Dominika Siegieda

1. Data- and code-archiving are important components of open science, as both make research more transparent, reproducible, accountable, and credible, allowing future researchers to identify errors and build on previous work. Despite progress in implementing data- and code-archiving policies in journals publishing ecology and evolution research, issues remain. To be more useful to future researchers, archived data and code must not only be archived, but also meet good practice standards. 2. We collected data from 1,861 papers published between 2017 and 2024 in the seven British Ecological Society (BES) journals, during a hackathon event. We systematically checked associated data and/or code, metadata, help files and annotations to assess archiving practices. We determined if and where data and code files were archived, whether they could be located, downloaded, and opened, and whether they had associated READMEs, digital object identifiers (DOI) and licenses. We also recorded the file extensions used to save data/code files, and which programming languages code was written in. 3. 93% of the 1,861 papers we examined used data and ~90% used code. While 97% of the 1,735 papers that used data also archived it, only 35% of the 1,670 papers that used code also archived code. Over 85% of archived data and code could be located, downloaded, and opened. Reusability, however, was more limited; around a third of papers did not have a README or similar to explain their data/code files, and the quality of READMEs varied substantially. 4. We recommend that researchers archive their code, and that archived code be explicitly mentioned in the Data (or Code) Availability statement. We also encourage researchers to provide more accessible and informative READMEs for data and code. To help achieve these recommendations, we advocate that journals employ Data/Code editors to review data and code quality, research institutions deliver more training in open science practices, and funding bodies set clear expectations on open data and code practices.

While global warming accelerates phytopathogen spread, still little is known on how fungal pathogens disrupt fragile balance in plant-microbe interactions. Here, we demonstrate that the thermotolerant fungus Pilidium lythri combines broad chemical resistance with a remarkable ability to destabilize microbial communities in strawberry soil-plant systems. Using high-throughput sequencing (16S rRNA and ITS markers) across 72 samples, combined with mixed-effects modelling, source-tracking, microbiota assembly mechanisms investigation and network analysis we demonstrate that P. lythri disrupted bacterial community assembly processes, transitioning from deterministic to stochastic dynamics in the bulk soil, aligning with the Anna Karenina Principle. Despite stable dominance index (ENS) under infection bacterial and fungal communities, rhizosphere fungal diversity increased under infection. Network analysis of this niche revealed decreased fungal connectivity, with enhanced antagonistic interactions between taxa. We also noted that microbial migration patterns between niches under pathogen inoculation highlighted shifts in community interactions. Our work uncovers how emerging thermotolerant fungal phytopathogens destabilize plant holobiont without reducing diversity, important for managing emerging agricultural threats in a warming climate.

The bacterial microbiome plays crucial role in plants’ resistance to diseases, nutrient uptake and productivity. We examined the microbiome characteristics of healthy and unhealthy strawberry farms, focusing on soil (bulk soil, rhizosphere soil) and plant (roots and shoots). The relative abundance of most abundant taxa were correlated with the chemical soil properties and shoot niche revealed the least amount of significant correlations between the two. While alpha and beta diversities did not show differences between health groups, we identified a number of core taxa (16–59) and marker bacterial taxa for each healthy (Unclassified Tepidisphaerales, Ohtaekwangia, Hydrocarboniphaga) and dysbiotic (Udaeobacter, Solibacter, Unclassified Chitinophagales, Unclassified Nitrosomonadaceae, Nitrospira, Nocardioides, Tardiphaga, Skermanella, Pseudomonas, Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium, Curtobacterium) niche. We also revealed selective pressure of strawberry rhizosphere soil and roots plants in unhealthy plantations increased stochastic ecological processes of bacterial microbiome assembly in shoots. Our findings contribute to understanding sustainable agriculture and plant-microbiome interactions.

Phytopathogenic microorganisms belonging to the genus Phytophthora have been recognized many times as causal agents of diseases that lower the yield of many plants important for agriculture. Meanwhile, Phytophthora cactorum causes crown rot and leather rot of berry fruits, mainly strawberries. However, widely-applied culture-based methods used for the detection of pathogens are time-consuming and often inaccurate. What is more, molecular techniques require costly equipment. Here we show a rapid and effective detection method for the aforementioned targets, deploying a simple molecular biology technique, Loop-Mediated Isothermal Amplification (LAMP). We optimized assays to amplify the translation elongation factor 1-α (EF1a) gene for two targets: Phytophthora sp. And Phytophthora cactorum. We optimized the LAMP on pure strains of the pathogens, isolated from organic plantations of strawberry, and successfully validated the assay on biological material from the environment including soil samples, rhizosphere, shoots and roots of strawberry, and with SYBR Green. Our results demonstrate that a simple and reliable molecular detection method, that requires only a thermoblock and simple DNA isolation kit, can be successfully applied to detect pathogens that are difficult to separate from the field. We anticipate our findings to be a starting point for developing easier and faster modifications of the isothermal detection methods and which can be applied directly in the plantation, in particular with the use of freeze-dried reagents and chemistry, allowing observation of the results with the naked eye.

Phytopathogens cause undeniably serious damage in agriculture by harming fruit cultivations and lowering harvest yields, which as a consequence substantially reduces food production efficiency. Fungi of the Botrytis, Colletotrichum and Verticillium genera are a main concern in berry production. However, no rapid detection method for detecting all of these pathogens simultaneously has been developed to date. Therefore, in this study, a multiplex real-time PCR assay for this purpose was established. Universal fungal primers for the D2 region of the large subunit ribosomal DNA and three multiplexable fluorogenic probes specific for the chosen fungi were designed and deployed. The triplex approach for the molecular detection of these fungi, which was developed in this study, allows for the rapid and effective detection of crucial berry pathogens, which contributes to a more rapid implementation of protective measures in plantations and a significant reduction in losses caused by fungal diseases.

Increasing consumer awareness of potentially harmful pesticides used in conventional agriculture has prompted organic farming to become notably more prevalent in recent decades. Central European countries are some of the most important producers of blueberries, raspberries and strawberries in the world and organic cultivation methods for these fruits have a significant market share. Fungal pathogens are considered to be the most significant threat to organic crops of berries, causing serious economic losses and reducing yields. In order to ameliorate the harmful effects of pathogenic fungi on cultivations, the application of rapid and effective identification methods is essential. At present, various molecular methods are applied for fungal species recognition, such as PCR, qPCR, LAMP and NGS.