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Mehrannia P, Moshiri B, Basir O. Knowledgebase approximation using association rule aggregation. INTERNATIONAL JOURNAL OF DATA SCIENCE AND ANALYTICS 2022. [DOI: 10.1007/s41060-021-00304-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Khan AM, Hu Y, Miotto O, Thevasagayam NM, Sukumaran R, Abd Raman HS, Brusic V, Tan TW, Thomas August J. Analysis of viral diversity for vaccine target discovery. BMC Med Genomics 2017; 10:78. [PMID: 29322922 PMCID: PMC5763473 DOI: 10.1186/s12920-017-0301-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Viral vaccine target discovery requires understanding the diversity of both the virus and the human immune system. The readily available and rapidly growing pool of viral sequence data in the public domain enable the identification and characterization of immune targets relevant to adaptive immunity. A systematic bioinformatics approach is necessary to facilitate the analysis of such large datasets for selection of potential candidate vaccine targets. RESULTS This work describes a computational methodology to achieve this analysis, with data of dengue, West Nile, hepatitis A, HIV-1, and influenza A viruses as examples. Our methodology has been implemented as an analytical pipeline that brings significant advancement to the field of reverse vaccinology, enabling systematic screening of known sequence data in nature for identification of vaccine targets. This includes key steps (i) comprehensive and extensive collection of sequence data of viral proteomes (the virome), (ii) data cleaning, (iii) large-scale sequence alignments, (iv) peptide entropy analysis, (v) intra- and inter-species variation analysis of conserved sequences, including human homology analysis, and (vi) functional and immunological relevance analysis. CONCLUSION These steps are combined into the pipeline ensuring that a more refined process, as compared to a simple evolutionary conservation analysis, will facilitate a better selection of vaccine targets and their prioritization for subsequent experimental validation.
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Affiliation(s)
- Asif M. Khan
- Centre for Bioinformatics, School of Data Sciences, Perdana University, Jalan MAEPS Perdana, Serdang, Selangor Darul Ehsan 43400 Malaysia
- Department of Pharmacology and Molecular Sciences, The Johns Hopkins University School of Medicine, 725 North Wolfe Street, Baltimore, MD 21205 USA
| | - Yongli Hu
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore, 117597 Singapore
| | - Olivo Miotto
- Centre for Genomics and Global Health, University of Oxford, Oxford, UK
- Mahidol-Oxford Research Unit, Faculty of Tropical Medicine, Mahidol University, Rajthevee, Bangkok, Thailand
| | - Natascha M. Thevasagayam
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore, 117597 Singapore
| | - Rashmi Sukumaran
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore, 117597 Singapore
| | - Hadia Syahirah Abd Raman
- Centre for Bioinformatics, School of Data Sciences, Perdana University, Jalan MAEPS Perdana, Serdang, Selangor Darul Ehsan 43400 Malaysia
| | - Vladimir Brusic
- Menzies Health Institute Queensland, Griffith University, Parklands Dr, Southport, 4215 QLD Australia
| | - Tin Wee Tan
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore, 117597 Singapore
| | - J. Thomas August
- Department of Pharmacology and Molecular Sciences, The Johns Hopkins University School of Medicine, 725 North Wolfe Street, Baltimore, MD 21205 USA
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Miotto O, Heiny AT, Albrecht R, García-Sastre A, Tan TW, August JT, Brusic V. Complete-proteome mapping of human influenza A adaptive mutations: implications for human transmissibility of zoonotic strains. PLoS One 2010; 5:e9025. [PMID: 20140252 PMCID: PMC2815782 DOI: 10.1371/journal.pone.0009025] [Citation(s) in RCA: 63] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2009] [Accepted: 12/27/2009] [Indexed: 12/11/2022] Open
Abstract
Background There is widespread concern that H5N1 avian influenza A viruses will emerge
as a pandemic threat, if they become capable of human-to-human (H2H)
transmission. Avian strains lack this capability, which suggests that it
requires important adaptive mutations. We performed a large-scale
comparative analysis of proteins from avian and human strains, to produce a
catalogue of mutations associated with H2H transmissibility, and to detect
their presence in avian isolates. Methodology/Principal Findings We constructed a dataset of influenza A protein sequences from 92,343 public
database records. Human and avian sequence subsets were compared, using a
method based on mutual information, to identify
characteristic sites where human isolates present
conserved mutations. The resulting catalogue comprises 68 characteristic
sites in eight internal proteins. Subtype variability prevented the
identification of adaptive mutations in the hemagglutinin and neuraminidase
proteins. The high number of sites in the ribonucleoprotein complex suggests
interdependence between mutations in multiple proteins. Characteristic sites
are often clustered within known functional regions, suggesting their
functional roles in cellular processes. By isolating and concatenating
characteristic site residues, we defined adaptation
signatures, which summarize the adaptive potential of specific
isolates. Most adaptive mutations emerged within three decades after the
1918 pandemic, and have remained remarkably stable thereafter. Two lineages
with stable internal protein constellations have circulated among humans
without reassorting. On the contrary, H5N1 avian and swine viruses reassort
frequently, causing both gains and losses of adaptive mutations. Conclusions Human host adaptation appears to be complex and systemic, involving nearly
all influenza proteins. Adaptation signatures suggest that the ability of
H5N1 strains to infect humans is related to the presence of an unusually
high number of adaptive mutations. However, these mutations appear unstable,
suggesting low pandemic potential of H5N1 in its current form. In addition,
adaptation signatures indicate that pandemic H1N1/09 strain possesses
multiple human-transmissibility mutations, though not an unusually high
number with respect to swine strains that infected humans in the past.
