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Tharanga S, Ünlü ES, Hu Y, Sjaugi MF, Çelik MA, Hekimoğlu H, Miotto O, Öncel MM, Khan AM. DiMA: sequence diversity dynamics analyser for viruses. Brief Bioinform 2024; 26:bbae607. [PMID: 39592151 PMCID: PMC11596295 DOI: 10.1093/bib/bbae607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2024] [Revised: 09/22/2024] [Accepted: 11/13/2024] [Indexed: 11/28/2024] Open
Abstract
Sequence diversity is one of the major challenges in the design of diagnostic, prophylactic, and therapeutic interventions against viruses. DiMA is a novel tool that is big data-ready and designed to facilitate the dissection of sequence diversity dynamics for viruses. DiMA stands out from other diversity analysis tools by offering various unique features. DiMA provides a quantitative overview of sequence (DNA/RNA/protein) diversity by use of Shannon's entropy corrected for size bias, applied via a user-defined k-mer sliding window to an input alignment file, and each k-mer position is dissected to various diversity motifs. The motifs are defined based on the probability of distinct sequences at a given k-mer alignment position, whereby an index is the predominant sequence, while all the others are (total) variants to the index. The total variants are sub-classified into the major (most common) variant, minor variants (occurring more than once and of incidence lower than the major), and the unique (singleton) variants. DiMA allows user-defined, sequence metadata enrichment for analyses of the motifs. The application of DiMA was demonstrated for the alignment data of the relatively conserved Spike protein (2,106,985 sequences) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the relatively highly diverse pol gene (2637) of the human immunodeficiency virus-1 (HIV-1). The tool is publicly available as a web server (https://dima.bezmialem.edu.tr), as a Python library (via PyPi) and as a command line client (via GitHub).
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Affiliation(s)
- Shan Tharanga
- Centre for Bioinformatics, School of Data Sciences, Perdana University, MAEPS Building, Jalan MAEPS Perdana, Serdang, Kuala Lumpur 50490, Malaysia
| | - Eyyüb Selim Ünlü
- Istanbul Faculty of Medicine, Istanbul University, Turgut Özal Millet St, Topkapi, Istanbul 34093, Türkiye
- Genome Surveillance Unit, Wellcome Sanger Institute, Mill Ln, Hinxton, Saffron Walden CB10 1SA, United Kingdom
| | - Yongli Hu
- Centre for Bioinformatics, School of Data Sciences, Perdana University, MAEPS Building, Jalan MAEPS Perdana, Serdang, Kuala Lumpur 50490, Malaysia
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597, Singapore
| | - Muhammad Farhan Sjaugi
- Centre for Bioinformatics, School of Data Sciences, Perdana University, MAEPS Building, Jalan MAEPS Perdana, Serdang, Kuala Lumpur 50490, Malaysia
| | - Muhammet A Çelik
- Celik Sarayı, Yeni Elektrik Santral St. No:29/2, Meram, Konya 42090, Türkiye
| | - Hilal Hekimoğlu
- Beykoz Institute of Life Sciences and Biotechnology, Bezmialem Vakif University, Ali Ihsan Kalmaz St., No.10 Beykoz, Istanbul 34820, Türkiye
| | - Olivo Miotto
- Nuffield Department of Clinical Medicine, University of Oxford, Old Road, Old Road Campus, Oxford OX3 7LF, United Kingdom
- Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, 420/6 Ratchawithi Rd., Ratchathewi District, Bangkok 10400, Thailand
| | - Muhammed Miran Öncel
- Beykoz Institute of Life Sciences and Biotechnology, Bezmialem Vakif University, Ali Ihsan Kalmaz St., No.10 Beykoz, Istanbul 34820, Türkiye
| | - Asif M Khan
- Centre for Bioinformatics, School of Data Sciences, Perdana University, MAEPS Building, Jalan MAEPS Perdana, Serdang, Kuala Lumpur 50490, Malaysia
- Beykoz Institute of Life Sciences and Biotechnology, Bezmialem Vakif University, Ali Ihsan Kalmaz St., No.10 Beykoz, Istanbul 34820, Türkiye
- College of Computing and Information Technology, University of Doha for Science and Technology, Jelaiah Street, Duhail North, Doha, Qatar
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de Carvalho Lima EN, Octaviano ALM, Piqueira JRC, Diaz RS, Justo JF. Coronavirus and Carbon Nanotubes: Seeking Immunological Relationships to Discover Immunotherapeutic Possibilities. Int J Nanomedicine 2022; 17:751-781. [PMID: 35241912 PMCID: PMC8887185 DOI: 10.2147/ijn.s341890] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 01/31/2022] [Indexed: 12/11/2022] Open
