Biology subjects

Schandry, N.

Publications and source records attributed to Schandry, N..

8 recordsLinked to original sources

bioRxiv2026

Plant associated bacteria are a rich reservoir for multidrug efflux pumps

Plants produce antibiotic substances and bacteria need to cope with those substances to colonize plants. We analyzed the inventory of genes encoding resistance-nodulation-cell division (RND) efflux pumps originating from 282 bacterial isolates from leaves or roots of the model plant Arabidopsis thaliana. We confirmed that, on average, plant associated bacteria hold a significantly increased repertoire of genes encoding RND antiporters homologs compared to strains isolated from other ecological niches, as reported in a previous study. While some RND antiporter clades were enriched in plant colonizers, other clades found in the genomes of isolates from other environments were underrepresented. An in-depth analysis of RND antiporters from plant colonizing bacteria revealed that conserved motifs can be found in each clade, possibly contributing to substrate specificity. Interestingly, we found horizontal gene transfer markers in 10% of the antiporter homologs, suggesting that horizontal gene transfer may significantly contribute to the adaptation of bacteria to the specific chemical environment created by different organs of plant hosts. In addition, homologs from leaf-isolated bacteria showed a lower diversification, and harbored markers of horizontal gene transfer in the heavy metal exporting clade. Sequence and structural analysis revealed a high diversity in RND-antiporters, with few residues under purifying selection, indicating that RND diversity is driven by random mutations. Our findings have major implications for the origin of multidrug resistances and for our understanding of the forces shaping the outcome of plant-microbe ecology in general.

microbiology↗

bioRxiv2025

Plant specialised metabolites modulate the molecular signatures of host-bacteria and bacteria-bacteria interactions

Plants participate in intricate interactions with a multitude of microorganisms, many of which also influence each other. This holobiont is situated in a chemical soil environment that is defined, in parts, by the specialised metabolite legacy of proximal and preceding organisms, including other plants. Here, we investigated the influence of external plant-derived specialised metabolites on the interactions among root-associated bacterial strains, and between these strains and a plant host. Using benzoxazinoids and their derivatives as a model in both simplified pairwise experiments and more complex multi-organism analyses, we show that these chemicals can modulate bacteria-bacteria, as well as bacteria-plant interactions. While the chemical environment alone had little effect on the plant at the molecular level, it differentially affected plant chemical defences, immunity, and sugar transport when combined with single-isolate or micro-community inoculums. Our study underlines the importance of the chemical environment in modulating organismic interactions and illustrates the value of combining reduced-complexity, bottom-up reconstruction approaches with top-down holobiont profiling. SIGNIFICANCEMany plant species secrete specialized metabolites into the soil, where they can have a long-lasting effect on subsequent plant generations and their associated microbiomes. Understanding the effect of this chemical environment on soil- and plant-associated microbiomes is crucial to determine the impact of soil legacy on host plants, for example in the context of crop rotations. Here, we report that the interactions among root-associated microbes are modulated by specialized metabolites of the benzoxazinoid family, which are prominent metabolites in many grasses. We further show that the chemical environment can inhibit the defence capacity of the plant towards colonizing bacteria, and that more complex bacterial communities are able to mitigate these effects. Our work highlights the importance of deconstructing bacterial communities and the chemical environment to gain insights into the fine-tuned molecular mechanisms that determine the outcome of complex organismic interactions.

plant biology↗

bioRxiv2025

A TNL receptor mediates microbiome feedbacks in Arabidopsis

Plant performance depends on the soil microbiome. While microbiome feedbacks are well documented, the mechanisms by which plants perceive and mediate these feedbacks remain unclear. We established a framework using two distinct microbiomes in the same soil, where one led to enhanced growth of the Arabidopsis thaliana accession Col-0. Screening 410 accessions revealed substantial variation in growth feedbacks, which we used for genome-wide association mapping. We identified the immune receptor Mediator of Microbiome Feedback 1 (MMF1) as a candidate gene involved in microbiota feedbacks. Characterisation in the reference accession Col-0 revealed that mmf1 mutants lost the beneficial growth feedback, had an altered root bacterial community, and failed to induce a defence-related transcriptional response observed in wild-type plants. The discovery of MMF1 implies that integration of microbial signals optimises host microbiome composition and immune status to enhance growth.

