Dataset Information

Host-Associated Quantitative Abundance Profiling Reveals the Microbial Load Variation of Root Microbiome.

ABSTRACT: Plant-associated microbes are critical for plant growth and survival under natural environmental conditions. To date, most plant microbiome studies involving high-throughput amplicon sequencing have focused on the relative abundance of microbial taxa. However, this technique does not assess the total microbial load and the abundance of individual microbes relative to the amount of host plant tissues. Here, we report the development of a host-associated quantitative abundance profiling (HA-QAP) method that can accurately examine total microbial load and colonization of individual root microbiome members relative to host plants by the copy-number ratio of microbial marker gene to plant genome. We validate the HA-QAP method using mock experiments, perturbation experiments, and metagenomic sequencing. The HA-QAP method eliminates the generation of spurious outputs in the classical method based on microbial relative abundance, and reveals the load of root microbiome to host plants. Using the HA-QAP method, we found that the copy-number ratios of microbial marker genes to plant genome range from 1.07 to 6.61 for bacterial 16S rRNA genes and from 0.40 to 2.26 for fungal internal transcribed spacers in the root microbiome samples from healthy rice and wheat. Furthermore, using HA-QAP we found that an increase in total microbial load represents a key feature of changes in root microbiome of rice plants exposed to drought stress and of wheat plants with root rot disease, which significantly influences patterns of differential taxa and species interaction networks. Given its accuracy and technical feasibility, HA-QAP would facilitate our understanding of genuine interactions between root microbiome and plants.

SUBMITTER: Guo X

PROVIDER: S-EPMC7747982 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Host-Associated Quantitative Abundance Profiling Reveals the Microbial Load Variation of Root Microbiome.

Guo Xiaoxuan X Zhang Xiaoning X Qin Yuan Y Liu Yong-Xin YX Zhang Jingying J Zhang Na N Wu Kun K Qu Baoyuan B He Zishan Z Wang Xin X Zhang Xinjian X Hacquard Stéphane S Fu Xiangdong X Bai Yang Y

Plant communications 20190916 1

Plant-associated microbes are critical for plant growth and survival under natural environmental conditions. To date, most plant microbiome studies involving high-throughput amplicon sequencing have focused on the relative abundance of microbial taxa. However, this technique does not assess the total microbial load and the abundance of individual microbes relative to the amount of host plant tissues. Here, we report the development of a host-associated quantitative abundance profiling (HA-QAP) m ...[more]

PMID: 33404537

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Project description:Plant-associated microorganisms have been shown to critically affect host physiology and performance, suggesting that evolution and ecology of plants and animals can only be understood in a holobiont (host and its associated organisms) context. Host-associated microbial community structures are affected by abiotic and host factors, and increased attention is given to the role of the microbiome in interactions such as pathogen inhibition. However, little is known about how these factors act on the microbial community, and especially what role microbe-microbe interaction dynamics play. We have begun to address this knowledge gap for phyllosphere microbiomes of plants by simultaneously studying three major groups of Arabidopsis thaliana symbionts (bacteria, fungi and oomycetes) using a systems biology approach. We evaluated multiple potential factors of microbial community control: we sampled various wild A. thaliana populations at different times, performed field plantings with different host genotypes, and implemented successive host colonization experiments under lab conditions where abiotic factors, host genotype, and pathogen colonization was manipulated. Our results indicate that both abiotic factors and host genotype interact to affect plant colonization by all three groups of microbes. Considering microbe-microbe interactions, however, uncovered a network of interkingdom interactions with significant contributions to community structure. As in other scale-free networks, a small number of taxa, which we call microbial "hubs," are strongly interconnected and have a severe effect on communities. By documenting these microbe-microbe interactions, we uncover an important mechanism explaining how abiotic factors and host genotypic signatures control microbial communities. In short, they act directly on "hub" microbes, which, via microbe-microbe interactions, transmit the effects to the microbial community. We analyzed two "hub" microbes (the obligate biotrophic oomycete pathogen Albugo and the basidiomycete yeast fungus Dioszegia) more closely. Albugo had strong effects on epiphytic and endophytic bacterial colonization. Specifically, alpha diversity decreased and beta diversity stabilized in the presence of Albugo infection, whereas they otherwise varied between plants. Dioszegia, on the other hand, provided evidence for direct hub interaction with phyllosphere bacteria. The identification of microbial "hubs" and their importance in phyllosphere microbiome structuring has crucial implications for plant-pathogen and microbe-microbe research and opens new entry points for ecosystem management and future targeted biocontrol. The revelation that effects can cascade through communities via "hub" microbes is important to understand community structure perturbations in parallel fields including human microbiomes and bioprocesses. In particular, parallels to human microbiome "keystone" pathogens and microbes open new avenues of interdisciplinary research that promise to better our understanding of functions of host-associated microbiomes.

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Dataset Information

Host-Associated Quantitative Abundance Profiling Reveals the Microbial Load Variation of Root Microbiome.

Publications

Host-Associated Quantitative Abundance Profiling Reveals the Microbial Load Variation of Root Microbiome.

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