Abstract
Since December 2019, the world has faced an unprecedented pandemic crisis due to a new coronavirus disease, coronavirus disease-2019 (COVID-19), which has instigated intensive studies on prevention and treatment possibilities. Here, we investigate the relationships between the immune activation induced by three coronaviruses associated with recent outbreaks, with special attention to SARS-CoV-2, the causative agent of COVID-19, and the immune activation induced by carbon nanotubes (CNTs) to understand the points of convergence in immune induction and modulation. Evidence suggests that CNTs are among the most promising materials for use as immunotherapeutic agents. Therefore, this investigation explores new possibilities of effective immunotherapies for COVID-19. This study aimed to raise interest and knowledge about the use of CNTs as immunotherapeutic agents in coronavirus treatment. Thus, we summarize the most important immunological aspects of various coronavirus infections and describe key advances and challenges in using CNTs as immunotherapeutic agents against viral infections and the activation of the immune response induced by CNTs, which can shed light on the immunotherapeutic possibilities of CNTs.
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Affiliation(s)
- Elidamar Nunes de Carvalho Lima
- Telecommunication and Control Engineering Department, Polytechnic School of the University of São Paulo, São Paulo, Brazil
- Infectious Diseases Division, Department of Medicine, Federal University of São Paulo, São Paulo, Brazil
- Electronic Systems Engineering Department, Polytechnic School of the University of São Paulo, São Paulo, SP, CEP 05508-010, Brazil
| | - Ana Luiza Moraes Octaviano
- Telecommunication and Control Engineering Department, Polytechnic School of the University of São Paulo, São Paulo, Brazil
| | - José Roberto Castilho Piqueira
- Telecommunication and Control Engineering Department, Polytechnic School of the University of São Paulo, São Paulo, Brazil
| | - Ricardo Sobhie Diaz
- Infectious Diseases Division, Department of Medicine, Federal University of São Paulo, São Paulo, Brazil
| | - João Francisco Justo
- Electronic Systems Engineering Department, Polytechnic School of the University of São Paulo, São Paulo, SP, CEP 05508-010, Brazil
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Krishnan G S, Joshi A, Akhtar N, Kaushik V. Immunoinformatics designed T cell multi epitope dengue peptide vaccine derived from non structural proteome. Microb Pathog 2021; 150:104728. [PMID: 33400987 DOI: 10.1016/j.micpath.2020.104728] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2020] [Revised: 12/20/2020] [Accepted: 12/27/2020] [Indexed: 12/20/2022]
Abstract
Dengue viral disease has been reported as an Aedes aegypti mosquito-borne human disease and causing a severe global public health concern. In this study, immunoinformatics methods was deployed for crafting CTL T-cell epitopes as dengue vaccine candidates. The NS1 protein sequence of dengue serotype 1 strain retrieved from the protein database and T-cell epitopes (n = 85) were predicted by the artificial neural network. The conserved epitopes (n = 10) were predicted and selected for intensive computational analysis. The machine learning technique and quantitative matrix-based toxicity analysis assured nontoxic peptide selection. Hidden Markov Model derived Structural Alphabet (SA) based algorithm predicted the 3D molecular structure and all-atom structure of peptide ligand validated by Ramachandran-plot. Three-tier molecular docking approaches were used to predictthe peptide - HLA docking complex. Molecular dynamics (MD) simulation study confirmed the docking complex was stable in the time frame of 100ns. Population coverage analysis predicted the interaction epitope interaction with a particular population of HLA. These results concluded that the computationally designed HTLWSNGVL and FTTNIWLKL epitope peptides could be used as putative agents for the multi CTL T cell epitope vaccine. The vaccine protein sequence expression and translation were analyzed in the prokaryotic vector adapted by codon usage. Such in silico formulated CTL T-cell-based prophylactic vaccines could encourage the commercial development of dengue vaccines.
