +39-049-827-2355 (L.B.); +39-049-827-2355 (G.P.)
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Barzon L, Pacenti M, Franchin E, Lavezzo E, Masi G, Squarzon L, Pagni S, Toppo S, Russo F, Cattai M, Cusinato R, Palu G. Whole genome sequencing and phylogenetic analysis of West Nile virus lineage 1 and lineage 2 from human cases of infection, Italy, August 2013. ACTA ACUST UNITED AC 2013; 18. [PMID: 24084339 DOI: 10.2807/1560-7917.es2013.18.38.20591] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
A human outbreak of West Nile virus (WNV) infection caused by WNV lineage 2 is ongoing in northern Italy. Analysis of six WNV genome sequences obtained from clinical specimens demonstrated similarities with strains circulating in central Europe and Greece and the presence of unique amino acid changes that identify a new viral strain. In addition, WNV lineage 1 Livenza, responsible for a large outbreak in north-eastern Italy in 2012, was fully sequenced from a blood donor during this 2013 outbreak.
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Affiliation(s)
- L Barzon
- Department of Molecular Medicine, University of Padova, Padova, Italy
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Barzon L, Lavezzo E, Costanzi G, Franchin E, Toppo S, Palù G. Next-generation sequencing technologies in diagnostic virology. J Clin Virol 2013; 58:346-50. [PMID: 23523339 DOI: 10.1016/j.jcv.2013.03.003] [Citation(s) in RCA: 74] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2012] [Revised: 03/01/2013] [Accepted: 03/02/2013] [Indexed: 11/15/2022]
Abstract
The data deluge produced by next-generation sequencing (NGS) technologies is an appealing feature for clinical virologists that are involved in the diagnosis of emerging viral infections, molecular epidemiology of viral pathogens, drug-resistance testing, and also like to do some basic and clinical research. Indeed, NGS platforms are being implemented in many clinical and research laboratories, as the costs of these platforms are progressively decreasing. We provide here some suggestions for virologists who are planning to implement a NGS platform in their clinical laboratory and an overview on the potential applications of these technologies in diagnostic virology.
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Affiliation(s)
- Luisa Barzon
- Department of Molecular Medicine, University of Padova, Via A. Gabelli 63, I-35121 Padova, Italy.
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Radivojac P, Clark WT, Oron TR, Schnoes AM, Wittkop T, Sokolov A, Graim K, Funk C, Verspoor K, Ben-Hur A, Pandey G, Yunes JM, Talwalkar AS, Repo S, Souza ML, Piovesan D, Casadio R, Wang Z, Cheng J, Fang H, Gough J, Koskinen P, Törönen P, Nokso-Koivisto J, Holm L, Cozzetto D, Buchan DWA, Bryson K, Jones DT, Limaye B, Inamdar H, Datta A, Manjari SK, Joshi R, Chitale M, Kihara D, Lisewski AM, Erdin S, Venner E, Lichtarge O, Rentzsch R, Yang H, Romero AE, Bhat P, Paccanaro A, Hamp T, Kaßner R, Seemayer S, Vicedo E, Schaefer C, Achten D, Auer F, Boehm A, Braun T, Hecht M, Heron M, Hönigschmid P, Hopf TA, Kaufmann S, Kiening M, Krompass D, Landerer C, Mahlich Y, Roos M, Björne J, Salakoski T, Wong A, Shatkay H, Gatzmann F, Sommer I, Wass MN, Sternberg MJE, Škunca N, Supek F, Bošnjak M, Panov P, Džeroski S, Šmuc T, Kourmpetis YAI, van Dijk ADJ, ter Braak CJF, Zhou Y, Gong Q, Dong X, Tian W, Falda M, Fontana P, Lavezzo E, Di Camillo B, Toppo S, Lan L, Djuric N, Guo Y, Vucetic S, Bairoch A, Linial M, Babbitt PC, Brenner SE, Orengo C, Rost B, Mooney SD, Friedberg I. A large-scale evaluation of computational protein function prediction. Nat Methods 2013; 10:221-7. [PMID: 23353650 PMCID: PMC3584181 DOI: 10.1038/nmeth.2340] [Citation(s) in RCA: 564] [Impact Index Per Article: 51.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2012] [Accepted: 12/10/2012] [Indexed: 01/03/2023]
Abstract
A report on the results of the first large-scale community-based critical assessment of protein function annotation (CAFA) experiment. 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.
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Affiliation(s)
- Predrag Radivojac
- School of Informatics and Computing, Indiana University, Bloomington, Indiana, USA
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Barzon L, Pacenti M, Franchin E, Squarzon L, Lavezzo E, Toppo S, Martello T, Cattai M, Cusinato R, Palù G. Novel West Nile virus lineage 1a full genome sequences from human cases of infection in north-eastern Italy, 2011. Clin Microbiol Infect 2012; 18:E541-4. [DOI: 10.1111/1469-0691.12001] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
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