Genomic biosurveillance detects a sexual hybrid in the sudden oak death pathogen.

Invasive exotic pathogens pose a threat to trees and forest ecosystems worldwide, hampering the provision of essential ecosystem services such as carbon sequestration and water purification. Hybridization is a major evolutionary force that can drive the emergence of pathogens. Phytophthora ramorum, an emergent pathogen that causes the sudden oak and larch death, spreads as reproductively isolated divergent clonal lineages. We use a genomic biosurveillance approach by sequencing genomes of P. ramorum from survey and inspection samples and report the discovery of variants of P. ramorum that are the result of hybridization via sexual recombination between North American and European lineages. We show that these hybrids are viable, can infect a host and produce spores for long-term survival and propagation. Genome sequencing revealed genotypic combinations at 54,515 single nucleotide polymorphism loci not present in parental lineages. More than 6,000 of those genotypes are predicted to have a functional impact in genes associated with host infection, including effectors, carbohydrate-active enzymes and proteases. We also observed post-meiotic mitotic recombination that could generate additional genotypic and phenotypic variation and contribute to homoploid hybrid speciation. Our study highlights the importance of plant pathogen biosurveillance to detect variants, including hybrids, and inform management and control.

Supervised learning on phylogenetically distributed data.

MOTIVATION: The ability to develop robust machine-learning (ML) models is considered imperative to the adoption of ML techniques in biology and medicine fields. This challenge is particularly acute when data available for training is not independent and identically distributed (iid), in which case trained models are vulnerable to out-of-distribution generalization problems. Of particular interest are problems where data correspond to observations made on phylogenetically related samples (e.g. antibiotic resistance data). RESULTS: We introduce DendroNet, a new approach to train neural networks in the context of evolutionary data. DendroNet explicitly accounts for the relatedness of the training/testing data, while allowing the model to evolve along the branches of the phylogenetic tree, hence accommodating potential changes in the rules that relate genotypes to phenotypes. Using simulated data, we demonstrate that DendroNet produces models that can be significantly better than non-phylogenetically aware approaches. DendroNet also outperforms other approaches at two biological tasks of significant practical importance: antiobiotic resistance prediction in bacteria and trophic level prediction in fungi. AVAILABILITY AND IMPLEMENTATION: https://github.com/BlanchetteLab/DendroNet.

CRISPR/Cas9 Gene Editing: An Unexplored Frontier for Forest Pathology.

CRISPR/Cas9 gene editing technology has taken the scientific community by storm since its development in 2012. First discovered in 1987, CRISPR/Cas systems act as an adaptive immune response in archaea and bacteria that defends against invading bacteriophages and plasmids. CRISPR/Cas9 gene editing technology modifies this immune response to function in eukaryotic cells as a highly specific, RNA-guided complex that can edit almost any genetic target. This technology has applications in all biological fields, including plant pathology. However, examples of its use in forest pathology are essentially nonexistent. The aim of this review is to give researchers a deeper understanding of the native CRISPR/Cas systems and how they were adapted into the CRISPR/Cas9 technology used today in plant pathology-this information is crucial for researchers aiming to use this technology in the pathosystems they study. We review the current applications of CRISPR/Cas9 in plant pathology and propose future directions for research in forest pathosystems where this technology is currently underutilized.

Fiber-optic endoscopic evaluation of swallowing (FEES): predictor of swallowing-related complications in the head and neck cancer population.

BACKGROUND: The treatment of head and neck cancer is associated with significant dysphagia and morbidity. Prescribing a safe oral diet in this population is challenging. METHODS: Data from 116 consecutive patients having 189 fiber-optic endoscopic evaluation of swallowing (FEES) examinations over a 3-year period were analyzed. All patients had been treated for head and neck cancer and subsequently were assessed by FEES. The primary outcome was the incidence of swallowing-related adverse events resulting from the FEES-based dietary recommendations. RESULTS: There were 10 episodes of aspiration pneumonia, 4 episodes of airway obstruction, 3 unanticipated insertions of gastrostomy tubes, and 2 unexplained deaths within the study period. The overall rate of adverse events was 10.1%. The only statistically significant predictor of adverse events was the Rosenbek score (p = .03). CONCLUSIONS: Our experience is that FEES guides appropriate and safe diet recommendations in this population.