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Affiliation(s)
- Sunil Krishnan G
- Domain of Bioinformatics, School of Bio-Engineering and Bio-Sciences, Lovely Professional University, Punjab, India.
| | - Amit Joshi
- Domain of Bioinformatics, School of Bio-Engineering and Bio-Sciences, Lovely Professional University, Punjab, India.
| | - Nahid Akhtar
- Domain of Bioinformatics, School of Bio-Engineering and Bio-Sciences, Lovely Professional University, Punjab, India.
| | - Vikas Kaushik
- Domain of Bioinformatics, School of Bio-Engineering and Bio-Sciences, Lovely Professional University, Punjab, India.
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Conserved epitopes with high HLA-I population coverage are targets of CD8 + T cells associated with high IFN-γ responses against all dengue virus serotypes. Sci Rep 2020; 10:20497. [PMID: 33235334 PMCID: PMC7687909 DOI: 10.1038/s41598-020-77565-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2020] [Accepted: 11/03/2020] [Indexed: 12/15/2022] Open
Abstract
Cytotoxic CD8+ T cells are key for immune protection against viral infections. The breadth and cross-reactivity of these responses are important against rapidly mutating RNA viruses, such as dengue (DENV), yet how viral diversity affect T cell responses and their cross-reactivity against multiple variants of the virus remains poorly defined. In this study, an integrated analysis was performed to map experimentally validated CD8+ T cell epitopes onto the distribution of DENV genome sequences across the 4 serotypes worldwide. Despite the higher viral diversity observed within HLA-I restricted epitopes, mapping of 609 experimentally validated epitopes sequences on 3985 full-length viral genomes revealed 19 highly conserved epitopes across the four serotypes within the immunogenic regions of NS3, NS4B and NS5. These conserved epitopes were associated with a higher magnitude of IFN-γ response when compared to non-conserved epitopes and were restricted to 13 HLA class I genotypes, hence providing high coverage among human populations. Phylogeographic analyses showed that these epitopes are largely conserved in most of the endemic regions of the world, and with only some of these epitopes presenting distinct mutated variants circulating in South America and Asia.This study provides evidence for the existence of highly immunogenic and conserved epitopes across serotypes, which may impact design of new universal T-cell-inducing vaccine candidates that minimise detrimental effects of viral diversification and at the same time induce responses to a broad human population.
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Ahmed SF, Quadeer AA, Barton JP, McKay MR. Cross-serotypically conserved epitope recommendations for a universal T cell-based dengue vaccine. PLoS Negl Trop Dis 2020; 14:e0008676. [PMID: 32956362 PMCID: PMC7529213 DOI: 10.1371/journal.pntd.0008676] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2019] [Revised: 10/01/2020] [Accepted: 08/04/2020] [Indexed: 11/18/2022] Open
Abstract
Dengue virus (DENV)-associated disease is a growing threat to public health across the globe. Co-circulating as four different serotypes, DENV poses a unique challenge for vaccine design as immunity to one serotype predisposes a person to severe and potentially lethal disease upon infection from other serotypes. Recent experimental studies suggest that an effective vaccine against DENV should elicit a strong T cell response against all serotypes, which could be achieved by directing T cell responses toward cross-serotypically conserved epitopes while avoiding serotype-specific ones. Here, we used experimentally-determined DENV T cell epitopes and patient-derived DENV sequences to assess the cross-serotypic variability of the epitopes. We reveal a distinct near-binary pattern of epitope conservation across serotypes for a large number of DENV epitopes. Based on the conservation profile, we identify a set of 55 epitopes that are highly conserved in at least 3 serotypes. Most of the highly conserved epitopes lie in functionally important regions of DENV non-structural proteins. By considering the global distribution of human leukocyte antigen (HLA) alleles associated with these DENV epitopes, we identify a potentially robust subset of HLA class I and class II restricted epitopes that can serve as targets for a universal T cell-based vaccine against DENV while covering ~99% of the global population.
