Biology subjects

Crampton, B.

Publications and source records attributed to Crampton, B..

5 recordsLinked to original sources

bioRxiv2026

Metabarcode and transcriptome datasets of Pinus sylvestris to assess fungal phyllosphere and disease dynamics.

Understanding how host-microbiome interactions influence tree disease is critical for understanding forest resilience. Here, we present foliar microbiome ITS2 metabarcoding transcriptomic datasets from Pinus sylvestris to investigate susceptibility to Dothistroma needle blight (DNB), a globally important foliar disease caused by Dothistroma septosporum. We hypothesised that host genotype shapes foliar microbial communities and their interactions, thereby influencing disease outcomes. Samples were collected from a progeny-provenance field trial in the south of Scotland representing a broad spectrum of disease susceptibilities. The dataset comprises ITS2 metabarcoding samples from 200 genotypes across three timepoints and RNAseq samples from 48 genotypes across two timepoints. Sampling captured key stages of pathogen exposure and disease progression. Both standardised and bespoke protocols were used for nucleotide extraction, sequencing, and quality control, including multiple negative and positive controls. These datasets, available in the European Nucleotide Archive (project accession PRJEB88228), enable analysis of temporal dynamics in foliar fungal communities, host-microbiome transcriptional responses, and genotype-dependent variation in disease susceptibility.

bioinformatics↗

bioRxiv2026

A decade of disease survey data in a progeny-provenance trial: Dothistroma needle blight in Scots pine

Longitudinal data on disease susceptibility in forest trees are rare but essential for understanding host-pathogen dynamics and genetic variation in susceptibility traits. We present a long-term multisite common garden dataset quantifying susceptibility of Scots pine (Pinus sylvestris) to Dothistroma needle blight. The dataset comprises annual disease assessments collected from the same trees across 11 years, spanning 168 families and 21 Scottish provenances. This design enables partitioning of genetic and environmental sources of variation, evaluation of temporal stability in host response, and estimation of variance components and narrow-sense heritability of susceptibility. The data support analyses of phenotypic plasticity, provenance-level responses, and interactions between disease susceptibility and other adaptive traits. This resource will facilitate predictive modelling of host susceptibility under current and future environmental conditions.

ecology↗

bioRxiv2025

Functional diversification of the cephalopod proteome by RNA-editing

Coleoid cephalopods exhibit the highest levels of ADAR-mediated RNA editing of any known animal, yet the functional consequences of most recoding events remain largely unknown. We integrate proteomics with biochemical and cellular assays to characterize thousands of recoding events across the Doryteuthis pealeii proteome. Using quantitative and functional mass spectrometry, we show that RNA edit-driven recoding reshapes the cellular proteome to alter protein stability, subcellular localization, post-translational modifications, and enzymatic activity. --Recoding can regulate post-translational modifications through their creation or ablation, and this has direct effects on protein function and protein-protein interactions. Recoding of the E3 ligase MARCHF5 drives widespread changes in substrate ubiquitylation and perturbs mitochondrial homeostasis, illustrating how RNA editing can influence organelle function. These data provide the first proteome-scale view of how extensive RNA recoding diversifies protein function in coleoid cephalopods and offers a new framework for understanding how RNA-level plasticity shapes protein function and cellular physiology.

molecular biology↗

bioRxiv2025

Large-scale culturing of the tree microbiome enables targeted disease suppression

The tree microbiome is essential for host health and pathogen suppression. Synthetic microbial communities (SynComs) are emerging as important tools to understand microbiome dynamics and engineer microbiomes to harness beneficial properties. However, while the rational design, assembly and application of SynComs requires representative microbiota isolate collections combined with functional information, microbial culture collections from tree species such as oak (Quercus) are critically lacking. Here, we generated an oak microbiota culture collection comprising >30,000 isolates from 150 oak trees across Britain, belonging to key bacterial and fungal taxa that represented 61% of the total bacterial sequences and 87% of total fungal sequences as determined by culture-independent sequencing. Over 22,000 isolates were screened for suppression of bacterial species associated with degradation of live stem tissue in trees affected by Acute Oak Decline (AOD), identifying 341 bacterial isolates that suppressed oak pathogens. In vitro screening of 40 randomly assembled SynComs demonstrated that oak microbiota SynComs can suppress oak pathogenic bacteria associated with AOD. Inoculation of a disease-suppressive SynCom into the stem of oak seedlings and logs prior to pathogen challenge reduced the quantities of the bacteria, Brenneria goodwinii and Gibbsiella quercinecans, by 56% and 87%, respectively, in seedlings, and 71% and 95% in logs. This work demonstrates that the tree microbiome can be engineered using disease suppressive SynComs.

microbiology↗

bioRxiv2024

Tesorai Search: Large pretrained model boosts identifications in mass spectrometry proteomics without the need for Percolator.

The original mass spectrometry search engines used simple algorithms for peptide identification. Recent tools improved accuracy by adding several extra components such as fragment ion intensities or retention times prediction and training target-decoy classifiers on-the-fly, leading to sometimes inconsistent results. Our study explores the impact of replacing those extra components with a deep-learning pretrained model that directly learns the complex relationship between the full spectra and associated peptide sequence, without using decoys. This simplified workflow has fewer parameters to tweak, making it easier to use and perform robustly on data from instruments and use-cases never seen during training. Surprisingly, our approach consistently identifies more peptides than FragPipe, PEAKS, and Proteome Discoverer (12%, 9%, and 21% more, respectively, across a range of datasets). Tesorai Search is also fast - 250 immunopeptidomics searches in 45 minutes - and free for academics, available as a webserver at console.tesorai.com.

bioinformatics↗