plant biology↗

bioRxiv2024

The 1001G+ project: A curated collection of Arabidopsis thaliana long-read genome assemblies to advance plant research

Arabidopsis thaliana was the first plant for which a high-quality genome sequence became available. The publication of the first reference genome sequence almost 25 years ago was already accompanied by genome-wide data on sequence polymorphisms in another accession, or naturally occurring strain. Since then, inventories of genome-wide diversity have been generated at increasingly precise levels. High-density genotype data for A. thaliana, including those from the 1001 Genomes Project, were key to demonstrating the enormous power of GWAS in inbred populations of wild plants, and the comparison of intraspecific polymorphism with interspecific divergence has illuminated many aspects of plant genome evolution. Over the past decade, an increasing number of nearly complete genome sequences have been published for many more accessions. Here, we highlight the diversity of a curated collection of previously published and so far unpublished genome sequences assembled using different types of long reads, including PacBio Continuous Long Reads (CLR), PacBio High Fidelity (HiFi) reads, and Oxford Nanopore Technologies (ONT) reads. This 1001 Genomes Plus (1001G+) resource is being made available at http://1001genomes.org. We invite colleagues with yet unpublished genome assemblies from A. thaliana accessions to contribute to this effort.

genomics↗

bioRxiv2023

The lactonase BxdA mediates metabolic adaptation of maize root bacteria to benzoxazinoids

Root exudates contain secondary metabolites that affect the plants root microbiome. How microbes cope with these bioactive compounds, and how this ability shapes root microbiomes remain largely unknown. We investigated how maize root bacteria metabolise benzoxazinoids, the main specialised metabolites of maize. Diverse and abundant bacteria metabolised the major compound (6-methoxy-benzoxazolin-2-one, MBOA) in the maize rhizosphere to 2-amino-7-methoxyphenoxazin-3-one (AMPO). By contrast, bacteria isolated from Arabidopsis, which does not produce benzoxazinoids, were unable to metabolise MBOA. Among Microbacteria strains, this differential metabolisation allowed to identify a conserved gene cluster containing the lactonase bxdA. BxdA converts MBOA to AMPO in vitro and we show that this capacity provided bacteria a growth benefit under carbon-limiting conditions. Together these results reveal that maize root bacteria - through BxdA - are metabolically adapted to the benzoxazinoids of their host. We propose that metabolic adaptation to plant-specialised compounds shapes root bacterial communities across the plant kingdom.

microbiology↗

bioRxiv2022

Transcriptional response of a target plant to benzoxazinoid and diterpene allelochemicals highlights commonalities in detoxification

Plants growing in proximity to other plants are exposed to a variety of metabolites that these neighbors release into the environment. Some species produce allelochemicals to inhibit growth of neighboring plants, which in turn have evolved ways to detoxify these compounds. In order to understand how the allelochemical-receiving target plants respond to chemically diverse compounds, we performed whole-genome transcriptome analysis of Arabidopsis thaliana exposed to either the benzoxazinoid derivative 2-amino-3H-phenoxazin-3-one (APO) or momilactone B. These two allelochemicals belong to two very different compound classes, benzoxazinoids and diterpenes, respectively, produced by different cereal crop species. Despite their distinct chemical nature, we observed similar molecular responses of A. thaliana to these allelochemicals. In particular, many of the same or closely related genes belonging to the three-phase detoxification pathway were upregulated in both treatments. Further, we observed an overlap between genes upregulated by allelochemicals and those involved in herbicide detoxification. Our findings highlight the overlap in the transcriptional response of a target plant to natural and synthetic phytotoxic compounds and illustrate how herbicide resistance could arise via pathways involved in plant-plant interaction.

