Hidden Viral Sequences in Public Sequencing Data and Warning for Future Emerging Diseases

ABSTRACT RNA viruses cause numerous emerging diseases, mostly due to transmission from mammalian and avian reservoirs. Large-scale surveillance of RNA viral infections in these animals is a fundamental step for controlling viral infectious diseases. Metagenomic analysis is a powerful method for viru...

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Autores principales:	Junna Kawasaki, Shohei Kojima, Keizo Tomonaga, Masayuki Horie
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2021
Materias:	RNA virus bioinformatics molecular epidemiology public health virus diversity zoonosis Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/d47b6c171b3845e9ac2574fd3e02fd53
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spelling	oai:doaj.org-article:d47b6c171b3845e9ac2574fd3e02fd532021-11-10T18:37:52ZHidden Viral Sequences in Public Sequencing Data and Warning for Future Emerging Diseases10.1128/mBio.01638-212150-7511https://doaj.org/article/d47b6c171b3845e9ac2574fd3e02fd532021-08-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mBio.01638-21https://doaj.org/toc/2150-7511ABSTRACT RNA viruses cause numerous emerging diseases, mostly due to transmission from mammalian and avian reservoirs. Large-scale surveillance of RNA viral infections in these animals is a fundamental step for controlling viral infectious diseases. Metagenomic analysis is a powerful method for virus identification with low bias and has contributed substantially to the discovery of novel viruses. Deep-sequencing data have been collected from diverse animals and accumulated in public databases, which can be valuable resources for identifying unknown viral sequences. Here, we screened for infections of 33 RNA viral families in publicly available mammalian and avian sequencing data and found approximately 900 hidden viral infections. We also discovered six nearly complete viral genomes in livestock, wild, and experimental animals: hepatovirus in a goat, hepeviruses in blind mole-rats and a galago, astrovirus in macaque monkeys, parechovirus in a cow, and pegivirus in tree shrews. Some of these viruses were phylogenetically close to human-pathogenic viruses, suggesting the potential risk of causing disease in humans upon infection. Furthermore, infections of five novel viruses were identified in several different individuals, indicating that their infections may have already spread in the natural host population. Our findings demonstrate the reusability of public sequencing data for surveying viral infections and identifying novel viral sequences, presenting a warning about a new threat of viral infectious disease to public health. IMPORTANCE Monitoring the spread of viral infections and identifying novel viruses capable of infecting humans through animal reservoirs are necessary to control emerging viral diseases. Massive amounts of sequencing data collected from various animals are publicly available, and these data may contain sequences originating from a wide variety of viruses. Here, we analyzed more than 46,000 public sequencing data and identified approximately 900 hidden RNA viral infections in mammalian and avian samples. Some viruses discovered in this study were genetically similar to pathogens that cause hepatitis, diarrhea, or encephalitis in humans, suggesting the presence of new threats to public health. Our study demonstrates the effectiveness of reusing public sequencing data to identify known and unknown viral infections, indicating that future continuous monitoring of public sequencing data by metagenomic analyses would help prepare and mitigate future viral pandemics.Junna KawasakiShohei KojimaKeizo TomonagaMasayuki HorieAmerican Society for MicrobiologyarticleRNA virusbioinformaticsmolecular epidemiologypublic healthvirus diversityzoonosisMicrobiologyQR1-502ENmBio, Vol 12, Iss 4 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	RNA virus bioinformatics molecular epidemiology public health virus diversity zoonosis Microbiology QR1-502
spellingShingle	RNA virus bioinformatics molecular epidemiology public health virus diversity zoonosis Microbiology QR1-502 Junna Kawasaki Shohei Kojima Keizo Tomonaga Masayuki Horie Hidden Viral Sequences in Public Sequencing Data and Warning for Future Emerging Diseases
description	ABSTRACT RNA viruses cause numerous emerging diseases, mostly due to transmission from mammalian and avian reservoirs. Large-scale surveillance of RNA viral infections in these animals is a fundamental step for controlling viral infectious diseases. Metagenomic analysis is a powerful method for virus identification with low bias and has contributed substantially to the discovery of novel viruses. Deep-sequencing data have been collected from diverse animals and accumulated in public databases, which can be valuable resources for identifying unknown viral sequences. Here, we screened for infections of 33 RNA viral families in publicly available mammalian and avian sequencing data and found approximately 900 hidden viral infections. We also discovered six nearly complete viral genomes in livestock, wild, and experimental animals: hepatovirus in a goat, hepeviruses in blind mole-rats and a galago, astrovirus in macaque monkeys, parechovirus in a cow, and pegivirus in tree shrews. Some of these viruses were phylogenetically close to human-pathogenic viruses, suggesting the potential risk of causing disease in humans upon infection. Furthermore, infections of five novel viruses were identified in several different individuals, indicating that their infections may have already spread in the natural host population. Our findings demonstrate the reusability of public sequencing data for surveying viral infections and identifying novel viral sequences, presenting a warning about a new threat of viral infectious disease to public health. IMPORTANCE Monitoring the spread of viral infections and identifying novel viruses capable of infecting humans through animal reservoirs are necessary to control emerging viral diseases. Massive amounts of sequencing data collected from various animals are publicly available, and these data may contain sequences originating from a wide variety of viruses. Here, we analyzed more than 46,000 public sequencing data and identified approximately 900 hidden RNA viral infections in mammalian and avian samples. Some viruses discovered in this study were genetically similar to pathogens that cause hepatitis, diarrhea, or encephalitis in humans, suggesting the presence of new threats to public health. Our study demonstrates the effectiveness of reusing public sequencing data to identify known and unknown viral infections, indicating that future continuous monitoring of public sequencing data by metagenomic analyses would help prepare and mitigate future viral pandemics.
format	article
author	Junna Kawasaki Shohei Kojima Keizo Tomonaga Masayuki Horie
author_facet	Junna Kawasaki Shohei Kojima Keizo Tomonaga Masayuki Horie
author_sort	Junna Kawasaki
title	Hidden Viral Sequences in Public Sequencing Data and Warning for Future Emerging Diseases
title_short	Hidden Viral Sequences in Public Sequencing Data and Warning for Future Emerging Diseases
title_full	Hidden Viral Sequences in Public Sequencing Data and Warning for Future Emerging Diseases
title_fullStr	Hidden Viral Sequences in Public Sequencing Data and Warning for Future Emerging Diseases
title_full_unstemmed	Hidden Viral Sequences in Public Sequencing Data and Warning for Future Emerging Diseases
title_sort	hidden viral sequences in public sequencing data and warning for future emerging diseases
publisher	American Society for Microbiology
publishDate	2021
url	https://doaj.org/article/d47b6c171b3845e9ac2574fd3e02fd53
work_keys_str_mv	AT junnakawasaki hiddenviralsequencesinpublicsequencingdataandwarningforfutureemergingdiseases AT shoheikojima hiddenviralsequencesinpublicsequencingdataandwarningforfutureemergingdiseases AT keizotomonaga hiddenviralsequencesinpublicsequencingdataandwarningforfutureemergingdiseases AT masayukihorie hiddenviralsequencesinpublicsequencingdataandwarningforfutureemergingdiseases
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Hidden Viral Sequences in Public Sequencing Data and Warning for Future Emerging Diseases

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