Plant-microbe eco-evolutionary dynamics in a changing world.

Both plants and their associated microbiomes can respond strongly to anthropogenic environmental changes. These responses can be both ecological (e.g. a global change affecting plant demography or microbial community composition) and evolutionary (e.g. a global change altering natural selection on plant or microbial populations). As a result, global changes can catalyse eco-evolutionary feedbacks. Here, we take a plant-focused perspective to discuss how microbes mediate plant ecological responses to global change and how these ecological effects can influence plant evolutionary response to global change. We argue that the strong and functionally important relationships between plants and their associated microbes are particularly likely to result in eco-evolutionary feedbacks when perturbed by global changes and discuss how improved understanding of plant-microbe eco-evolutionary dynamics could inform conservation or even agriculture.

DiSCount: computer vision for automated quantification of Striga seed germination.

BACKGROUND: Plant parasitic weeds belonging to the genus Striga are a major threat for food production in Sub-Saharan Africa and Southeast Asia. The parasite's life cycle starts with the induction of seed germination by host plant-derived signals, followed by parasite attachment, infection, outgrowth, flowering, reproduction, seed set and dispersal. Given the small seed size of the parasite (< 200 µm), quantification of the impact of new control measures that interfere with seed germination relies on manual, labour-intensive counting of seed batches under the microscope. Hence, there is a need for high-throughput assays that allow for large-scale screening of compounds or microorganisms that adversely affect Striga seed germination. RESULTS: Here, we introduce DiSCount (Digital Striga Counter): a computer vision tool for automated quantification of total and germinated Striga seed numbers in standard glass fibre filter assays. We developed the software using a machine learning approach trained with a dataset of 98 manually annotated images. Then, we validated and tested the model against a total dataset of 188 manually counted images. The results showed that DiSCount has an average error of 3.38 percentage points per image compared to the manually counted dataset. Most importantly, DiSCount achieves a 100 to 3000-fold speed increase in image analysis when compared to manual analysis, with an inference time of approximately 3 s per image on a single CPU and 0.1 s on a GPU. CONCLUSIONS: DiSCount is accurate and efficient in quantifying total and germinated Striga seeds in a standardized germination assay. This automated computer vision tool enables for high-throughput, large-scale screening of chemical compound libraries and biological control agents of this devastating parasitic weed. The complete software and manual are hosted at https://gitlab.com/lodewijk-track32/discount_paper and the archived version is available at Zenodo with the DOI 10.5281/zenodo.3627138. The dataset used for testing is available at Zenodo with the DOI 10.5281/zenodo.3403956.

Harnessing the microbiome to control plant parasitic weeds.

Microbiomes can significantly expand the genomic potential of plants, contributing to nutrient acquisition, plant growth promotion and tolerance to (a)biotic stresses. Among biotic stressors, root parasitic weeds (RPWs), mainly of the genera Orobanche, Phelipanche and Striga, are major yield-limiting factors of a wide range of staple crops, particularly in developing countries. Here, we provide a conceptual synthesis of putative mechanisms by which soil and plant microbiomes could be harnessed to control RPWs. These mechanisms are partitioned in direct and indirect modes of action and discussed in the context of past and present studies on microbe-mediated suppression of RPWs. Specific emphasis is given to the large but yet unexplored potential of root-associated microorganisms to interfere with the chemical signalling cascade between the host plant and the RPWs. We further provide concepts and ideas for future research directions and prospective designs of novel control strategies.