Adaptation signatures provide a novel tool for identifying zoonotic strains
with the potential to infect humans.
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Affiliation(s)
- Olivo Miotto
- Centre for Genomics and Global Health, University of Oxford, Oxford, United Kingdom.
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Halling-Brown MD, Moss DS, Sansom CE, Shepherd AJ. A computational Grid framework for immunological applications. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2009; 367:2705-2716. [PMID: 19487206 DOI: 10.1098/rsta.2009.0046] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
We have developed a computational Grid that enables us to exploit through a single interface a range of local, national and international resources. It insulates the user as far as possible from issues concerning administrative boundaries, passwords and different operating system features. This work has been undertaken as part of the European Union ImmunoGrid project whose aim is to develop simulations of the immune system at the molecular, cellular and organ levels. The ImmunoGrid consortium has members with computational resources on both sides of the Atlantic. By making extensive use of existing Grid middleware, our Grid has enabled us to exploit consortium and publicly available computers in a unified way, notwithstanding the diverse local software and administrative environments. We took 40 000 polypeptide sequences from 4000 avian and mammalian influenza strains and used a neural network for class I T-cell epitope prediction tools for 120 class I alleles and haplotypes to generate over 14 million high-quality protein-peptide binding predictions that we are mapping onto the three-dimensional structures of the proteins. By contrast, the Grid is also being used for developing new methods for class T-cell epitope predictions, where we have running batches of 120 molecular dynamics free-energy calculations.
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Affiliation(s)
- Mark D Halling-Brown
- Institute of Structural and Molecular Biology, School of Crystallography, Birkbeck College, Malet Street, London WC1E 7HX, UK
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Tong JC, Ren EC. Immunoinformatics: current trends and future directions. Drug Discov Today 2009; 14:684-9. [PMID: 19379830 PMCID: PMC7108239 DOI: 10.1016/j.drudis.2009.04.001] [Citation(s) in RCA: 51] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2008] [Revised: 03/30/2009] [Accepted: 04/06/2009] [Indexed: 01/28/2023]
Abstract
Immunoinformatics has recently emerged as a critical field for accelerating immunology research. Although still an evolving process, computational models now play instrumental roles, not only in directing the selection of key experiments, but also in the formulation of new testable hypotheses through detailed analysis of complex immunologic data that could not be achieved using traditional approaches alone. Immunomics, which combines traditional immunology with computer science, mathematics, chemistry, biochemistry, genomics and proteomics for the large-scale analysis of immune system function, offers new opportunities for future bench-to-bedside research. In this article, we review the latest trends and future directions of the field.
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Affiliation(s)
- Joo Chuan Tong
- Institute for Infocomm Research, 1 Fusionopolis Way, #21-01 Connexis, South Tower, Singapore 138632, Singapore.
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Ranganathan S, Gribskov M, Tan TW. Bioinformatics research in the Asia Pacific: a 2007 update. BMC Bioinformatics 2008; 9 Suppl 1:S1. [PMID: 18315840 PMCID: PMC2259402 DOI: 10.1186/1471-2105-9-s1-s1] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
We provide a 2007 update on the bioinformatics research in the Asia-Pacific from the Asia Pacific Bioinformatics Network (APBioNet), Asia's oldest bioinformatics organisation set up in 1998. From 2002, APBioNet has organized the first International Conference on Bioinformatics (InCoB) bringing together scientists working in the field of bioinformatics in the region. This year, the InCoB2007 Conference was organized as the 6th annual conference of the Asia-Pacific Bioinformatics Network, on Aug. 27-30, 2007 at Hong Kong, following a series of successful events in Bangkok (Thailand), Penang (Malaysia), Auckland (New Zealand), Busan (South Korea) and New Delhi (India). Besides a scientific meeting at Hong Kong, satellite events organized are a pre-conference training workshop at Hanoi, Vietnam and a post-conference workshop at Nansha, China. This Introduction provides a brief overview of the peer-reviewed manuscripts accepted for publication in this Supplement. We have organized the papers into thematic areas, highlighting the growing contribution of research excellence from this region, to global bioinformatics endeavours.
