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Effects of Waterlogging on Soybean Rhizosphere Bacterial Community Using V4, LoopSeq, and PacBio 16S rRNA Sequence
Waterlogging causes a significant reduction in soil oxygen levels, which in turn negatively affects soil nutrient use efficiency and crop yields. Rhizosphere microbes can help plants to better use nutrients and thus better adapt to this stress, while it is not clear how the plant-associated microbes...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society for Microbiology
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8849089/ https://www.ncbi.nlm.nih.gov/pubmed/35171049 http://dx.doi.org/10.1128/spectrum.02011-21 |
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author | Yu, Taobing Cheng, Lang Liu, Qi Wang, Shasha Zhou, Yuan Zhong, Hongbin Tang, Meifang Nian, Hai Lian, Tengxiang |
author_facet | Yu, Taobing Cheng, Lang Liu, Qi Wang, Shasha Zhou, Yuan Zhong, Hongbin Tang, Meifang Nian, Hai Lian, Tengxiang |
author_sort | Yu, Taobing |
collection | PubMed |
description | Waterlogging causes a significant reduction in soil oxygen levels, which in turn negatively affects soil nutrient use efficiency and crop yields. Rhizosphere microbes can help plants to better use nutrients and thus better adapt to this stress, while it is not clear how the plant-associated microbes respond to waterlogging stress. There are also few reports on whether this response is influenced by different sequencing methods and by different soils. In this study, using partial 16S rRNA sequencing targeting the V4 region and two full-length 16S rRNA sequencing approaches targeting the V1 to V9 regions, the effects of waterlogging on soybean rhizosphere bacterial structure in two types of soil were examined. Our results showed that, compared with the partial 16S sequencing, full-length sequencing, both LoopSeq and Pacific Bioscience (PacBio) 16S sequencing, had a higher resolution. On both types of soil, all the sequencing methods showed that waterlogging significantly affected the bacterial community structure of the soybean rhizosphere and increased the relative abundance of Geobacter. Furthermore, modular analysis of the cooccurrence network showed that waterlogging increased the relative abundance of some microorganisms related to nitrogen cycling when using V4 sequencing and increased the microorganisms related to phosphorus cycling when using LoopSeq and PacBio 16S sequencing methods. Core microorganism analysis further revealed that the enriched members of different species might play a central role in maintaining the stability of bacterial community structure and ecological functions. Together, our study explored the role of microorganisms enriched at the rhizosphere under waterlogging in assisting soybeans to resist stress. Furthermore, compared to partial and PacBio 16S sequencing, LoopSeq offers improved accuracy and reduced sequencing prices, respectively, and enables accurate species-level and strain identification from complex environmental microbiome samples. IMPORTANCE Soybeans are important oil-bearing crops, and waterlogging has caused substantial decreases in soybean production all over the world. The microbes associated with the host have shown the ability to promote plant growth, nutrient absorption, and abiotic resistance. High-throughput sequencing of partial 16S rRNA is the most commonly used method to analyze the microbial community. However, partial sequencing cannot provide correct classification information below the genus level, which greatly limits our research on microbial ecology. In this study, the effects of waterlogging on soybean rhizosphere microbial structure in two soil types were explored using partial 16S rRNA and full-length 16S gene sequencing by LoopSeq and Pacific Bioscience (PacBio). The results showed that full-length sequencing had higher classification resolution than partial sequencing. Three sequencing methods all indicated that rhizosphere bacterial community structure was significantly impacted by waterlogging, and the relative abundance of Geobacter was increased in the rhizosphere in both soil types after suffering waterlogging. Moreover, the core microorganisms obtained by different sequencing methods all contain species related to nitrogen cycling. Together, our study not only explored the role of microorganisms enriched at the rhizosphere level under waterlogging in assisting soybean to resist stress but also showed that LoopSeq sequencing is a less expensive and more convenient method for full-length sequencing by comparing different sequencing methods. |
format | Online Article Text |
id | pubmed-8849089 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Society for Microbiology |
record_format | MEDLINE/PubMed |
