A dynamical systems model for poly-cyclic foliar forest pathogens

A simple systems model is proposed to understand and quantify the onset and epidemiology of red needle cast in radiata pine. This disease is impacting much of the New Zealand forestry estate being driven through the production of self-replicating spores which are dispersed with water. The model is at present deterministic, not spatially or age-structured, nor dependent on environmental or seasonal effects. This model shows the clear existence of calculable thresholds for disease proliferation and elimination, showing it has captured the essential components of the biological mechanisms. It is to be used to identify thresholds for infection to spread or retract. Further it will provide a base model from which we can fit and then predict experimental outcomes. References C Lee Campbell, Laurence V Madden, et al. Introduction to plant disease epidemiology. John Wiley and Sons., 1990. Margaret Anne Dick, Nari Michelle Williams, Martin Karl-Friedrich Bader, Judy Frances Gardner, and Lindsay Stuart Bulman. Pathogenicity of phytophthora pluvialis to pinus radiata and its relation with red needle cast disease in new zealand. New Zealand Journal of Forestry Science, 44(1):6, 2014. Heidi S Dungey, Nari M Williams, Charlie B Low, and Graham T Stovold. First evidence of genetic-based tolerance to red needle cast caused by phytophthora pluvialis in radiata pine. New Zealand Journal of Forestry Science, 44(1):31, 2014. RJ Ganley, NM Williams, CA Rolando, IA Hood, HS Dungey, PN Beets, LS Bulman, et al. Management of red needle cast, caused by phytophthora pluvialis, a new disease of radiata pine in new zealand. N. Z. Plant Protect.-SE, 67:48–53, 2014. Wake GC. Private communication, 2017. Christopher A Gilligan. An epidemiological framework for disease management. Advances in botanical research, 38:1–64, 2002. MJ Jeger. Asymptotic behaviour and threshold criteria in model plant disease epidemics. Plant Pathology, 35(3):355–361, 1986. Nurul S Abdul Latif, Graeme C Wake, Tony Reglinski, and Philip AG Elmer. Modelling induced resistance to plant diseases. Journal of theoretical biology, 347:144–150, 2014. Nurul S Abdul Latif, Graeme C Wake, Tony Reglinski, Philip AG Elmer, and Joseph T Taylor. Modeling induced resistance to plant disease using a dynamical systems approach. Frontiers in plant science, 4, 2013. Laurence V Madden, Gareth Hughes, Frank Bosch, et al. The study of plant disease epidemics. American Phytopathological Society (APS Press), 2007. CA Rolando, MA Dick, J Gardner, M Bader, NM Williams, et al. Chemical control of two phytophthora species infecting the canopy of monterey pine (pinus radiata). Forest Pathology, 47(3), 2017. Carol Rolando, Robyn Gaskin, David Horgan, Nari Williams, and Martin KF Bader. The use of adjuvants to improve uptake of phosphorous acid applied to pinus radiata needles for control of foliar phytophthora diseases. New Zealand Journal of Forestry Science, 44(1):8, 2014

Evolutionary trait-based approaches for predicting future global impacts of plant pathogens in the genus Phytophthora

1. Plant pathogens are introduced to new geographical regions ever more frequently as global connectivity increases. Predicting the threat they pose to plant health can be difficult without in‐depth knowledge of behaviour, distribution and spread. Here, we evaluate the potential for using biological traits and phylogeny to predict global threats from emerging pathogens. 2. We use a species‐level trait database and phylogeny for 179 Phytophthora species: oomycete pathogens impacting natural, agricultural, horticultural and forestry settings. We compile host and distribution reports for Phytophthora species across 178 countries and evaluate the power of traits, phylogeny and time since description (reflecting species‐level knowledge) to explain and predict their international transport, maximum latitude and host breadth using Bayesian phylogenetic generalised linear mixed models. 3. In the best‐performing models, traits, phylogeny and time since description together explained up to 90%, 97% and 87% of variance in number of countries reached, latitudinal limits and host range, respectively. Traits and phylogeny together explained up to 26%, 41% and 34% of variance in the number of countries reached, maximum latitude and host plant families affected, respectively, but time since description had the strongest effect. 4. Root‐attacking species were reported in more countries, and on more host plant families than foliar‐attacking species. Host generalist pathogens had thicker‐walled resting structures (stress‐tolerant oospores) and faster growth rates at their optima. Cold‐tolerant species are reported in more countries and at higher latitudes, though more accurate interspecific empirical data are needed to confirm this finding. 5. Policy implications. We evaluate the potential of an evolutionary trait‐based framework to support horizon‐scanning approaches for identifying pathogens with greater potential for global‐scale impacts. Potential future threats from Phytophthora include Phytophthora x heterohybrida, P. lactucae, P. glovera, P. x incrassata, P. amnicola and P. aquimorbida, which are recently described, possibly under‐reported species, with similar traits and/or phylogenetic proximity to other high‐impact species. Priority traits to measure for emerging species may be thermal minima, oospore wall index and growth rate at optimum temperature. Trait‐based horizon‐scanning approaches would benefit from the development of international and cross‐sectoral collaborations to deliver centralised databases incorporating pathogen distributions, traits and phylogeny

