ArticleThe ISME journal2020
Combining whole-genome shotgun sequencing and rRNA gene amplicon analyses to improve detection of microbe-microbe interaction networks in plant leaves.
Article in The ISME journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.
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Who cites it
48 citing papers in PubMed.
- Article
- Functional memory of drought affects leaf chemical defenses and microbial interactions in aspen.The New phytologist · 2026Article
- Review
- Exploring sagebrush leaf microbial metagenomes from deep, host-derived sequencing.Microbiology spectrum · 2026Article
- Advancing Plant Microbiome Research Through Host DNA Depletion Techniques.Plant biotechnology journal · 2026Review
- Diverse banana endophytes reveal potential genotype-driven community structure affected by domestication.Frontiers in microbiology · 2026Article
- Targeted assembly recovers high ammonia monooxygenase diversity in mudflat intertides.mSystems · 2025Article
- A major trade-off between growth and defense in Arabidopsis thaliana can vanish in field conditions.PLoS biology · 2025Article
- Deterministic colonization arises early during the transition of soil bacteria to the phyllosphere and is shaped by plant-microbe interactions.Microbiome · 2025Article
- Efficient recovery and DNA extraction for algae-associated microbial communities.Frontiers in plant science · 2025Article
- Strong pairwise interactions do not drive interactions in a plant leaf associated microbial community.ISME communications · 2025Article
- Glucosinolate structural diversity shapes recruitment of a metabolic network of leaf-associated bacteria.Nature communications · 2024Article
- Continental-scale associations of Arabidopsis thaliana phyllosphere members with host genotype and drought.Nature microbiology · 2024Article
- Spatial metatranscriptomics resolves host-bacteria-fungi interactomes.Nature biotechnology · 2024Article
- Embracing complexity in plant-microbiome systems.Environmental microbiology reports · 2024Review
- Article
- Metagenomic sequencing and reconstruction of 82 microbial genomes from barley seed communities.Scientific data · 2024Article
- Unraveling plant-microbe interactions: can integrated omics approaches offer concrete answers?Journal of experimental botany · 2024Article
- The Interaction between Arbuscular Mycorrhizal Fungi (AMF) and Grass Endophyte (Journal of fungi (Basel, Switzerland) · 2024Review
- Omics approaches in understanding the benefits of plant-microbe interactions.Frontiers in microbiology · 2024Review
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Authors and funding
8 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Microorganisms from all domains of life establish associations with plants. Although some harm the plant, others antagonize pathogens or prime the plant immune system, support the acquisition of nutrients, tune plant hormone levels, or perform additional services. Most culture-independent plant microbiome research has focused on amplicon sequencing of the 16S rRNA gene and/or the internal transcribed spacer (ITS) of rRNA genomic loci, which show the relative abundance of the microbes to each other. Here, we describe shotgun sequencing of 275 wild Arabidopsis thaliana leaf microbiomes from southwest Germany, with additional bacterial 16S and eukaryotic ITS1 rRNA amplicon data from 176 of these samples. Shotgun data, which unlike the amplicon data capture the ratio of microbe to plant DNA, enable scaling of microbial read abundances to reflect the microbial load on the host. In a more cost-effective hybrid strategy, we show they also allow a similar scaling of amplicon data to overcome compositionality problems. Our wild plants were dominated by bacterial sequences, with eukaryotes contributing only a minority of reads. Microbial membership showed weak associations with both site of origin and plant genotype, both of which were highly confounded in this dataset. There was large variation among microbiomes, with one extreme comprising samples of low complexity and a high load of microorganisms typical of infected plants, and the other extreme being samples of high complexity and a low microbial load. Critically, considering absolute microbial load led to fundamentally different conclusions about microbiome assembly and the interaction networks among major taxa.
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