Biology subjects

Hope, M.

Publications and source records attributed to Hope, M..

3 recordsLinked to original sources

bioRxiv2025

Spatiotemporal regulation of arbuscular mycorrhizal symbiosis at cellular resolution

Arbuscular mycorrhizal (AM) symbiosis develops through successive colonization of root epidermal and cortical cells, culminating in the formation of arbuscules, tree-like intracellular structures that are transient yet essential sites of nutrient exchange. To dissect the cellular and structural complexity of AM establishment in rice roots colonized by Rhizophagus irregularis, we applied dual-species spatial transcriptomics to simultaneously monitor plant and fungal gene transcripts at single-cell resolution. This approach revealed surprising differences in transcriptional activity between fungal structures and showed that morphologically similar arbuscules can be transcriptionally distinct. These findings suggest hidden functional diversity among arbuscules at single-cell resolution. Because arbuscules form and degenerate within only a few days, we further sought to capture translational activities across their life span. We pioneered AM-inducible TRAP-seq (Translating Ribosome Affinity Purification followed by RNA-seq) using stage-specific promoters, enabling cell-type- and stage-resolved profiling in AM symbiosis. This revealed extensive spatiotemporal reprogramming of nutrient transport and signalling, with distinct sets of phosphate, nitrogen, and carbon transporters and regulators induced or repressed at different stages of arbuscule development, suggesting that nutrient exchange is dynamically regulated across the arbuscule life cycle. More broadly, cell wall biosynthesis genes and key defence markers were suppressed during arbuscule formation, whereas at a later stage, defence markers were strongly upregulated, suggesting a host-driven shift towards arbuscule termination. Together, these findings highlight the nuanced and dynamic regulation of AM symbiosis at the cellular level, refining our understanding of how nutrient exchange and fungal development are coordinated in space and time.

plant biology↗

bioRxiv2025

Molecular mimicry of plant cell-surface immune receptors by fungal secreted leucine-rich repeat proteins

O_LILeucine-rich repeat (LRR) receptor-like kinases (LRR-RLKs) are important plant immunity proteins. The wheat pathogen Zymoseptoria tritici produces many virulence effectors during infection; however, most remain uncharacterised. We identified a secreted protein from Z. tritici (ZtLRR) that consists of a single LRR domain and hypothesised that it mimics host LRR-RLKs to suppress plant immunity. C_LIO_LIWe used transient expression to probe ZtLRR function related to production of reactive oxygen species (ROS) and cell death, two important immune processes. We used AlphaFold structural predictions with targeted yeast two-hybrid to demonstrate protein-protein interactions. Transgenic wheat allowed assessment of effector function in the natural host. C_LIO_LIZtLRR suppressed ROS production and cell death in N. benthamiana with high potency. Structural predictions suggested high similarity to several plant LRR-RLKs and interaction with TaBAK1 was confirmed by targeted yeast two-hybrid. Transgenic wheat expressing ZtLRR was impaired in PAMP-triggered immunity (PTI) and had increased susceptibility to infection with compatible Z. tritici. We identified structural orthologs of ZtLRR in diverse fungal lineages and demonstrated that several of these proteins have similar immune-suppressing properties as ZtLRR. C_LIO_LIOur work demonstrates that molecular mimicry of host LRR-RLKs by phytopathogen sLRR effectors is effective at disrupting host immune pathways. C_LI

molecular biology↗

bioRxiv2020

RiboDiPA: A novel tool for differential pattern analysis in Ribo-seq data

AO_SCPLOWBSTRACTC_SCPLOWRibosome profiling (also known as Ribo-seq) has become an important technique to investigate changes in translation across a wide variety of contexts. Ribo-seq data not only provides the abundance of ribosomes bound to transcripts, but also positional information across transcripts that could be indicative of differences in translation dynamics between conditions. While many computational tools exist for the analysis of Ribo-seq data, including those that assess differences in translational efficiency between conditions, no tool currently exists for rigorous test of the pattern differences in ribosome footprint. In this paper we propose a novel approach together with an R package, RiboDiPA, for Differential PPattern Analysis of Ribo-seq data. RiboDiPA allows for quick identification of genes with statistically significant differences in ribosome occupancy patterns for model organisms ranging from yeast to mammals. We show that differential pattern analysis reveals information that is distinct and complimentary to the existing methods that focus on translational efficiency analysis. Using both simulated Ribo-seq footprint data and two benchmark data sets, we illustrate that RiboDiPA can not only uncover meaningful global translational differences between conditions, but also the detailed differential ribosome binding patterns to a single codon resolution.

bioinformatics↗