Functional analysis of RXLR effectors from the New Zealand kauri dieback pathogen Phytophthora agathidicida

New Zealand kauri is an ancient, iconic, gymnosperm tree species that is under threat from a lethal dieback disease caused by the oomycete Phytophthora agathidicida. To gain insight into this pathogen, we determined whether proteinaceous effectors of P. agathidicida interact with the immune system of a model angiosperm, Nicotiana, as previously shown for Phytophthora pathogens of angiosperms. From the P. agathidicida genome, we defined and analysed a set of RXLR effectors, a class of proteins that typically have important roles in suppressing or activating the plant immune system. RXLRs were screened for their ability to activate or suppress the Nicotiana plant immune system using Agrobacterium tumefaciens transient transformation assays. Nine P. agathidicida RXLRs triggered cell death or suppressed plant immunity in Nicotiana, of which three were expressed in kauri. For the most highly expressed, P. agathidicida (Pa) RXLR24, candidate cognate immune receptors associated with cell death were identified in Nicotiana benthamiana using RNA silencing-based approaches. Our results show that RXLRs of a pathogen of gymnosperms can interact with the immune system of an angiosperm species. This study provides an important foundation for studying the molecular basis of plant–pathogen interactions in gymnosperm forest trees, including kauri

Comparative Genomic Analysis of 31 Phytophthora Genomes Reveals Genome Plasticity and Horizontal Gene Transfer

Phytophthora species are oomycete plant pathogens that cause great economic and ecological impacts. The Phytophthora genus includes over 180 known species, infecting a wide range of plant hosts, including crops, trees, and ornamentals. We sequenced the genomes of 31 individual Phytophthora species and 24 individual transcriptomes to study genetic relationships across the genus. De novo genome assemblies revealed variation in genome sizes, numbers of predicted genes, and in repetitive element content across the Phytophthora genus. A genus-wide comparison evaluated orthologous groups of genes. Predicted effector gene counts varied across Phytophthora species by effector family, genome size, and plant host range. Predicted numbers of apoplastic effectors increased as the host range of Phytophthora species increased. Predicted numbers of cytoplasmic effectors also increased with host range but leveled off or decreased in Phytophthora species that have enormous host ranges. With extensive sequencing across the Phytophthora genus, we now have the genomic resources to evaluate horizontal gene transfer events across the oomycetes. Using a machine-learning approach to identify horizontally transferred genes with bacterial or fungal origin, we identified 44 candidates over 36 Phytophthora species genomes. Phylogenetic reconstruction indicates that the transfers of most of these 44 candidates happened in parallel to major advances in the evolution of the oomycetes and Phytophthora spp. We conclude that the 31 genomes presented here are essential for investigating genus-wide genomic associations in genus Phytophthora. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license

Comparative genomic analysis of 31 Phytophthora genomes reveal genome plasticity and horizontal gene transfer

