Biology subjects

Bollmann-Giolai, A.

Publications and source records attributed to Bollmann-Giolai, A..

4 recordsLinked to original sources

bioRxiv2025

Arabidopsis arenosa influences its microbiome as a serpentine soil adaptation strategy

There is growing evidence that microbes can facilitate plant growth in metal-rich soils. However, our current understanding of how plants recruit their microbiomes under abiotic stress remains incomplete. Serpentine soils are elementally skewed, with high concentrations of magnesium and nickel, often accompanied by other heavy metals, which can limit calcium availability and present unique challenges to plant growth. These soils are also nutrient-poor, prone to erosion, and have low water-holding capacity. To date, the mechanisms by which plants adapt to serpentine soils remain poorly understood and the role of plant-associated microbiomes in this process has not been described. Here, we focus on Arabidopsis arenosa populations adapted to serpentine conditions and investigate their bacterial and fungal microbiomes to better understand the role of plant-associated microbes in serpentine adaptation. We show that serpentine soils harbour distinct plant-associated microbiomes across different plant niches and that the plant genetic background plays a key role in shaping microbial community composition. Finally, we identify serpentine-specific bacterial and fungal variants that may contribute to plant adaptation under these challenging soil conditions.

ecology↗

bioRxiv2024

Local cryptic diversity in salinity adaptation mechanisms in a wild outcrossing Brassica

It is generally assumed that populations of the same species should evolve shared mechanisms of adaptation to common stressors due to evolutionary constraint. Here, we describe a novel system of within-species local adaptation to coastal habitats, Brassica fruticulosa, and detail surprising mechanistic variability in adaptive responses to extreme salinity. These radically different adaptive responses in neighbouring populations are evidenced by transcriptomes, diverse physiological outputs, and completely distinct genomic selective landscapes. In response to high salinity Northern Catalonian populations restrict root-to-shoot Na+ transport, favouring K+ uptake. Contrastingly, Central Catalonian populations accumulate Na+ in leaves and compensate for the osmotic imbalance with compatible solutes such as proline and elevated Ca2+. Despite contrasting responses, both metapopulations were salinity tolerant relative to all inland accessions. To characterise the genomic basis of these two divergent adaptive strategies in an otherwise non-saline-tolerant endemic, we generate a long-read-based genome and population sequencing of 18 populations (9 inland, 9 coastal) across the B. fruticulosa species range. Results of genomic and transcriptomic approaches confirm the physiological observations of completely distinct underlying mechanisms of adaptation to extreme salinity and reveal potential genetic targets of these two recently evolved salinity adaptations. We therefore provide a new model of within-species salinity adaptation and reveal cryptic variation in neighbouring plant populations in the mechanisms of adaptation to an important natural stressor highly relevant to agriculture. SignificanceIts usually expected that closely related populations of a given species should adapt to the same environmental stressor in the same way due to genetic or physiological constraints. However, this is not commonly tested due to practical constraints. Here we show that, even at the level of neighbouring populations, contrasting adaptive mechanisms control adaptive responses to extreme coastal salinity in a new plant model, Brassica fruticulosa, a close wild relative of many crops of worldwide importance. This indicates multiple options for engineering an agriculturally crucial adaptation: soil salinization. These results will be of great interest to not only those studying fundamental mechanisms of adaptation, but also resilience improvement in Brassica species.

evolutionary biology↗

bioRxiv2023

Barley cultivars shape the abundance, phenotype, genotype and gene expression of their associated microbiota by differential root exudate secretion

Plant associated microbes play vital roles in promoting plant growth and health, with plants secreting root exudates into the rhizosphere to attract beneficial microbes. Exudate composition defines the nature of microbial recruitment, with different plant species attracting distinct microbiota to enable optimal adaptation to the soil environment. To more closely examine the relationship between plant genotype and microbial recruitment, we analysed the rhizosphere microbiomes of landrace (Chevallier) and modern (NFC Tipple) barley cultivars. Distinct differences were observed between the plant-associated microbiomes of the two cultivars, with the plant-growth promoting rhizobacterial genus Pseudomonas substantially more abundant in the Tipple rhizosphere. Striking differences were also observed between the phenotypes of recruited Pseudomonas populations, alongside distinct genotypic clustering by cultivar. Cultivar-driven Pseudomonas selection was driven by root exudate composition, with the greater abundance of hexose sugars secreted from Tipple roots attracting microbes better adapted to growth on these metabolites, and vice versa. Cultivar-driven selection also operates at the molecular level, with both gene expression and the abundance of ecologically relevant loci differing between Tipple and Chevallier Pseudomonas isolates. Finally, cultivar-driven selection is important for plant health, with both cultivars showing a distinct preference for microbes selected by their genetic siblings in rhizosphere transplantation assays.

microbiology↗

bioRxiv2020

A low-cost pipeline for soil microbiome profiling

BackgroundCommon bottlenecks in environmental microbiome studies are the consumable and personnel costs necessary for genomic DNA extraction and sequencing library construction. This is harder for challenging environmental samples such as soil, which is rich in PCR inhibitors. To address this, we have established a low-cost genomic DNA extraction method for inhibitor rich samples alongside an Illumina-compatible 16S and ITS rRNA gene amplicon library preparation workflow that uses common laboratory equipment. We evaluated the performance of our genomic DNA extraction method against two leading commercial soil genomic DNA kits (MoBio PowerSoil(R) and MP Biomedicals FastDNA SPIN) and a recently published non-commercial extraction method by Zou et al. (2017). Our benchmarking experiment used four different soil types (coniferous, broad leafed, and mixed forest plus a standardised cereal crop compost mix) assessing the quality and quantity of the extracted genomic DNA by analysing sequence variants of 16S V4 and ITS rRNA amplicons. ResultsWe found that our genomic DNA extraction method compares well to both commercially available genomic DNA extraction kits in DNA quality and quantity. The MoBio PowerSoil(R) kit, which relies on silica column-based DNA extraction with extensive washing delivered the cleanest genomic DNA e.g. best A260:A280 and A260:A230 absorbance ratios. The MP Biomedicals FastDNA SPIN kit, which uses a large amount of binding material, yielded the most genomic DNA. Our method fits between the two commercial kits, producing both good yields and clean genomic DNA with fragment sizes of approximately 10 kb. Comparative analysis of detected amplicon sequence variants shows that our method correlates well with the two commercial kits. ConclusionHere we present a low-cost genomic DNA extraction method for inhibitor rich sample types such as soil that can be coupled to an Illumina-compatible simple two step amplicon library construction workflow for 16S V4 and ITS marker genes. Our method delivers high quality genomic DNA at a fraction of the cost of commercial kits and enables cost-effective, large scale amplicon sequencing projects. Notably our extracted gDNA molecules are long enough to be suitable for downstream techniques such as full gene sequencing or even metagenomics shotgun approaches using long reads (PacBio or Nanopore), 10x Genomics linked reads, Dovetail genomics etc.

genomics↗