Specialized metabolic functions of keystone taxa sustain soil microbiome stability

Xun, Weibing; Liu, Yunpeng; Li, Wei; Ren, Yi; Xiong, Wu; Xu, Zhihui; Zhang, Nan; Miao, Youzhi; Shen, Qirong; Zhang, Ruifu

doi:10.1186/s40168-020-00985-9

Cited by 352 publications

(170 citation statements)

References 80 publications

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“…Similarly, the relative abundances of Mortierella and Trichoderma are higher in healthy than in diseased bayberry rhizosphere soil, while fungi from the two genera can not only promote plant growth [26,27], but also degrade lignin and cellulose [36,37], which results in increases in organic matter and magnesium content, as well as available nitrogen, calcium and phosphorus. However, bacteria from the genus Rhizomicrobium have been reported to participate in phosphate and phosphite metabolism in soil [38]. Therefore, it can be speculated that the increase in available phosphorus in diseased bayberry rhizosphere soil may be due to the fact that Rhizomicrobium has a greater effect on available phosphorus compared to Acidothermus, Mortierella and Trichoderma.…”

Section: Soil Propertiesmentioning

confidence: 99%

The Damage Caused by Decline Disease in Bayberry Plants through Changes in Soil Properties, Rhizosphere Microbial Community Structure and Metabolites

Ren

Wang

et al. 2021

Plants

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Decline disease causes serious damage and rapid death in bayberry, an important fruit tree in south China, but the cause of this disease remains unclear. The aim of this study was to investigate soil quality, microbial community structure and metabolites of rhizosphere soil samples from healthy and diseased trees. The results revealed a significant difference between healthy and diseased bayberry in soil properties, microbial community structure and metabolites. Indeed, the decline disease caused a 78.24% and 78.98% increase in Rhizomicrobium and Cladophialophora, but a 28.60%, 57.18%, 38.84% and 68.25% reduction in Acidothermus, Mortierella, Trichoderma and Geminibasidium, respectively, compared with healthy trees, based on 16S and ITS amplicon sequencing of soil microflora. Furthermore, redundancy discriminant analysis of microbial communities and soil properties indicated that the main variables of bacterial and fungal communities included pH, organic matter, magnesium, available phosphorus, nitrogen and calcium, which exhibited a greater influence in bacterial communities than in fungal communities. In addition, there was a high correlation between the changes in microbial community structure and secondary metabolites. Indeed, GC–MS metabolomics analysis showed that the healthy and diseased samples differed over six metabolic pathways, including thiamine metabolism, phenylalanine–tyrosine–tryptophan biosynthesis, valine–leucine–isoleucine biosynthesis, phenylalanine metabolism, fatty acid biosynthesis and fatty acid metabolism, where the diseased samples showed a 234.67% and 1007.80% increase in palatinitol and cytidine, respectively, and a 17.37%–8.74% reduction in the other 40 metabolites compared to the healthy samples. Overall, these results revealed significant changes caused by decline disease in the chemical properties, microbiota and secondary metabolites of the rhizosphere soils, which provide new insights for understanding the cause of this bayberry disease.

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Section: Soil Propertiesmentioning

confidence: 99%

The Damage Caused by Decline Disease in Bayberry Plants through Changes in Soil Properties, Rhizosphere Microbial Community Structure and Metabolites

Ren

Wang

et al. 2021

Plants

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“…This might indicate that waterlogging is less harmful to neutral soils than acidic soils, at least on the level of the microbial functions. However, microorganisms related to the phosphorus cycle (e.g., Flavisolibacter, Massilia, and Gemmatimonas) were depleted in neutral soils [89,90,92]. In this study, acidic soil had lower phosphorus content than neutral soil.…”

Section: Discussionmentioning

confidence: 61%

“…Nitrospira was the core microorganism shared by V4 and PacBio sequencing, while Bacillus was the core microorganism shared by V4 and LoopSeq sequencing. Nitrospira is the most common genus affecting soil nitrogen metabolism [92][93][94]. Bacillus can utilize multiple electron donors or collectors to enrich nutrients [95] and maintain normal root growth [72].…”

Section: Discussionmentioning

confidence: 99%

Effects of Waterlogging on Soybean Rhizosphere Microbial Community Profiled Using Illumina MiSeq, LoopSeq, and PacBio 16S rRNA Genes Sequences

