DOI: 10.5061/dryad.4mw6m90jv
title: High temperatures reduce growth, infection, and transmission of a naturally occurring fungal plant pathogen

description: Climate change is rapidly altering the distribution of suitable habitats
 for many species as well as their pathogenic microbes. For many pathogens,
 including vector-borne diseases of humans and agricultural pathogens,
 climate change is expected to increase transmission and lead to pathogen
 range expansions. However, if pathogens have a lower heat tolerance than
 their host, increased warming could generate ‘thermal refugia’ for hosts.
 Predicting the outcomes of warming on disease transmission requires
 detailed knowledge of the thermal tolerances of both the host and the
 pathogen. Such thermal tolerance studies are generally lacking for fungal
 pathogens of wild plant populations, despite the fact that plants form the
 base of all terrestrial communities. Here, we quantified three aspects of
 the thermal tolerance (growth, infection, and propagule production) of the
 naturally occurring fungal pathogen Microbotryum lychnidis-dioicae, which
 causes a sterilizing anther-smut disease on the herbaceous plant Silene
 latifolia. We also quantified two aspects of host thermal tolerance:
 seedling survival and flowering rate. We found that temperatures
 &gt;30 degreeC reduced the ability of anther-smut spores to germinate,
 grow, and conjugate in vitro. In addition, we found that high temperatures
 (30 degreeC) during, or shortly after the time of inoculation strongly
 reduced the likelihood of infection in seedlings. Finally, we found that
 high summer temperatures in the field temporarily cured infected plants,
 likely reducing transmission. Notably, high temperatures did not reduce
 survival or flowering of the host plants. Taken together, our results show
 that the fungus is considerably more sensitive to high temperatures than
 its host plant. A warming climate could therefore result in reduced
 disease spread or even local pathogen extirpation, leading to thermal
 refugia for the host.
description: Data was collected in three separate sets of
 expeirments: 1) In vitro assays of pathogen
 germination, growth, and conjugation in growth chambers set to different
 temperature 2) Greenhouse inoculaiton expeirment
 of <em>S. latifolia </em>seedlings at different temperature
 treatments 3) A field experiment, where diseased plants
 were monitored for signs of heat-curing over the course of one summer
 field season.
description: # High temperatures reduce growth, infection, and transmission of a
 naturally occurring fungal plant pathogen
 [https://doi.org/10.5061/dryad.4mw6m90jv](https://doi.org/10.5061/dryad.4mw6m90jv) A series of three experiments were carried out using the fungal pathogen *Microbotryum lychnidis-dioicae* and its host plant *Silene latifolia* in the manuscript: 1) in vitro assays of fungal germination, growth and conjugation under different temperatures in a growth chamber, 2) in planta assay of infection rate at different inoculation temperatures, and 3) disease expression of infected plants in the field from May to November.    ## Description of the data and file structure There are 12 separate data files associated with this manuscript and 7 r-files for analysis.  We have organized them according to the three experiments reported in the paper.  Data files are typically in csv text files.  In some cases they are stored as xls files with two sheets: One containing the data, and one a readme description of all column names. Analysis scripts are stored as R files. ## Sharing/Access information All of the data was generated by the authors of the paper and is only accessible here.  ## Code/Software We used R for all statistical analyses and figure generation.  There are 7 individual scripts used are described above for experiments 1-3.  Details on the packages used are in the R scripts. ## **Data files and R scripts for Experiment 1** **Brief description**: The lab experiment where three pathogen traits (germination, growth, and conjugation) were measured over a range of temperatures from 4-30 °C. **Data sets included:** ·      Germination data.xlsx ·      Growth data strain 2.xlsx ·      Growth data strain 3.xlsx ·      Growth data strain 4.xlsx ·      Conjugation Data strain 2.xlsx ·      Conjugation Data strain 3.xlsx ·      Conjugation Data strain 4.xlsx **Data analysis scripts** ·      Germination data code.R- Fig 1a and analysis for the germination assay ·      Growth data code.R- Fig 1b and analysis for the colony growth assay ·      Conjugation data code.R- Fig 1c and analysis for the conjugation assay **Details on data sets:** 1.     