Phytophthora species are oomycete plant pathogens that cause great economic and ecological impacts. The Phytophthora genus includes over 180 known species, infecting a wide range of plant hosts including crops, trees, and ornamentals. We sequenced 31 individual Phytophthora species genomes and 24 individual transcriptomes to study genetic relationships across the genus. De novo genome assemblies revealed variation in genome sizes, numbers of predicted genes, and in repetitive element content across the Phytophthora genus. A genus-wide comparison evaluated orthologous groups of genes. Predicted effector gene counts varied across Phytophthora species by effector family, genome size, as well as plant host range. Predicted numbers of apoplastic effectors increased as the host range of Phytophthora species increased. Predicted numbers of cytoplasmic effectors also increased with host range but leveled off or decreased in Phytophthora species that have enormous host ranges. With extensive sequencing across the Phytophthora genus we now have the genomic resources to evaluate horizontal gene transfer events across the oomycetes. Using a machine learning approach to identify horizontally transferred genes with bacterial or fungal origin we identified 44 candidates over 36 Phytophthora species genomes. Phylogenetic reconstruction indicates that the transfers of most of these 44 candidates happened in parallel to major advances in the evolution of the oomycetes and Phytophthoras. We conclude that the 31 genomes presented here are essential for investigating genus-wide genomic associations in Phytophthora

Effects of fluoxetine on functional outcomes after acute stroke (FOCUS): a pragmatic, double-blind, randomised, controlled trial

Background Results of small trials indicate that fluoxetine might improve functional outcomes after stroke. The FOCUS trial aimed to provide a precise estimate of these effects. Methods FOCUS was a pragmatic, multicentre, parallel group, double-blind, randomised, placebo-controlled trial done at 103 hospitals in the UK. Patients were eligible if they were aged 18 years or older, had a clinical stroke diagnosis, were enrolled and randomly assigned between 2 days and 15 days after onset, and had focal neurological deficits. Patients were randomly allocated fluoxetine 20 mg or matching placebo orally once daily for 6 months via a web-based system by use of a minimisation algorithm. The primary outcome was functional status, measured with the modified Rankin Scale (mRS), at 6 months. Patients, carers, health-care staff, and the trial team were masked to treatment allocation. Functional status was assessed at 6 months and 12 months after randomisation. Patients were analysed according to their treatment allocation. This trial is registered with the ISRCTN registry, number ISRCTN83290762. Findings Between Sept 10, 2012, and March 31, 2017, 3127 patients were recruited. 1564 patients were allocated fluoxetine and 1563 allocated placebo. mRS data at 6 months were available for 1553 (99·3%) patients in each treatment group. The distribution across mRS categories at 6 months was similar in the fluoxetine and placebo groups (common odds ratio adjusted for minimisation variables 0·951 [95% CI 0·839–1·079]; p=0·439). Patients allocated fluoxetine were less likely than those allocated placebo to develop new depression by 6 months (210 [13·43%] patients vs 269 [17·21%]; difference 3·78% [95% CI 1·26–6·30]; p=0·0033), but they had more bone fractures (45 [2·88%] vs 23 [1·47%]; difference 1·41% [95% CI 0·38–2·43]; p=0·0070). There were no significant differences in any other event at 6 or 12 months. Interpretation Fluoxetine 20 mg given daily for 6 months after acute stroke does not seem to improve functional outcomes. Although the treatment reduced the occurrence of depression, it increased the frequency of bone fractures. These results do not support the routine use of fluoxetine either for the prevention of post-stroke depression or to promote recovery of function. Funding UK Stroke Association and NIHR Health Technology Assessment Programme

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

No carbon limitation after lower crown loss in Pinus radiata

Background and Aims Biotic and abiotic stressors can cause different defoliation patterns within trees. Foliar pathogens of conifers commonly prefer older needles and infection with defoliation that progresses from the bottom crown to the top. The functional role of the lower crown of trees is a key question to address the impact of defoliation caused by foliar pathogens.Methods A 2 year artificial defoliation experiment was performed using two genotypes of grafted Pinus radiata to investigate the effects of lower-crown defoliation on carbon (C) assimilation and allocation. Grafts received one of the following treatments in consecutive years: control-control, control-defoliated, defoliated-control and defoliated-defoliated.Results No upregulation of photosynthesis either biochemically or through stomatal control was observed in response to defoliation. The root:shoot ratio and leaf mass were not affected by any treatment, suggesting prioritization of crown regrowth following defoliation. In genotype B. defoliation appeared to impose C shortage and caused reduced above-ground growth and sugar storage in roots, while in genotype A, neither growth nor storage was altered. Root C storage in genotype B decreased only transiently and recovered over the second growing season. Conclusions In genotype A. the contribution of the lower crown to the whole-tree C uptake appears to be negligible, presumably conferring resilience to foliar pathogens affecting the lower crown. Our results suggest that there is no C limitation after lower-crown defoliation in P. radiata grafts. Further, our findings imply genotype-specific defoliation tolerance in P. radiata