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A global dataset of microbial community in ticks from metagenome study

Ticks are important vectors of various zoonotic pathogens that can infect animals and humans, and most documented tick-borne pathogens have a strong bias towards microorganisms with strong disease phenotypes. The recent development of next-generation sequencing (NGS) has enabled the study of microbi...

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Autores principales: Liu, Mei-Chen, Zhang, Jing-Tao, Chen, Jin-Jin, Zhu, Ying, Fu, Bo-Kang, Hu, Zhen-Yu, Fang, Li-Qun, Zhang, Xiao-Ai, Liu, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9464217/
https://www.ncbi.nlm.nih.gov/pubmed/36088366
http://dx.doi.org/10.1038/s41597-022-01679-7
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author Liu, Mei-Chen
Zhang, Jing-Tao
Chen, Jin-Jin
Zhu, Ying
Fu, Bo-Kang
Hu, Zhen-Yu
Fang, Li-Qun
Zhang, Xiao-Ai
Liu, Wei
author_facet Liu, Mei-Chen
Zhang, Jing-Tao
Chen, Jin-Jin
Zhu, Ying
Fu, Bo-Kang
Hu, Zhen-Yu
Fang, Li-Qun
Zhang, Xiao-Ai
Liu, Wei
author_sort Liu, Mei-Chen
collection PubMed
description Ticks are important vectors of various zoonotic pathogens that can infect animals and humans, and most documented tick-borne pathogens have a strong bias towards microorganisms with strong disease phenotypes. The recent development of next-generation sequencing (NGS) has enabled the study of microbial communities, referred to as microbiome. Herein, we undertake a systematic review of published literature to build a comprehensive global dataset of microbiome determined by NGS in field-collected ticks. The dataset comprised 4418 records from 76 literature involving geo-referenced occurrences for 46 species of ticks and 219 microorganism families, revealing a total of 83 emerging viruses identified from 24 tick species belonging to 6 tick genera since 1980. The viral, bacterial and eukaryotic composition was compared regarding the tick species, their live stage and types of the specimens, or the geographic location. The data can assist the further investigation of ecological, biogeographical and epidemiological features of the tick-borne disease.
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spelling pubmed-94642172022-09-12 A global dataset of microbial community in ticks from metagenome study Liu, Mei-Chen Zhang, Jing-Tao Chen, Jin-Jin Zhu, Ying Fu, Bo-Kang Hu, Zhen-Yu Fang, Li-Qun Zhang, Xiao-Ai Liu, Wei Sci Data Data Descriptor Ticks are important vectors of various zoonotic pathogens that can infect animals and humans, and most documented tick-borne pathogens have a strong bias towards microorganisms with strong disease phenotypes. The recent development of next-generation sequencing (NGS) has enabled the study of microbial communities, referred to as microbiome. Herein, we undertake a systematic review of published literature to build a comprehensive global dataset of microbiome determined by NGS in field-collected ticks. The dataset comprised 4418 records from 76 literature involving geo-referenced occurrences for 46 species of ticks and 219 microorganism families, revealing a total of 83 emerging viruses identified from 24 tick species belonging to 6 tick genera since 1980. The viral, bacterial and eukaryotic composition was compared regarding the tick species, their live stage and types of the specimens, or the geographic location. The data can assist the further investigation of ecological, biogeographical and epidemiological features of the tick-borne disease. Nature Publishing Group UK 2022-09-10 /pmc/articles/PMC9464217/ /pubmed/36088366 http://dx.doi.org/10.1038/s41597-022-01679-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Data Descriptor
Liu, Mei-Chen
Zhang, Jing-Tao
Chen, Jin-Jin
Zhu, Ying
Fu, Bo-Kang
Hu, Zhen-Yu
Fang, Li-Qun
Zhang, Xiao-Ai
Liu, Wei
A global dataset of microbial community in ticks from metagenome study
title A global dataset of microbial community in ticks from metagenome study
title_full A global dataset of microbial community in ticks from metagenome study
title_fullStr A global dataset of microbial community in ticks from metagenome study
title_full_unstemmed A global dataset of microbial community in ticks from metagenome study
title_short A global dataset of microbial community in ticks from metagenome study
title_sort global dataset of microbial community in ticks from metagenome study
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9464217/
https://www.ncbi.nlm.nih.gov/pubmed/36088366
http://dx.doi.org/10.1038/s41597-022-01679-7
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