Germination data.xlsx Data set that provides the proportion of teliospores that germinated after 20 hours at each temperature. This data was used to generate Figure 1a. 2.     Growth data strain 2.xlsx, Growth data strain 3.xlsx, and Growth data strain 4.xlsx These data sets provide the number of visible colonies after one week at each temperature. Each data set contains the data for one pathogen strain (2, 3, or 4). This data was used to generate Figure 1b. 3.     Conjugation Data strain 2.xlsx, Conjugation Data strain 3.xlsx, and Conjugation Data strain 4.xlsx These data sets provide the proportion of conjugating sporidia after 20 hours at each temperature. Each data set contains the data for one pathogen strain (2, 3, or 4). This data was used to generate Figure 1c. ## **Data files and R scripts for Experiment 2** Brief description: The greenhouse experiment where seedlings were inoculated at 24 °C, 26 °C, and 30 °C right at the time of inoculation or 4 days delayed after inoculation. **Data sets included:** ·      seedling inoculation – inoculation data.xlsx ·      seedling inoculation- death data.xlsx **Data analysis scripts** ·      seedling inoculation infection data code.R- Figure 2 and analysis for the infection data ·      seedling inoculation death data code.R- Figure S2 and analysis for the mortality data **Details on data sets:** 1.     seedling inoculation- inoculation data.xlsx Data set provides the raw disease/healthy data for each plant scored. This data was used to generate Figure 2 2.     seedling inoculation- death data.xlsx Data set provides the raw number of dead plants used in the analysis. This data was used to generate Figure S2. ## **Data files and R scripts for Experiment 3** Brief description: The field experiment where infected plants were transplanted outside and monitored for symptoms from May- November 2021.  **Data sets included:** ·      daily_high_temps.txt ·      flower_summary_data.xls ·      raw field data.xls **Data analysis scripts** ·      ‘temperature_by_date_figures.R’ – all figures and analysis for Fig 3. ·      ‘2-line models.R’ – shows how the 2 line model was fit to determine the ‘cut-off’ temperature for heat-dependent curing **Details on data sets:** 1.     daily_high_temps.txt :Data set that provides the daily high temperature for every data date in the field, taken from the Beltsville weather station. This data was used to generate Figure 3a. 2.     flower.summary.data.xls : Summary data set that provides daily and average high and low temperatures for each collection date in the field, as well as the total number of healthy and infected flowering plants (Experiment 3). This data was used to generate Figures 3b-d. Data is saved as an excel file, and the second tab contains a readme with explanations for each column 3.     Raw_field_data.xls: The raw data on infection status for the 178 infected plants in the field. Each row is an individual plant.  * Each row is one plant, with different columns for status at each day. * The first two rows give positional data for the plant * Columns marked ‘Status_date’ (no color) give the raw data on plant status that was collected in the field. V=vegetative, B=bolting, D=diseased (all), PD = partially diseased, LD= light disease, X=dead, PO= post reproductive (not flowering), ST = sterile (no sign of pollen, stigma or spores). * Columns marked ‘veg_date’ and highlighted in green show a binomial score for whether the plant was flowering (‘F’-pink) or vegetative (‘V’ -green). * Columns marked ‘infected_date’ are scored as either: ‘D’ – all flowers with spores, 'H' -all flowers Healthy, or ‘PD’ – a mix of healthy and infected flowers. Sterile ‘st’ flowers were considered healthy here, because the fungus is not reproducing. * ‘Dis.flwrs_date’ is an ordinal score for the number of diseased flowers per plant (0=0, 1= 1-10, 2=11-150, 3=150-200). * ‘Healthy.flwrs_date’ is an ordinal score for the number of healthy flowers per plant.  Same criteria as above. **Missing data code**: NA