Effects of Waterlogging on Soybean Rhizosphere Bacterial Community Using V4, LoopSeq, and PacBio 16S rRNA Sequence

Yu, Tao; Ling, Cheng; Liu, Qi; Wang, Shasha; Zhou, Yuan; Huang, Zhong; Meifang, Tang; Nian, Hai; Lian, Tengxiang

doi:10.1128/spectrum.02011-21

Cited by 19 publications

(12 citation statements)

References 107 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Megamonas rupellensis, Bacteroides plebeius, and Bacteroides coprocola were the dominant species in both sequencing methods. Previous studies have reported that the community profiles using synthetic long-read sequencing technologies (LoopSeq) and PacBio CCS from the same fecal samples were comparable ( Yu et al, 2022 ). Compared to PacBio 16S sequencing, 16S-FAS-NGS offered high fidelity species identification but reduced sequencing prices, which was an attractive technology with species-level resolution.…”

Section: Resultsmentioning

confidence: 99%

16S-FASAS: an integrated pipeline for synthetic full-length 16S rRNA gene sequencing data analysis

Zhang

Lin

Chang

et al. 2022

PeerJ

View full text Add to dashboard Cite

Background The full-length 16S rRNA sequencing can better improve the taxonomic and phylogenetic resolution compared to the partial 16S rRNA gene sequencing. The 16S-FAS-NGS (16S rRNA full-length amplicon sequencing based on a next-generation sequencing platform) technology can generate high-quality, full-length 16S rRNA gene sequences using short-read sequencers, together with assembly procedures. However there is a lack of a data analysis suite that can help process and analyze the synthetic long read data. Results Herein, we developed software named 16S-FASAS (16S full-length amplicon sequencing data analysis software) for 16S-FAS-NGS data analysis, which provided high-fidelity species-level microbiome data. 16S-FASAS consists of data quality control, de novo assembly, annotation, and visualization modules. We verified the performance of 16S-FASAS on both mock and fecal samples. In mock communities, we proved that taxonomy assignment by MegaBLAST had fewer misclassifications and tended to find more low abundance species than the USEARCH-UNOISE3-based classifier, resulting in species-level classification of 85.71% (6/7), 85.71% (6/7), 72.72% (8/11), and 70% (7/10) of the target bacteria. When applied to fecal samples, we found that the 16S-FAS-NGS datasets generated contigs grouped into 60 and 56 species, from which 71.62% (43/60) and 76.79% (43/56) were shared with the Pacbio datasets. Conclusions 16S-FASAS is a valuable tool that helps researchers process and interpret the results of full-length 16S rRNA gene sequencing. Depending on the full-length amplicon sequencing technology, the 16S-FASAS pipeline enables a more accurate report on the bacterial complexity of microbiome samples. 16S-FASAS is freely available for use at https://github.com/capitalbio-bioinfo/FASAS.

show abstract

Section: Resultsmentioning

confidence: 99%

16S-FASAS: an integrated pipeline for synthetic full-length 16S rRNA gene sequencing data analysis

Zhang

Lin

Chang

et al. 2022

PeerJ

View full text Add to dashboard Cite

show abstract

“…The total rhizosphere soil of total plants of RS and RSSI plant treatments was removed at 30 dpi by shaking the root manually; meanwhile, the basal soil (BS, non-rhizosphere soil) was collected as the control [ 57 ]. Furthermore, the soil samples were mixed and used for three separate determinations of soil chemical properties, soil enzymes and soil microorganisms, and metabolite profiles.…”

Section: Methodsmentioning

confidence: 99%

Silicon Application for the Modulation of Rhizosphere Soil Bacterial Community Structures and Metabolite Profiles in Peanut under Ralstonia solanacearum Inoculation

