Biology subjects

Poersch, K.

Publications and source records attributed to Poersch, K..

3 recordsLinked to original sources

bioRxiv2024

Field conditions greatly modify a major growth-defense tradeoff in Arabidopsis thaliana

When plants defend themselves from pathogens, this often comes with a trade-off: the same genes that protect a plant from disease can also reduce its growth and fecundity in the absence of pathogens. One protein implicated in a major growth-defense trade-off in the plant Arabidopsis thaliana is ACCELERATED CELL DEATH 6 (ACD6), an ion channel that modulates salicylic acid (SA) synthesis to potentiate a wide range of defenses. Wild plant populations maintain significant functional variation in the ACD6 gene, with some alleles making the protein hyperactive. In the greenhouse, plants with hyperactive ACD6 alleles are resistant to diverse pathogens, yet are of smaller stature, their leaves senesce earlier, and they set fewer seeds. We hypothesized that such hyperactive alleles would not only affect the growth of microbial pathogens, but also more generally leaf microbiome assembly in the wild. To test this, we grew plants with hyperactive, standard, and defective ACD6 alleles in the same field-collected soil, both in climate-controlled conditions and outdoors. We surveyed visual phenotypes, gene expression, hormone levels, seed production, and the microbiome in each environment. To our surprise, we discovered that mature field plants, in stark contrast to greenhouse plants, were unaffected by their ACD6 genotype, suggesting that additional abiotic and/or microbial signals present outdoors - but not in the greenhouse - greatly modulate ACD6 activity.

plant biology↗

bioRxiv2021

Contrasting patterns of microbial dominance in the Arabidopsis thaliana phyllosphere

Sphingomonas is one of the most abundant bacterial genera in the phyllosphere of wild Arabidopsis thaliana, but relative to Pseudomonas, the ecology of Sphingomonas and its interaction with plants remains elusive. We analyzed the genomic features of over 400 Sphingomonas isolates collected from local A. thaliana populations, which revealed high intergenomic diversity, in contrast to genetically much more uniform Pseudomonas isolates found in the same host populations. Variation in Sphingomonas plasmid complements and additional genomic features suggest high adaptability of this genus, and the widespread presence of protein secretion systems hints at frequent biotic interactions. While some of the isolates showed plant-protective properties in lab tests, this was a rare trait. To begin to understand the extent of strain sharing across alternate hosts, we employed amplicon sequencing and a novel bulk-culturing metagenomics approach on both A. thaliana and neighboring plants. Our data reveal that Sphingomonas and Pseudomonas both thrive on other diverse plant hosts, but that Sphingomonas is a poor competitor in dying or dead leaves.

ecology↗

bioRxiv2019

Combining whole genome shotgun sequencing and rDNA amplicon analyses to improve detection of microbe-microbe interaction networks in plant leaves

Microorganisms from all domains of life establish associations with plants. Although some harm the plant, others antagonize pathogens or prime the plant immune system, acquire nutrients, tune plant hormone levels, or perform additional services. Most culture-independent plant microbiome research has focused on amplicon sequencing of 16S rDNA and/or the internal transcribed spacer (ITS) of rDNA loci, but the decreasing cost of high-throughput sequencing has made shotgun metagenome sequencing increasingly accessible. Here, we describe shotgun sequencing of 275 wild Arabidopsis thaliana leaf microbiomes from southwest Germany, with additional bacterial 16S rDNA and eukaryotic ITS1 amplicon data from 176 of these samples. The shotgun data were dominated by bacterial sequences, with eukaryotes contributing only a minority of reads. For shotgun and amplicon data, 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. We use the metagenome data, which captures the ratio of bacterial to plant DNA in leaves of wild plants, to scale the 16S rDNA amplicon data such that they reflect absolute bacterial abundance. We show that this cost-effective hybrid strategy overcomes compositionality problems in amplicon data and leads to fundamentally different conclusions about microbiome community assembly.

genomics↗