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      Stochastic profile of Epstein-Barr virus in nasopharyngeal carcinoma settings

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          Abstract

          We build a profile of the Epstein-Barr virus (EBV) by means of genomic sequences obtained from patients with nasopharyngeal carcinoma (NPC). We consider a set of sequences coming from the NCBI free source and we assume that this set is a collection of independent samples of stochastic processes related by an equivalence relation. Given a collection {( X j t) t∈ℤ} p j=1 of p independent discrete time Markov processes with finite alphabet A and state space S, we state that the elements ( i, s) and ( j, r) in {1, 2,…, p} ×  S are equivalent if and only if they share the same transition probability for all the elements in the alphabet. The equivalence allows to reduce the number of parameters to be estimated in the model avoiding to delete states of S to achieve that reduction. Through the equivalence relationship, we build the global profile for all the EBV in NPC sequences, this model allows us to represent the underlying and common stochastic law of the set of sequences. The equivalence classes define an optimal partition of {1, 2,…, p} ×  S, and it is in relation to this partition that we define the profile of the set of genomic sequences.

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          Genomic sequence analysis of Epstein-Barr virus strain GD1 from a nasopharyngeal carcinoma patient.

          To date, the only entire Epstein-Barr virus (EBV) genomic sequence available in the database is the prototype B95.8, which was derived from an individual with infectious mononucleosis. A causative link between EBV and nasopharyngeal carcinoma (NPC), a disease with a distinctly high incidence in southern China, has been widely investigated. However, no full-length analysis of any substrain of EBV from this area has been reported. In this study, we analyzed the entire genomic sequence of an EBV strain from a patient with NPC in Guangdong, China. This EBV strain was termed GD1 (Guangdong strain 1), and the full-length sequence of GD1 was submitted to the GenBank database. The assigned accession number is AY961628. The entire GD1 sequence is 171,656 bp in length, with 59.5% G+C content and 40.5% A+T content. We detected many sequence variations in GD1 compared to prototypical strain B95.8, including 43 deletion sites, 44 insertion sites, and 1,413 point mutations. Furthermore, we evaluated the frequency of some of these GD1 mutations in Cantonese NPC patients and found them to be highly prevalent. These findings suggest that GD1 is highly representative of the EBV strains isolated from NPC patients in Guangdong, China, an area with the highest incidence of NPC in the world. Furthermore, these findings provide the second full-length sequence analysis of any EBV strain as well as the first full-length sequence analysis of an NPC-derived EBV strain.
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            Genomic Sequencing and Comparative Analysis of Epstein-Barr Virus Genome Isolated from Primary Nasopharyngeal Carcinoma Biopsy

            Whether certain Epstein-Barr virus (EBV) strains are associated with pathogenesis of nasopharyngeal carcinoma (NPC) is still an unresolved question. In the present study, EBV genome contained in a primary NPC tumor biopsy was amplified by Polymerase Chain Reaction (PCR), and sequenced using next-generation (Illumina) and conventional dideoxy-DNA sequencing. The EBV genome, designated HKNPC1 (Genbank accession number JQ009376) is a type 1 EBV of approximately 171.5 kb. The virus appears to be a uniform strain in line with accepted monoclonal nature of EBV in NPC but is heterogeneous at 172 nucleotide positions. Phylogenetic analysis with the four published EBV strains, B95-8, AG876, GD1, and GD2, indicated HKNPC1 was more closely related to the Chinese NPC patient-derived strains, GD1 and GD2. HKNPC1 contains 1,589 single nucleotide variations (SNVs) and 132 insertions or deletions (indels) in comparison to the reference EBV sequence (accession number NC007605). When compared to AG876, a strain derived from Ghanaian Burkitt's lymphoma, we found 322 SNVs, of which 76 were non-synonymous SNVs and were shared amongst the Chinese GD1, GD2 and HKNPC1 isolates. We observed 88 non-synonymous SNVs shared only by HKNPC1 and GD2, the only other NPC tumor-derived strain reported thus far. Non-synonymous SNVs were mainly found in the latent, tegument and glycoprotein genes. The same point mutations were found in glycoprotein (BLLF1 and BALF4) genes of GD1, GD2 and HKNPC1 strains and might affect cell type specific binding. Variations in LMP1 and EBNA3B epitopes and mutations in Cp (11404 C>T) and Qp (50134 G>C) found in GD1, GD2 and HKNPC1 could potentially affect CD8+ T cell recognition and latent gene expression pattern in NPC, respectively. In conclusion, we showed that whole genome sequencing of EBV in NPC may facilitate discovery of previously unknown variations of pathogenic significance.
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              Distributions of statistics of hidden state sequences through the sum-product algorithm

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                Author and article information

                Contributors
                Role: Guest Editor
                Journal
                fopen
                https://www.4open-sciences.org
                4open
                4open
                EDP Sciences
                2557-0250
                11 July 2019
                11 July 2019
                2019
                : 2
                : ( publisher-idID: fopen/2019/01 )
                Affiliations
                [1 ] Department of Mathematics, Federal University of Technology, , Avenida Monteiro Lobato, s/n – Km 04, Ponta Grossa, CEP 84016-210 Paraná, Brazil,
                [2 ] Department of Statistics, University of Campinas, , Sergio Buarque de Holanda, 651, Campinas, CEP 13083-859 São Paulo, Brazil,
                Author notes
                [* ]Corresponding author: jg@ 123456ime.unicamp.br
                Article
                fopen190013
                10.1051/fopen/2019020
                © M.T.A. Cordeiro et al., Published by EDP Sciences, 2019

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                Page count
                Figures: 0, Tables: 5, Equations: 72, References: 6, Pages: 7
                Product
                Self URI (journal page): https://www.4open-sciences.org/
                Categories
                Mathematics - Applied Mathematics
                Research Article
                Statistical Inference in Copula Models and Markov Processes, Case Studies and Insights
                Custom metadata
                4open 2019, 2, 25
                2019
                2019
                2019

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