Deng

Líu

et al. 2023

IJMS

View full text Add to dashboard Cite

Silicon (Si) has been shown to promote peanut growth and yield, but whether Si can enhance the resistance against peanut bacterial wilt (PBW) caused by Ralstonia solanacearum, identified as a soil-borne pathogen, is still unclear. A question regarding whether Si enhances the resistance of PBW is still unclear. Here, an in vitro R. solanacearum inoculation experiment was conducted to study the effects of Si application on the disease severity and phenotype of peanuts, as well as the microbial ecology of the rhizosphere. Results revealed that Si treatment significantly reduced the disease rate, with a decrement PBW severity of 37.50% as compared to non-Si treatment. The soil available Si (ASi) significantly increased by 13.62–44.87%, and catalase activity improved by 3.01–3.10%, which displayed obvious discrimination between non-Si and Si treatments. Furthermore, the rhizosphere soil bacterial community structures and metabolite profiles dramatically changed under Si treatment. Three significantly changed bacterial taxa were observed, which showed significant abundance under Si treatment, whereas the genus Ralstonia genus was significantly suppressed by Si. Similarly, nine differential metabolites were identified to involve into unsaturated fatty acids via a biosynthesis pathway. Significant correlations were also displayed between soil physiochemical properties and enzymes, the bacterial community, and the differential metabolites by pairwise comparisons. Overall, this study reports that Si application mediated the evolution of soil physicochemical properties, the bacterial community, and metabolite profiles in the soil rhizosphere, which significantly affects the colonization of the Ralstonia genus and provides a new theoretical basis for Si application in PBW prevention.

show abstract

“…Plant-associated microbial communities are well known for their impact on the ecology and evolution of their host ( Trivedi et al, 2020 ; Malacrinò et al, 2022a ). The structure of plant microbiomes largely differentiate within the same plant (e.g., between roots, leaves, fruits, flowers, seeds), and within the same compartment (e.g., different tissues within the same organ; Abdelfattah et al, 2016 ; Dastogeer et al, 2020 ; Trivedi et al, 2020 ), and it is influenced by several factors, including soil ( Zarraonaindia et al, 2015 ; Malacrinò et al, 2021a ), herbivores ( French et al, 2021 ; Malacrinò et al, 2021a , b ; Frew, 2022 ), pathogens ( Ginnan et al, 2020 ; Wen et al, 2020 ; Ewing et al, 2021 ), and abiotic stresses ( Vescio et al, 2021 ; Yu et al, 2022 ). Despite the great deal of research in this field, we still know little about the rules that govern the assembly of plant microbiomes.…”

Section: Introductionmentioning

confidence: 99%

Plant genotype influence the structure of cereal seed fungal microbiome

et al. 2023

View full text Add to dashboard Cite

Plant genotype is a crucial factor for the assembly of the plant-associated microbial communities. However, we still know little about the variation of diversity and structure of plant microbiomes across host species and genotypes. Here, we used six species of cereals (Avena sativa, Hordeum vulgare, Secale cereale, Triticum aestivum, Triticum polonicum, and Triticum turgidum) to test whether the plant fungal microbiome varies across species, and whether plant species use different mechanisms for microbiome assembly focusing on the plant ears. Using ITS2 amplicon metagenomics, we found that host species influences the diversity and structure of the seed-associated fungal communities. Then, we tested whether plant genotype influences the structure of seed fungal communities across different cultivars of T. aestivum (Aristato, Bologna, Rosia, and Vernia) and T. turgidum (Capeiti, Cappelli, Mazzancoio, Trinakria, and Timilia). We found that cultivar influences the seed fungal microbiome in both species. We found that in T. aestivum the seed fungal microbiota is more influenced by stochastic processes, while in T. turgidum selection plays a major role. Collectively, our results contribute to fill the knowledge gap on the wheat seed microbiome assembly and, together with other studies, might contribute to understand how we can manipulate this process to improve agriculture sustainability.

show abstract

Effects of Waterlogging on Soybean Rhizosphere Bacterial Community Using V4, LoopSeq, and PacBio 16S rRNA Sequence

Abstract: 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.

Cited by 19 publications

References 107 publications

16S-FASAS: an integrated pipeline for synthetic full-length 16S rRNA gene sequencing data analysis

16S-FASAS: an integrated pipeline for synthetic full-length 16S rRNA gene sequencing data analysis

Silicon Application for the Modulation of Rhizosphere Soil Bacterial Community Structures and Metabolite Profiles in Peanut under Ralstonia solanacearum Inoculation

Plant genotype influence the structure of cereal seed fungal microbiome

Contact Info

Product

Resources

About