spelling | pubmed-88490892022-02-17 Effects of Waterlogging on Soybean Rhizosphere Bacterial Community Using V4, LoopSeq, and PacBio 16S rRNA Sequence Yu, Taobing Cheng, Lang Liu, Qi Wang, Shasha Zhou, Yuan Zhong, Hongbin Tang, Meifang Nian, Hai Lian, Tengxiang Microbiol Spectr Research Article Waterlogging causes a significant reduction in soil oxygen levels, which in turn negatively affects soil nutrient use efficiency and crop yields. Rhizosphere microbes can help plants to better use nutrients and thus better adapt to this stress, while it is not clear how the plant-associated microbes respond to waterlogging stress. There are also few reports on whether this response is influenced by different sequencing methods and by different soils. In this study, using partial 16S rRNA sequencing targeting the V4 region and two full-length 16S rRNA sequencing approaches targeting the V1 to V9 regions, the effects of waterlogging on soybean rhizosphere bacterial structure in two types of soil were examined. Our results showed that, compared with the partial 16S sequencing, full-length sequencing, both LoopSeq and Pacific Bioscience (PacBio) 16S sequencing, had a higher resolution. On both types of soil, all the sequencing methods showed that waterlogging significantly affected the bacterial community structure of the soybean rhizosphere and increased the relative abundance of Geobacter. Furthermore, modular analysis of the cooccurrence network showed that waterlogging increased the relative abundance of some microorganisms related to nitrogen cycling when using V4 sequencing and increased the microorganisms related to phosphorus cycling when using LoopSeq and PacBio 16S sequencing methods. Core microorganism analysis further revealed that the enriched members of different species might play a central role in maintaining the stability of bacterial community structure and ecological functions. Together, our study explored the role of microorganisms enriched at the rhizosphere under waterlogging in assisting soybeans to resist stress. Furthermore, compared to partial and PacBio 16S sequencing, LoopSeq offers improved accuracy and reduced sequencing prices, respectively, and enables accurate species-level and strain identification from complex environmental microbiome samples. IMPORTANCE Soybeans are important oil-bearing crops, and waterlogging has caused substantial decreases in soybean production all over the world. The microbes associated with the host have shown the ability to promote plant growth, nutrient absorption, and abiotic resistance. High-throughput sequencing of partial 16S rRNA is the most commonly used method to analyze the microbial community. However, partial sequencing cannot provide correct classification information below the genus level, which greatly limits our research on microbial ecology. In this study, the effects of waterlogging on soybean rhizosphere microbial structure in two soil types were explored using partial 16S rRNA and full-length 16S gene sequencing by LoopSeq and Pacific Bioscience (PacBio). The results showed that full-length sequencing had higher classification resolution than partial sequencing. Three sequencing methods all indicated that rhizosphere bacterial community structure was significantly impacted by waterlogging, and the relative abundance of Geobacter was increased in the rhizosphere in both soil types after suffering waterlogging. Moreover, the core microorganisms obtained by different sequencing methods all contain species related to nitrogen cycling. Together, our study not only explored the role of microorganisms enriched at the rhizosphere level under waterlogging in assisting soybean to resist stress but also showed that LoopSeq sequencing is a less expensive and more convenient method for full-length sequencing by comparing different sequencing methods. American Society for Microbiology 2022-02-16 /pmc/articles/PMC8849089/ /pubmed/35171049 http://dx.doi.org/10.1128/spectrum.02011-21 Text en Copyright © 2022 Yu et al. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Article Yu, Taobing Cheng, Lang Liu, Qi Wang, Shasha Zhou, Yuan Zhong, Hongbin Tang, Meifang Nian, Hai Lian, Tengxiang Effects of Waterlogging on Soybean Rhizosphere Bacterial Community Using V4, LoopSeq, and PacBio 16S rRNA Sequence |
title | Effects of Waterlogging on Soybean Rhizosphere Bacterial Community Using V4, LoopSeq, and PacBio 16S rRNA Sequence |
title_full | Effects of Waterlogging on Soybean Rhizosphere Bacterial Community Using V4, LoopSeq, and PacBio 16S rRNA Sequence |
title_fullStr | Effects of Waterlogging on Soybean Rhizosphere Bacterial Community Using V4, LoopSeq, and PacBio 16S rRNA Sequence |
title_full_unstemmed | Effects of Waterlogging on Soybean Rhizosphere Bacterial Community Using V4, LoopSeq, and PacBio 16S rRNA Sequence |
title_short | Effects of Waterlogging on Soybean Rhizosphere Bacterial Community Using V4, LoopSeq, and PacBio 16S rRNA Sequence |
title_sort | effects of waterlogging on soybean rhizosphere bacterial community using v4, loopseq, and pacbio 16s rrna sequence |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8849089/ https://www.ncbi.nlm.nih.gov/pubmed/35171049 http://dx.doi.org/10.1128/spectrum.02011-21 |
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