Rhizopus stolonifer Exhibits Necrotrophic Behavior when Causing Soft Rot in Ripe Fruit

Citation

Mesquida-Pesci, S. D., Morales-Cruz, A., Rodriguez-Pires, S., Figueroa-Balderas, R., Silva, C. J., Sbodio, A., ... & Blanco-Ulate, B. (2024). Rhizopus stolonifer Exhibits Necrotrophic Behavior when Causing Soft Rot in Ripe Fruit. Phytopathology, 114(3), 1–13. https://doi.org/10.1094/PHYTO-03-24-0081-R

Abstract

Rhizopus stolonifer is known for causing soft rot in fruits and vegetables during postharvest. Although it has traditionally been considered a saprophyte, it appears to behave more like a necrotrophic pathogen. In this study, we propose that R. stolonifer invades host tissues by actively killing host cells and overcoming the host defense mechanisms, as opposed to growing saprophytically on decaying plant matter. We tested this hypothesis by characterizing R. stolonifer infection strategies when infecting four fruit hosts (tomato, grape, strawberry, and plum). We started by generating a high-quality genome assembly for R. stolonifer using PacBio sequencing. This led to a genome size of 45.02 Mb, an N50 of 2.87 Mb, and 12,644 predicted loci with protein-coding genes. Next, we performed a transcriptomic analysis to identify genes that R. stolonifer preferentially uses when growing in fruit versus culture media. We categorized these infection-related genes into clusters according to their expression patterns during the interaction with the host. Based on the expression data, we determined that R. stolonifer has a core infection toolbox consisting of strategies typical of necrotrophs, which includes a set of 33 oxidoreductases, 7 proteases, and 4 cell wall-degrading enzymes to facilitate tissue breakdown and maceration across various hosts. This study provides new genomic resources for R. stolonifer and advances the knowledge of Rhizopus–fruit interactions, which can assist in formulating effective and sustainable integrated pest management approaches for soft rot prevention.

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Acknowledgments We thank Yiduo Wei and Stefan Petrasch for assisting us with data analysis and interpretation; Manon Paineau for providing advice on optimizing the bioinformatic pipeline; and Carlos Carachure, Juniper Piedmont, and Annie Willett for their review of the manuscript's narrative. Author contributions: B.B.-U. designed the study. B.B.-U., A.M.-C., and R.F.-B. designed the methodology. S.D.M.-P., A.M.-C., S.R.-P., R.F.-B., C.J.S., A.S., E.G.-B., and P.M.R. conducted the experiments. S.D.M.-P., A.M.-C., and C.J.S. conducted genomic and transcriptomic analyses. B.B.-U., S.D.M.-P., and A.M.-C. carried out data analysis and interpretation of results. B.B.-U. and S.D.M.-P. wrote the manuscript, with contributions and revisions from all co-authors. B.B.-U. and D.C. provided funding and resources and coordinated the study. Funding: Support was provided by the College of Agriculture and Environmental Sciences and the Department of Plant Sciences at the University of California, Davis as start-up funding to B. Blanco-Ulate; and the Department of Plant Sciences, University of California, Davis, funded by endowments, particularly the James Monroe McDonald Endowment, administered by the Division of Agriculture and Natural Resources, University of California as a graduate student award to S. D. Mesquida-Pesci. The project leading to these results received funding from the “La Caixa” Foundation (ID 100010434; under the agreement LCF/BQ/AA19/11720034) to S. D. Mesquida-Pesci. The author(s) declare no conflict of interest.

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