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Affiliation(s)
- Syed Faraz Ahmed
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, China
| | - Ahmed A. Quadeer
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, China
| | - John P. Barton
- Department of Physics and Astronomy, University of California, Riverside, California, United States of America
| | - Matthew R. McKay
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, China
- Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Hong Kong, China
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Waickman AT, Friberg H, Gargulak M, Kong A, Polhemus M, Endy T, Thomas SJ, Jarman RG, Currier JR. Assessing the Diversity and Stability of Cellular Immunity Generated in Response to the Candidate Live-Attenuated Dengue Virus Vaccine TAK-003. Front Immunol 2019; 10:1778. [PMID: 31417556 PMCID: PMC6684763 DOI: 10.3389/fimmu.2019.01778] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Accepted: 07/15/2019] [Indexed: 11/13/2022] Open
Abstract
The development of an efficacious DENV vaccine has been a long-standing public health priority. However, this effort has been complicated significantly due to the hazard presented by incomplete humoral immunity in mediating immune enhancement of infection and disease severity. Therefore, there is a significant need for DENV vaccine platforms capable of generating broad immune responses including durable cellular immunity, as well as novel analytical tools to assess the magnitude, diversity, and persistence of vaccine-elicited immunity. In this study, we demonstrate that a single dose of the recombinant, tetravalent, live-attenuated DENV vaccine TAK-003 elicits potent and durable cellular immunity against both the structural and non-structural proteins of all four DENV serotypes, which is maintained for at least 4 months post-immunization. Although not contained within the vaccine formulation, significant reactivity against the non-structural (NS) proteins of DENV-1,-3, and-4 is observed following vaccination, to an extent directly proportional to the magnitude of responses to the corresponding vaccine (DENV-2) components. Distinct, quantifiable, and durable patterns of DENV antigen reactivity can be observed in individuals following vaccination. Detailed epitope mapping of T cell reactivity against the DENV-2 proteome using a matrix of overlapping peptide pools demonstrated that TAK-003 elicits a broad response directed across the DENV-2 proteome, with focused reactivity against NS1 and NS3. We conclude that, as measured by an IFN-γ ELISPOT assay, a single dose of TAK-003 generates potent T cell-mediated immunity which is durable in magnitude and breadth through 4 months post-vaccination.
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Affiliation(s)
- Adam T Waickman
- Viral Diseases Branch, Walter Reed Army Institute of Research, Silver Spring, MA, United States
| | - Heather Friberg
- Viral Diseases Branch, Walter Reed Army Institute of Research, Silver Spring, MA, United States
| | - Morgan Gargulak
- Viral Diseases Branch, Walter Reed Army Institute of Research, Silver Spring, MA, United States
| | - Amanda Kong
- Viral Diseases Branch, Walter Reed Army Institute of Research, Silver Spring, MA, United States
| | - Mark Polhemus
- Department of Medicine, Upstate Medical University of New York, Syracuse, NY, United States
| | - Timothy Endy
- Department of Medicine, Upstate Medical University of New York, Syracuse, NY, United States
| | - Stephen J Thomas
- Viral Diseases Branch, Walter Reed Army Institute of Research, Silver Spring, MA, United States
| | - Richard G Jarman
- Viral Diseases Branch, Walter Reed Army Institute of Research, Silver Spring, MA, United States
| | - Jeffrey R Currier
- Viral Diseases Branch, Walter Reed Army Institute of Research, Silver Spring, MA, United States
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Huang YW, Lee CT, Wang TC, Kao YC, Yang CH, Lin YM, Huang KS. The Development of Peptide-based Antimicrobial Agents against Dengue Virus. Curr Protein Pept Sci 2018; 19:998-1010. [PMID: 29852867 PMCID: PMC6446661 DOI: 10.2174/1389203719666180531122724] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2018] [Revised: 04/20/2018] [Accepted: 05/25/2018] [Indexed: 11/22/2022]
Abstract
Dengue fever has become an imminent threat to international public health because of global warming and climate change. The World Health Organization proclaimed that more than 50% of the world's population is at risk of dengue virus (DENV) infection. Therefore, developing a clinically approved vaccine and effective therapeutic remedy for treating dengue fever is imperative. Peptide drug development has become a novel pharmaceutical research field. This article reviews various peptidesbased antimicrobial agents targeting three pathways involved in the DENV lifecycle. Specifically, they are peptide vaccines from immunomodulation, peptide drugs that inhibit virus entry, and peptide drugs that interfere with viral replication. Many antiviral peptide studies against DENV have been conducted in animal model trials, and progression to clinical trials for these promising peptide drugs is anticipated.
