Cargando…
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...
Autores principales: | , , , , , , , , |
---|---|
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 |
_version_ | 1784787535394766848 |
---|---|
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. |
format | Online Article Text |
id | pubmed-9464217 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT liumeichen aglobaldatasetofmicrobialcommunityinticksfrommetagenomestudy AT zhangjingtao aglobaldatasetofmicrobialcommunityinticksfrommetagenomestudy AT chenjinjin aglobaldatasetofmicrobialcommunityinticksfrommetagenomestudy AT zhuying aglobaldatasetofmicrobialcommunityinticksfrommetagenomestudy AT fubokang aglobaldatasetofmicrobialcommunityinticksfrommetagenomestudy AT huzhenyu aglobaldatasetofmicrobialcommunityinticksfrommetagenomestudy AT fangliqun aglobaldatasetofmicrobialcommunityinticksfrommetagenomestudy AT zhangxiaoai aglobaldatasetofmicrobialcommunityinticksfrommetagenomestudy AT liuwei aglobaldatasetofmicrobialcommunityinticksfrommetagenomestudy AT liumeichen globaldatasetofmicrobialcommunityinticksfrommetagenomestudy AT zhangjingtao globaldatasetofmicrobialcommunityinticksfrommetagenomestudy AT chenjinjin globaldatasetofmicrobialcommunityinticksfrommetagenomestudy AT zhuying globaldatasetofmicrobialcommunityinticksfrommetagenomestudy AT fubokang globaldatasetofmicrobialcommunityinticksfrommetagenomestudy AT huzhenyu globaldatasetofmicrobialcommunityinticksfrommetagenomestudy AT fangliqun globaldatasetofmicrobialcommunityinticksfrommetagenomestudy AT zhangxiaoai globaldatasetofmicrobialcommunityinticksfrommetagenomestudy AT liuwei globaldatasetofmicrobialcommunityinticksfrommetagenomestudy |