plant biology↗

bioRxiv2021

Plant-derived benzoxazinoids act as antibiotics and shape bacterial communities

Plants synthesize and release specialized metabolites into their environment that can serve as chemical cues for other organisms. Metabolites that are released from the roots are important factors in determining which microorganisms will colonize the root and become part of the plant rhizosphere. Root exudates can be converted by soil microorganisms, which can result in the formation of toxic compounds. How individual members of the plant rhizosphere respond to individual compounds and how the differential response of individual microorganisms contributes to the response of a microbial community remains an open question. Here, we investigated the impact of derivatives of benzoxazinoids, a class of plant root exudates released by important crops such as wheat and maize, on a collection of 180 root-associated bacteria. Phenoxazine, derived in soil from benzoxazinoids, inhibited the growth of root-associated bacteria in vitro in an isolate-specific manner, with sensitive and resistant isolates present in most of the studied clades. Using synthetic communities, we show that community stability is a consequence of the resilience of its individual members, with communities assembled from tolerant isolates being overall more tolerant to benzoxazinoids. However, the performance of an isolate in a community context was not correlated with its individual performance but appeared to be shaped by interactions between isolates. These interactions were independent of the overall community composition and were strain-specific, with interactions between different representatives of the same bacterial genera accounting for differential community composition.

plant biology↗

bioRxiv2020

araDEEPopsis: From images to phenotypic traits using deep transfer learning

Linking plant phenotype to genotype, i.e., identifying genetic determinants of phenotypic traits, is a common goal of both plant breeders and geneticists. While the ever-growing genomic resources and rapid decrease of sequencing costs have led to enormous amounts of genomic data, collecting phenotypic data for large numbers of plants remains a bottleneck. Many phenotyping strategies rely on imaging plants, which makes it necessary to extract phenotypic measurements from these images rapidly and robustly. Common image segmentation tools for plant phenotyping mostly rely on color information, which is error-prone when either background or plant color deviate from the underlying expectations. We have developed a versatile, fully open-source pipeline to extract phenotypic measurements from plant images in an unsupervised manner. O_SCPLOWARAC_SCPLOWO_SCPLOWDEEPC_SCPLOWO_SCPLOWOPSISC_SCPLOW was built around the deep-learning model DeepLabV3+ that was re-trained for segmentation of Arabidopsis thaliana rosettes. It uses semantic segmentation to classify leaf tissue into up to three categories: healthy, anthocyanin-rich, and senescent. This makes O_SCPLOWARAC_SCPLOWO_SCPLOWDEEPC_SCPLOWO_SCPLOWOPSISC_SCPLOW particularly powerful at quantitative phenotyping from early to late developmental stages, of mutants with aberrant leaf color and/or phenotype, and of plants growing in stressful conditions where leaf color may deviate from green. Using our tool on a panel of 210 natural Arabidopsis accessions, we were able to not only accurately segment images of phenotypically diverse genotypes but also to map known loci related to anthocyanin production and early necrosis using the O_SCPLOWARAC_SCPLOWO_SCPLOWDEEPC_SCPLOWO_SCPLOWOPSISC_SCPLOW output in genome-wide association analyses. Our pipeline is able to handle images of diverse origins, image quality, and background composition, and could even accurately segment images of a distantly related Brassicaceae. Because it can be deployed on virtually any common operating system and is compatible with several high-performance computing environments, O_SCPLOWARAC_SCPLOWO_SCPLOWDEEPC_SCPLOWO_SCPLOWOPSISC_SCPLOW can be used independently of bioinformatics expertise and computing resources. O_SCPLOWARAC_SCPLOWO_SCPLOWDEEPC_SCPLOWO_SCPLOWOPSISC_SCPLOW is available at https://github.com/Gregor-Mendel-Institute/aradeepopsis.

plant biology↗