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Affiliation(s)
| | | | | | | | | | | | - Keng-Shiang Huang
- Address correspondence to this author at the School of Chinese Medicine for Post-Baccalaureate, I-Shou University, Kaohsiung, Taiwan;, Tel: +886-988-399-979; E-mail:
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Meza B, Ascencio F, Sierra-Beltrán AP, Torres J, Angulo C. A novel design of a multi-antigenic, multistage and multi-epitope vaccine against Helicobacter pylori: An in silico approach. INFECTION GENETICS AND EVOLUTION 2017; 49:309-317. [DOI: 10.1016/j.meegid.2017.02.007] [Citation(s) in RCA: 94] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2017] [Revised: 02/02/2017] [Accepted: 02/05/2017] [Indexed: 02/07/2023]
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Olsen LR, Simon C, Kudahl UJ, Bagger FO, Winther O, Reinherz EL, Zhang GL, Brusic V. A computational method for identification of vaccine targets from protein regions of conserved human leukocyte antigen binding. BMC Med Genomics 2015; 8 Suppl 4:S1. [PMID: 26679766 PMCID: PMC4682376 DOI: 10.1186/1755-8794-8-s4-s1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Background Computational methods for T cell-based vaccine target discovery focus on selection of highly conserved peptides identified across pathogen variants, followed by prediction of their binding of human leukocyte antigen molecules. However, experimental studies have shown that T cells often target diverse regions in highly variable viral pathogens and this diversity may need to be addressed through redefinition of suitable peptide targets. Methods We have developed a method for antigen assessment and target selection for polyvalent vaccines, with which we identified immune epitopes from variable regions, where all variants bind HLA. These regions, although variable, can thus be considered stable in terms of HLA binding and represent valuable vaccine targets. Results We applied this method to predict CD8+ T-cell targets in influenza A H7N9 hemagglutinin and significantly increased the number of potential vaccine targets compared to the number of targets discovered using the traditional approach where low-frequency peptides are excluded. Conclusions We developed a webserver with an intuitive visualization scheme for summarizing the T cell-based antigenic potential of any given protein or proteome using human leukocyte antigen binding predictions and made a web-accessible software implementation freely available at http://met-hilab.cbs.dtu.dk/blockcons/.
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Comber JD, Karabudak A, Huang X, Piazza PA, Marques ETA, Philip R. Dengue virus specific dual HLA binding T cell epitopes induce CD8+ T cell responses in seropositive individuals. Hum Vaccin Immunother 2015; 10:3531-43. [PMID: 25668665 DOI: 10.4161/21645515.2014.980210] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Dengue virus infects an estimated 300 million people each year and even more are at risk of becoming infected as the virus continues to spread into new areas. Despite the increase in viral prevalence, no anti-viral medications or vaccines are approved for treating or preventing infection. CD8+ T cell responses play a major role in viral clearance. Therefore, effective vaccines that induce a broad, multi-functional T cell response with substantial cross-reactivity between all virus serotypes can have major impacts on reducing infection rates and infection related complications. Here, we took an immunoproteomic approach to identify novel MHC class I restricted T cell epitopes presented by dengue virus infected cells, representing the natural and authentic targets of the T cell response. Using this approach we identified 4 novel MHC-I restricted epitopes: 2 with the binding motif for HLA-A24 molecules and 2 with both HLA-A2 and HLA-A24 binding motifs. These peptides were able to activate CD8+ T cell responses in both healthy, seronegative individuals and in seropositive individuals who have previously been infected with dengue virus. Importantly, the dual binding epitopes activated pre-existing T cell precursors in PBMCs obtained from both HLA-A2+ and HLA-A24+ seropositive individuals. Together, the data indicate that these epitopes are immunologically relevant T cell activating peptides presented on infected cells during a natural infection and therefore may serve as candidate antigens for the development of effective multi-serotype specific dengue virus vaccines.