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Affiliation(s)
- Shoba Ranganathan
- Department of Chemistry and Biomolecular Sciences and Biotechnology Research Institute, Macquarie University, Sydney NSW 2109, Australia
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597
| | - Michael Gribskov
- Department of Biological Sciences, Purdue University, Lilly Hall of Life Sciences 915 W. State Street, West Lafayette IN 47907-2054, USA
| | - Tin Wee Tan
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597
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Heiny AT, Miotto O, Srinivasan KN, Khan AM, Zhang GL, Brusic V, Tan TW, August JT. Evolutionarily conserved protein sequences of influenza a viruses, avian and human, as vaccine targets. PLoS One 2007; 2:e1190. [PMID: 18030326 PMCID: PMC2065905 DOI: 10.1371/journal.pone.0001190] [Citation(s) in RCA: 126] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2007] [Accepted: 10/17/2007] [Indexed: 01/16/2023] Open
Abstract
Background Influenza A viruses generate an extreme genetic diversity through point mutation and gene segment exchange, resulting in many new strains that emerge from the animal reservoirs, among which was the recent highly pathogenic H5N1 virus. This genetic diversity also endows these viruses with a dynamic adaptability to their habitats, one result being the rapid selection of genomic variants that resist the immune responses of infected hosts. With the possibility of an influenza A pandemic, a critical need is a vaccine that will recognize and protect against any influenza A pathogen. One feasible approach is a vaccine containing conserved immunogenic protein sequences that represent the genotypic diversity of all current and future avian and human influenza viruses as an alternative to current vaccines that address only the known circulating virus strains. Methodology/Principal Findings Methodologies for large-scale analysis of the evolutionary variability of the influenza A virus proteins recorded in public databases were developed and used to elucidate the amino acid sequence diversity and conservation of 36,343 sequences of the 11 viral proteins of the recorded virus isolates of the past 30 years. Technologies were also applied to identify the conserved amino acid sequences from isolates of the past decade, and to evaluate the predicted human lymphocyte antigen (HLA) supertype-restricted class I and II T-cell epitopes of the conserved sequences. Fifty-five (55) sequences of 9 or more amino acids of the polymerases (PB2, PB1, and PA), nucleoprotein (NP), and matrix 1 (M1) proteins were completely conserved in at least 80%, many in 95 to 100%, of the avian and human influenza A virus isolates despite the marked evolutionary variability of the viruses. Almost all (50) of these conserved sequences contained putative supertype HLA class I or class II epitopes as predicted by 4 peptide-HLA binding algorithms. Additionally, data of the Immune Epitope Database (IEDB) include 29 experimentally identified HLA class I and II T-cell epitopes present in 14 of the conserved sequences. Conclusions/Significance This study of all reported influenza A virus protein sequences, avian and human, has identified 55 highly conserved sequences, most of which are predicted to have immune relevance as T-cell epitopes. This is a necessary first step in the design and analysis of a polyepitope, pan-influenza A vaccine. In addition to the application described herein, these technologies can be applied to other pathogens and to other therapeutic modalities designed to attack DNA, RNA, or protein sequences critical to pathogen function.
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Affiliation(s)
- A. T. Heiny
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Olivo Miotto
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Institute of Systems Science, National University of Singapore, Singapore, Singapore
| | - Kellathur N. Srinivasan
- Department of Pharmacology and Molecular Sciences, The Johns Hopkins University School of Medicine, Maryland, United States of America
- Product Evaluation and Registration Division, Centre for Drug Administration, Health Sciences Authority, Singapore, Singapore
| | - Asif M. Khan
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Department of Microbiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - G. L. Zhang
- Institute for Infocomm Research, Singapore, Singapore
| | - Vladimir Brusic
- Cancer Vaccine Center, Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America
| | - Tin Wee Tan
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - J. Thomas August
- Department of Pharmacology and Molecular Sciences, The Johns Hopkins University School of Medicine, Maryland, United States of America
- * To whom correspondence should be addressed. E-mail:
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