Large-Scale Characterization of the Soil Microbiome in Ancient Tea Plantations Using High-Throughput 16S rRNA and Internal Transcribed Spacer Amplicon Sequencing.

16S and ITS rRNA Camellia sinensis var. assamica ancient tea plantations function microbiome

Journal

Frontiers in microbiology
ISSN: 1664-302X
Titre abrégé: Front Microbiol
Pays: Switzerland
ID NLM: 101548977

Informations de publication

Date de publication:
2021
Historique:
received: 21 07 2021
accepted: 31 08 2021
entrez: 1 11 2021
pubmed: 2 11 2021
medline: 2 11 2021
Statut: epublish

Résumé

There is a special interaction between the environment, soil microorganisms, and tea plants, which constitute the ecosystem of tea plantations. Influenced by environmental factors and human management, the changes in soil microbial community affected the growth, quality, and yield of tea plants. However, little is known about the composition and structure of soil bacterial and fungal communities in 100-year-old tea plantations and the mechanisms by which they are affected. In this regard, we characterized the microbiome of tea plantation soils by considering the bacterial and fungal communities in 448 soil samples from 101 ancient tea plantations in eight counties of Lincang city, which is one of the tea domestication centers in the world. 16S and Internal Transcribed Spacer (ITS) rRNA high-throughput amplicon sequencing techniques were applied in this study. The results showed that the abundance, diversity, and composition of the bacterial and fungal communities have different sensitivity with varying pH, altitude, and latitude. pH and altitude affect soil microbial communities, and bacterial communities are more sensitive than fungi in terms of abundance and diversity to pH. The highest α-diversity of bacterial communities is shown in the pH 4.50-5.00 and 2,200-m group, and fungi peaked in the pH 5.00-5.50 and 900-m group. Because of environmental and geographical factors, all microbes are similarly changing, and further correlations showed that the composition and structure of bacterial communities are more sensitive than fungal communities, which were affected by latitude and altitude. In conclusion, the interference of anthropogenic activities plays a more important role in governing fungal community selection than environmental or geographical factors, whereas for the bacterial community, it is more selective to environment adaptation than to adaptation to human activities.

Identifiants

pubmed: 34721345
doi: 10.3389/fmicb.2021.745225
pmc: PMC8555698
doi:

Types de publication

Journal Article

Langues

eng

Pagination

745225

Informations de copyright

Copyright © 2021 Kui, Xiang, Wang, Wang, Li, Li, Yan, Ye, Wang, Yang, Zhang, Zhang, Zhou, Gui, Xu, Chen, Zhang, Huang, Majeed, Sheng and Dong.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Ling Kui (L)

Shenzhen Qianhai Shekou Free Trade Zone Hospital, Shenzhen, China.

Guisheng Xiang (G)

Yunnan Agricultural University Applied Genomics Technology Laboratory, School of Biological Big Data, Yunnan Agricultural University, Kunming, China.

Ya Wang (Y)

College of Food Science and Technology, Yunnan Agricultural University, Kunming, China.

Zijun Wang (Z)

Yunnan Agricultural University Applied Genomics Technology Laboratory, School of Biological Big Data, Yunnan Agricultural University, Kunming, China.

Guorong Li (G)

Lincang Tea Research Institute, Lincang, China.

Dawei Li (D)

Yunnan Agricultural University Applied Genomics Technology Laboratory, School of Biological Big Data, Yunnan Agricultural University, Kunming, China.

Jing Yan (J)

Yunnan Agricultural University Applied Genomics Technology Laboratory, School of Biological Big Data, Yunnan Agricultural University, Kunming, China.

Shuang Ye (S)

Yunnan Agricultural University Applied Genomics Technology Laboratory, School of Biological Big Data, Yunnan Agricultural University, Kunming, China.

Chunping Wang (C)

Yunnan Agricultural University Applied Genomics Technology Laboratory, School of Biological Big Data, Yunnan Agricultural University, Kunming, China.

Ling Yang (L)

Yunnan Agricultural University Applied Genomics Technology Laboratory, School of Biological Big Data, Yunnan Agricultural University, Kunming, China.

Shiyu Zhang (S)

Yunnan Agricultural University Applied Genomics Technology Laboratory, School of Biological Big Data, Yunnan Agricultural University, Kunming, China.

Shuangyan Zhang (S)

Yunnan Agricultural University Applied Genomics Technology Laboratory, School of Biological Big Data, Yunnan Agricultural University, Kunming, China.

Ling Zhou (L)

Yunnan Agricultural University Applied Genomics Technology Laboratory, School of Biological Big Data, Yunnan Agricultural University, Kunming, China.
Longrun Pu'er Tea College of Yunnan Agricultural University, Kunming, China.

Heng Gui (H)

CAS Key Laboratory for Plant Diversity and Biogeography of East Asia, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China.
Centre for Mountain Futures, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China.

Jianchu Xu (J)

CAS Key Laboratory for Plant Diversity and Biogeography of East Asia, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China.
Centre for Mountain Futures, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China.

Wei Chen (W)

College of Agronomy and Biotechnology, Yunnan Agricultural University, Kunming, China.

Jun Zhang (J)

Shenzhen Qianhai Shekou Free Trade Zone Hospital, Shenzhen, China.

Tingyuan Huang (T)

Guangzhou Center for Disease Control and Prevention, Guangzhou, China.

Aasim Majeed (A)

Molecular Genetics Laboratory, Central University of Punjab, Lahore, India.

Jun Sheng (J)

State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, Yunnan Agricultural University, Kunming, China.
Yunnan Research Institute for Local Plateau Agriculture and Industry, Kunming, China.
Key Laboratory for Agro-Biodiversity and Pest Control of Ministry of Education, Yunnan Agricultural University, Kunming, China.

Yang Dong (Y)

State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, Yunnan Agricultural University, Kunming, China.
Yunnan Research Institute for Local Plateau Agriculture and Industry, Kunming, China.

Classifications MeSH