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Simon C, Kudahl UJ, Sun J, Olsen LR, Zhang GL, Reinherz EL, Brusic V. FluKB: A Knowledge-Based System for Influenza Vaccine Target Discovery and Analysis of the Immunological Properties of Influenza Viruses. J Immunol Res 2015; 2015:380975. [PMID: 26504853 PMCID: PMC4609449 DOI: 10.1155/2015/380975] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2015] [Accepted: 03/12/2015] [Indexed: 01/01/2023] Open
Abstract
FluKB is a knowledge-based system focusing on data and analytical tools for influenza vaccine discovery. The main goal of FluKB is to provide access to curated influenza sequence and epitope data and enhance the analysis of influenza sequence diversity and the analysis of targets of immune responses. FluKB consists of more than 400,000 influenza protein sequences, known epitope data (357 verified T-cell epitopes, 685 HLA binders, and 16 naturally processed MHC ligands), and a collection of 28 influenza antibodies and their structurally defined B-cell epitopes. FluKB was built using a modular framework allowing the implementation of analytical workflows and includes standard search tools, such as keyword search and sequence similarity queries, as well as advanced tools for the analysis of sequence variability. The advanced analytical tools for vaccine discovery include visual mapping of T- and B-cell vaccine targets and assessment of neutralizing antibody coverage. FluKB supports the discovery of vaccine targets and the analysis of viral diversity and its implications for vaccine discovery as well as potential T-cell breadth and antibody cross neutralization involving multiple strains. FluKB is representation of a new generation of databases that integrates data, analytical tools, and analytical workflows that enable comprehensive analysis and automatic generation of analysis reports.
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Affiliation(s)
- Christian Simon
- Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, 2800 Lyngby, Denmark
- Department of Disease Systems Biology, Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Ulrich J. Kudahl
- Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, 2800 Lyngby, Denmark
- Cancer Vaccine Center, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Jing Sun
- Cancer Vaccine Center, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Lars Rønn Olsen
- Cancer Vaccine Center, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
- Bioinformatics Centre, Department of Biology, University of Copenhagen, 1017 Copenhagen, Denmark
| | - Guang Lan Zhang
- Cancer Vaccine Center, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
- Department of Computer Science, Metropolitan College, Boston University, Boston, MA 02215, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Ellis L. Reinherz
- Cancer Vaccine Center, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- Laboratory of Immunobiology, Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
| | - Vladimir Brusic
- Cancer Vaccine Center, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
- Department of Computer Science, Metropolitan College, Boston University, Boston, MA 02215, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
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Duan Z, Guo J, Huang X, Liu H, Chen X, Jiang M, Wen J. Identification of cytotoxic T lymphocyte epitopes in dengue virus serotype 1. J Med Virol 2015; 87:1077-89. [PMID: 25777343 DOI: 10.1002/jmv.24167] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/20/2015] [Indexed: 11/12/2022]
Abstract
Dengue virus (DENV) has a serious and growing impact on global health and the exact role of DENV-specific CD8(+) T-cells in DENV infection is still uncertain. In the present study, SYFPEITHI algorithm was used to screen the amino acid sequence of Dengue virus serotype 1 (DENV-1) for potential epitopes, and seven putative HLA-A*1101-restricted and five putative HLA-A*2402-restricted epitopes conserved in hundreds of DENV-1 strains were synthesized. The binding affinity of these epitope candidates to corresponding HLA molecules was evaluated using competitive peptide-binding assay. The immunogenicity and specificity of peptides were further tested in HLA-A*1101 transgenic mice, HLA-A*2402 transgenic mice and peripheral blood mononuclear cells (PBMCs) of patients infected with DENV-1. Percentage inhibition (PI) values calculated in competitive peptide-binding assay showed that six peptides (E39-47 PTLDIELLK, NS5(505-513) GVEGEGLHK, NS2b(15-23) SILLSSLLK, NS5(561-569) ALLATSIFK, NS3(99-107) AVEPGKNPK, and NS4b(159-167) VVYDAKFEK) could bind to HLA-A*1101 molecule with high affinity and five peptides (NS3472-480 QYIYMGQPL, NS4a40-48 AYRHAMEEL, NS5(880-888) DYMTSMKRF, NS3(548-556) SYKVASEGF, and NS3(22-30) IYRILQRGL) have a high affinity for HLA-A*2402 molecule. Enzyme-linked immunospot (ELISPOT) results indicated that these high-affinity peptides were recognized by splenocytes of DENV-1-infected transgenic mice and high-affinity peptide-immunized transgenic mice displayed high levels of peptide-specific IFN-γ-secreting cells. In addition, both peptide-pulsed splenocytes and DENV-1-infected splenic monocytes were efficiently killed by these peptide-specific cytotoxic T lymphocytes. Finally, except NS2b(15-23), 10 high-affinity peptides were recognized by PBMCs of patients infected with DENV-1. These identified epitopes would contribute to the understanding of the function of DENV-specific CD8(+) T-cells.