Ling

Liu

et al. 2021

Preprint

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Background: Waterlogging on the global environment has led to a significant decline in crop yields. However, the response of plant-associated microbes to waterlogging stress on different soils is not known. Moreover, there are few reports on whether this response is influenced by different sequencing methods. In this study, the effects of waterlogging on soybean rhizosphere microbial structure on two types of soil were examined, using a short reading 16S rRNA sequencing variable region V4 and two full-length 16S rRNA sequencing variable regions V1-V9.Results: The results revealed some similarities and differences in three sequencing methods for soybean rhizosphere microbial response to waterlogging stress. Based on CPCoA analysis, all the sequencing methods showed that waterlogging on both types of soil significantly affected the bacterial community structure of the soybean rhizosphere, and increased the relative abundance of Geobacter. However, the full-length sequencing methods had higher classification resolution than short-read sequencing (except phylum level of all sequencing methods and class level of LoopSeq sequencing). Further, analysis on OTU level and network showed that waterlogging increased the abundance of some microorganisms related to nitrogen cycle using V4 sequencing, and microorganisms related to phosphorus cycling when using two full-length sequencing methods. This is in line with the core microbial analysis. Environmental factors affecting the structure of microbial communities differed among sequencing methods.Conclusions: In summary, this piece of work detected the effects of waterlogging on soybean rhizosphere microbes using three sequencing methods. Some functional microbes were enriched in the rhizosphere, which may benefit soybean in resisting waterlogging stress. On the other hand, there were several differences in results among the three sequencing methods which might affect the response of rhizosphere microbial structure to stress. Our analysis of sequencing methods on various levels provides some useful information on environmental samples sequencing.

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“…The Sloan neutral community model prediction and statistics were performed by "MicEco" package in R [76], and the overall fitness of the model (R 2 value) and the proxy of dispersal limitation (estimated migration rate, m value) were calculated at the same time [45]. The beta Nearest Taxon Index (βNTI) values, an index representing the null assembly hypothesis, were calculated by "picante" package [77] in R. The βNTI value was used to infer the major driving forces controlling the community assembly process. A βNTI ≥ 2 is considered of variable selection of deterministic processes and βNTI ≤ 2 is considered of variable selection of deterministic processes, while |βNTI| < 2 considered of stochastic processes.…”

Section: Discussionmentioning

confidence: 99%

Sequencing Introduced False Positive Rare Taxa Lead to Distorted Microbial Community Diversity, Assembly, and Interaction Interpretation in Amplicon Studies

Jia

Zhao

Guo³

et al. 2021

Preprint

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Background: Due to the inherent scarcity of the microbial rare taxa, it is difficult to distinguish between bona fide rare taxa and potential false positives in metabarcoding amplicon sequencing studies. Although recently developed quality control and clustering or denoising algorithms could remove sequencing errors or non-biological artifact reads, no algorithm could remove high quality reads from sample-wise cross contaminations introduced by index misassignment. Results: We thoroughly evaluated the rate of index misassignment of the mostly used NovaSeq 6000 and DNBSEQ-G400 sequencing platforms using both commercial and customized mock communities, and observed significant higher (5.68% vs 0.08%) fraction of potential false positive reads for NovaSeq 6000 compared to DNBSEQ-G400 in. Significant batch effects could be caused by the randomly detected false positive or false negative rare taxa. These false detections introduced by index misassignment could also lead to inflated alpha diversity for relatively simple samples while underestimated alpha diversity for complex samples. Further test using a set of cow rumen samples reported differential rare taxa by different sequencing platforms. Correlation test of the rare taxa detected by each sequencing platform demonstrated that the Novaseq 6000 platform detected rare taxa had a much lower possibility to be correlated with the physiochemical properties of rumen fluid. Community assembly mechanism and microbial network association analysis indicated that false positive or negative rare taxa detection could lead to distorted community assembly process and identification of even fake keystone species of the community, one of which was confirmed negative by PCR cloning and following Sanger sequencing. Conclusions: Metabarcoding amplicon sequencing process may introduce scarce but not neglectable false positives. We highly suggest proper positive and negative controls and technical replicate settings, and proper sequencing platform selection in future amplicon studies, especially when the microbial rare biosphere should be focused.

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Specialized metabolic functions of keystone taxa sustain soil microbiome stability

Cited by 352 publications

References 80 publications

The Damage Caused by Decline Disease in Bayberry Plants through Changes in Soil Properties, Rhizosphere Microbial Community Structure and Metabolites

The Damage Caused by Decline Disease in Bayberry Plants through Changes in Soil Properties, Rhizosphere Microbial Community Structure and Metabolites

Effects of Waterlogging on Soybean Rhizosphere Microbial Community Profiled Using Illumina MiSeq, LoopSeq, and PacBio 16S rRNA Genes Sequences

Sequencing Introduced False Positive Rare Taxa Lead to Distorted Microbial Community Diversity, Assembly, and Interaction Interpretation in Amplicon Studies

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