DOI: 10.15482/usda.adc/26239976
title: Data and code from: Pyrrocidines A and B demonstrate synergistic inhibition of <i>Fusarium verticillioides</i> growth

description: This dataset contains all raw data and R statistical code needed to reproduce the model fitting, model predictions, and data/model visualizations from the article:Lofton, L.W., Read, Q.D., Hamilton, H.L., Glenn, A.E., Hawkins, J.A., Mitchell, T.R., & Gold, S.E. (2025). Pyrrocidines A and B demonstrate synergistic inhibition of Fusarium verticillioides growth. Front. Microbiol., vol. 15. https://doi.org/10.3389/fmicb.2024.1480920<i>Fusarium verticillioides</i> – a mycotoxigenic fungus and food safety threat – coinhabits maize kernels with <i>Sarocladium zeae</i>. This protective endophyte produces secondary metabolites of interest, pyrrocidines A and B, which inhibit the growth of <i>F. verticillioides</i> and specifically block fumonisin biosynthesis. Here, using pyrrocidine dose-response assays, we discovered a potent synergy between pyrrocidines A and B, where they functioned powerfully together to inhibit <i>F. verticillioides</i> growth. Further, results provided evidence that <i>FvZBD1</i> confers partial tolerance to pyrrocidines, particularly pyrrocidine A, and that pyrrocidine functions through <i>FvZBD1</i> to effectively eliminate fumonisin biosynthesis. Additionally, we showed that the <i>FvABC3</i> (FVEG_11089) mutant, earlier described as hypersensitive to pyrrocidine, is particularly sensitive to pyrrocidine B. Thus, pyrrocidine A and B show different target specificity (<i>FvZBD1 </i>or <i>FvABC3</i>) and synergistic action.The primary data analysis is a Bayesian generalized additive mixed model (GAMM) fit to the optical density data recorded at regular intervals from <i>F. verticillioides </i>strains grown in Bioscreen microtiter plates under different conditions, in a full-factorial design crossing strain (wild-type and two mutant strains) with multiple levels of pyrrocidine A and B concentration. The RMarkdown notebook imports the data, makes plots of the raw observations, fits the model to the data, and uses the posterior samples from the model to make predictions. Predictions are shown in graphical and tabular form, and evidence for effects is assessed using credible intervals of predictions, and Bayesian maximum <i>a posteriori </i>p-values (p<sub>MAP</sub>). A secondary analysis is presented of a dose-response assay: this is a frequentist linear model fit to a log-transformed concentration as a function of pyrrocidine type and concentration, followed by post-hoc comparisons within each pyrrocidine type. Again, results are presented in graphical and tabular form.The following files are included:<b>PyrrSynergy_MetaData.pdf</b>: File with column metadata for the data objects listed below<b>bioscreen_data.csv</b>: Primary results of Bioscreen assay<b>bioscreen_data_wt1020.csv</b>: Results of additional Bioscreen assay with concentration levels between 10 and 20<b>AGlenn_Fvzbd1PyrrbFUM.xlsx</b>: Results of dose-response assay 1 of 2<b>LLofton_Fvzbd1PyrrFUM.xlsx</b>: Results of dose-response assay 2 of 2<b>pyrrocidine_bioscreen.html</b>: HTML rendered output of R code notebook containing analysis and visualization of main dataset (Bioscreen assays)<b>fumonisin_synthesis_analysis.html</b>: HTML rendered output of R code notebook containing analysis and visualization of secondary dataset (dose-response assay)<b>pyrrocidine_bioscreen.Rmd</b>: RMarkdown notebook, main analysis<b>fumonisin_synthesis_analysis.Rmd</b>: RMarkdown notebook, secondary analysis<b>splinefit_bioscreen_20240415.rds</b>: Pre-fit model object, created by R package <b>brms</b>, so that notebook may be run to reproduce results without refitting model, which may take days to run<br>