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Affiliation(s)
- Zhiliang Duan
- Department of Microbiology and Immunology, School of Basic Medical Sciences, Wenzhou Medical University, Wenzhou, China; Department of Clinical Laboratory, The Second Affiliated Hospital & Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China
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Olsen LR, Campos B, Barnkob MS, Winther O, Brusic V, Andersen MH. Bioinformatics for cancer immunotherapy target discovery. Cancer Immunol Immunother 2014; 63:1235-49. [PMID: 25344903 PMCID: PMC11029190 DOI: 10.1007/s00262-014-1627-7] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2013] [Accepted: 10/08/2014] [Indexed: 12/13/2022]
Abstract
The mechanisms of immune response to cancer have been studied extensively and great effort has been invested into harnessing the therapeutic potential of the immune system. Immunotherapies have seen significant advances in the past 20 years, but the full potential of protective and therapeutic cancer immunotherapies has yet to be fulfilled. The insufficient efficacy of existing treatments can be attributed to a number of biological and technical issues. In this review, we detail the current limitations of immunotherapy target selection and design, and review computational methods to streamline therapy target discovery in a bioinformatics analysis pipeline. We describe specialized bioinformatics tools and databases for three main bottlenecks in immunotherapy target discovery: the cataloging of potentially antigenic proteins, the identification of potential HLA binders, and the selection epitopes and co-targets for single-epitope and multi-epitope strategies. We provide examples of application to the well-known tumor antigen HER2 and suggest bioinformatics methods to ameliorate therapy resistance and ensure efficient and lasting control of tumors.
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Affiliation(s)
- Lars Rønn Olsen
- Department of Biology, Bioinformatics Centre, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark,
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Big data analytics in immunology: a knowledge-based approach. BIOMED RESEARCH INTERNATIONAL 2014; 2014:437987. [PMID: 25045677 PMCID: PMC4090507 DOI: 10.1155/2014/437987] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/31/2014] [Accepted: 05/07/2014] [Indexed: 01/27/2023]
Abstract
With the vast amount of immunological data available, immunology research is entering the big data era. These data vary in granularity, quality, and complexity and are stored in various formats, including publications, technical reports, and databases. The challenge is to make the transition from data to actionable knowledge and wisdom and bridge the knowledge gap and application gap. We report a knowledge-based approach based on a framework called KB-builder that facilitates data mining by enabling fast development and deployment of web-accessible immunological data knowledge warehouses. Immunological knowledge discovery relies heavily on both the availability of accurate, up-to-date, and well-organized data and the proper analytics tools. We propose the use of knowledge-based approaches by developing knowledgebases combining well-annotated data with specialized analytical tools and integrating them into analytical workflow. A set of well-defined workflow types with rich summarization and visualization capacity facilitates the transformation from data to critical information and knowledge. By using KB-builder, we enabled streamlining of normally time-consuming processes of database development. The knowledgebases built using KB-builder will speed up rational vaccine design by providing accurate and well-annotated data coupled with tailored computational analysis tools and workflow.
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15
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Olsen LR, Kudahl UJ, Simon C, Sun J, Schönbach C, Reinherz EL, Zhang GL, Brusic V. BlockLogo: visualization of peptide and sequence motif conservation. J Immunol Methods 2013; 400-401:37-44. [PMID: 24001880 DOI: 10.1016/j.jim.2013.08.014] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2013] [Revised: 08/20/2013] [Accepted: 08/25/2013] [Indexed: 12/21/2022]
Abstract
BlockLogo is a web-server application for the visualization of protein and nucleotide fragments, continuous protein sequence motifs, and discontinuous sequence motifs using calculation of block entropy from multiple sequence alignments. The user input consists of a multiple sequence alignment, selection of motif positions, type of sequence, and output format definition. The output has BlockLogo along with the sequence logo, and a table of motif frequencies. We deployed BlockLogo as an online application and have demonstrated its utility through examples that show visualization of T-cell epitopes and B-cell epitopes (both continuous and discontinuous). Our additional example shows a visualization and analysis of structural motifs that determine the specificity of peptide binding to HLA-DR molecules. The BlockLogo server also employs selected experimentally validated prediction algorithms to enable on-the-fly prediction of MHC binding affinity to 15 common HLA class I and class II alleles as well as visual analysis of discontinuous epitopes from multiple sequence alignments. It enables the visualization and analysis of structural and functional motifs that are usually described as regular expressions. It provides a compact view of discontinuous motifs composed of distant positions within biological sequences. BlockLogo is available at: http://research4.dfci.harvard.edu/cvc/blocklogo/ and http://met-hilab.bu.edu/blocklogo/.
