A systematic bioinformatics approach for large-scale identification and characterization of host-pathogen shared sequences

BMC Genomics

卷:22

Methodology

Hui San Ong¹  Ranjeev Hari¹  Asif M. Khan²  Stephen Among James³ 

[1] Centre for Bioinformatics, School of Data Sciences, Perdana University, 50490, Damansara Heights, Kuala Lumpur, Malaysia;

[2] Centre for Bioinformatics, School of Data Sciences, Perdana University, 50490, Damansara Heights, Kuala Lumpur, Malaysia;Beykoz Institute of Life Sciences and Biotechnology, Bezmialem Vakif University, Beykoz, 34820, Istanbul, Turkey;

[3] Centre for Bioinformatics, School of Data Sciences, Perdana University, 50490, Damansara Heights, Kuala Lumpur, Malaysia;Department of Biochemistry, Faculty of Science, Kaduna State University, 800211, Kaduna, Nigeria;

关键词: Shared sequences;    Share-ome;    Host-pathogen;    Bioinformatics;    Large-scale;    Methodology;    Flaviviridae;    Flavivirus;    Hepacivirus;    Pegivirus;    Pestivirus;    Dengue virus;    West Nile virus;    Hepatitis C virus;    Cross-reactivity;    Crossreactome;    Peptide sharing;    Peptide overlap;    and Molecular mimicry.;   

DOI  :  10.1186/s12864-021-07657-4

 received in 2021-03-14, accepted in 2021-04-28,  发布年份 2021

来源: Springer

【 摘 要 】

BackgroundBiology has entered the era of big data with the advent of high-throughput omics technologies. Biological databases provide public access to petabytes of data and information facilitating knowledge discovery. Over the years, sequence data of pathogens has seen a large increase in the number of records, given the relatively small genome size and their important role as infectious and symbiotic agents. Humans are host to numerous pathogenic diseases, such as that by viruses, many of which are responsible for high mortality and morbidity. The interaction between pathogens and humans over the evolutionary history has resulted in sharing of sequences, with important biological and evolutionary implications.ResultsThis study describes a large-scale, systematic bioinformatics approach for identification and characterization of shared sequences between the host and pathogen. An application of the approach is demonstrated through identification and characterization of the Flaviviridae-human share-ome. A total of 2430 nonamers represented the Flaviviridae-human share-ome with 100% identity. Although the share-ome represented a small fraction of the repertoire of Flaviviridae (~ 0.12%) and human (~ 0.013%) non-redundant nonamers, the 2430 shared nonamers mapped to 16,946 Flaviviridae and 7506 human non-redundant protein sequences. The shared nonamer sequences mapped to 125 species of Flaviviridae, including several with unclassified genus. The majority (~ 68%) of the shared sequences mapped to Hepacivirus C species; West Nile, dengue and Zika viruses of the Flavivirus genus accounted for ~ 11%, ~ 7%, and ~ 3%, respectively, of the Flaviviridae protein sequences (16,946) mapped by the share-ome. Further characterization of the share-ome provided important structural-functional insights to Flaviviridae-human interactions.ConclusionMapping of the host-pathogen share-ome has important implications for the design of vaccines and drugs, diagnostics, disease surveillance and the discovery of unknown, potential host-pathogen interactions. The generic workflow presented herein is potentially applicable to a variety of pathogens, such as of viral, bacterial or parasitic origin.

【 授权许可】

CC BY   
© The Author(s) 2021

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