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Affiliation(s)
- Lars Rønn Olsen
- Cancer Vaccine Center, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA; Bioinformatics Centre, Department of Biology, University of Copenhagen, Copenhagen, Denmark
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16
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Identification of B cell epitopes of dengue virus 2 NS3 protein by monoclonal antibody. Appl Microbiol Biotechnol 2012; 97:1553-60. [PMID: 23081772 DOI: 10.1007/s00253-012-4419-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2012] [Revised: 08/28/2012] [Accepted: 09/04/2012] [Indexed: 10/27/2022]
Abstract
Dengue virus is a major international public health concern, and there is a lack of available effective vaccines. Virus-specific epitopes could help in developing epitope peptide vaccine. Previously, a neutralizing monoclonal antibody (mAb) 4F5 against nonstructural protein 3 (NS3) of dengue virus 2 (DV2) was developed in our lab. In this work, the B cell epitope recognized by mAb 4F5 was identified using the phage-displayed peptide library. The results of the binding assay and competitive inhibition assay indicated that the peptides, residues 460-469 (U460-469 RVGRNPKNEN) of DV2 NS3 protein, were the B cell epitopes recognized by mAb 4F5. Furthermore, the epitope peptides and a control peptide were synthesized and then immunized female BALB/c mice. ELISA analysis showed that immunization with synthesized epitope peptide elicited a high level of antibody in mice, and immunofluorescent staining showed that the antisera from fusion epitope-immunized mice also responded to DV2 NS3 protein, which further characterized the specific response of the present epitope peptide. Therefore, the present work revealed the specificity of the newly identified epitope (U460-469) of DV2 NS3 protein, which may shed light on dengue virus (DV) vaccine design, DV pathogenesis study, and even DV diagnostic reagent development.
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17
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Islam R, Sakib MS, Zaman A. A computational assay to design an epitope-based peptide vaccine against chikungunya virus. Future Virol 2012. [DOI: 10.2217/fvl.12.95] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Aim: Chikungunya virus, an arthropod-borne alphavirus, belongs to the Togavirus family. Despite severe epidemic outbreaks on several occasions, not much progress has been made with regard to epitope-based drug design for chikungunya virus. In this study we performed a proteome-wide search to look for a conserved region among the available viral proteins, one which has the capacity to trigger a significant immune response. Materials & methods: The conserved region was analyzed by performing an alignment of sequences collected from sources from varied geographic locations and time periods. Subsequently, the immune parameters for the peptide sequences were determined using several in silico tools and immune databases. Results: Both T-cell immunity and B-cell immunity were checked for the peptides to ensure that they had the capacity to induce both humoral and cell-based immunity. Our study reveals a stretch of conserved region in glycoprotein E2; yet this peptide sequence could interact with as many as seven HLAs and showed population coverage as high as 73.46%. The epitope was further tested for binding against the HLA structure using in silico docking techniques to validate the binding cleft epitope interaction in detail. Conclusion: Although the study requires further in vivo screening, keeping in mind the consistency and reproducibility of the immune system at selecting and reacting to peptide epitopes, this study allows us to claim a novel peptide antigen target in E2 protein with good confidence.
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Affiliation(s)
- Rezaul Islam
- Department of Biochemistry & Molecular Biology, University of Dhaka, Dhaka, Bangladesh
| | - M Sadman Sakib
- Department of Biochemistry & Molecular Biology, University of Dhaka, Dhaka, Bangladesh
| | - Aubhishek Zaman
- Department of Genetic Engineering & Biotechnology, University of Dhaka, Dhaka, Bangladesh
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