The early dodder gets the host: decoding the coiling patterns of Cuscuta campestris with automated image processing.

Autor: Bentelspacher M; Division of Plant Science and Technology, University of Missouri, Columbia, MO, 65211, USA., Amézquita EJ; Division of Plant Science and Technology, University of Missouri, Columbia, MO, 65211, USA. eah4d@missouri.edu.; Department of Mathematics, University of Missouri, Columbia, MO, 65211, USA. eah4d@missouri.edu., Adhikari S; Division of Plant Science and Technology, University of Missouri, Columbia, MO, 65211, USA., Barros J; Division of Plant Science and Technology, University of Missouri, Columbia, MO, 65211, USA., Park SY; Division of Plant Science and Technology, University of Missouri, Columbia, MO, 65211, USA. parksoy33@gmail.com.
Jazyk: angličtina
Zdroj: Plant cell reports [Plant Cell Rep] 2024 Nov 16; Vol. 43 (12), pp. 282. Date of Electronic Publication: 2024 Nov 16.
DOI: 10.1007/s00299-024-03337-1
Abstrakt: Key Message: We developed an in-house Python-based image analysis pipeline to investigate the movement patterns of Cuscuta. Our analysis unveiled that the coiling and circumnutation movements of Cuscuta are regulated by its intrinsic circadian rhythm. Cuscuta spp., commonly known as dodders, are rootless and leafless stem parasitic plants. Upon germination, Cuscuta starts rotating immediately in a counterclockwise direction (circumnutation) to locate a host plant, creating a seamless vascular connection to steal water and nutrients from its host. In this study, our aim was to elucidate the dynamics of the coiling patterns of Cuscuta, which is an essential step for successful parasitism. Using time-lapse photography, we recorded the circumnutation and coiling movements of C. campestris at different inoculation times on non-living hosts. Subsequent image analyses were facilitated through an in-house Python-based image processing pipeline to detect coiling locations, angles, initiation and completion times, and duration of coiling stages in between. The study revealed that the coiling efficacy of C. campestris varied with the inoculation time of day, showing higher success and faster initiation in morning than in evening. These observations suggest that Cuscuta, despite lacking leaves and a developed chloroplast, can discern photoperiod changes, significantly determining its parasitic efficiency. The automated image analysis results confirmed the reliability of our Python pipeline by aligning closely with manual annotations. This study provides significant insights into the parasitic strategies of C. campestris and demonstrates the potential of integrating computational image analysis in plant biology for exploring complex plant behaviors. Furthermore, this method provides an efficient tool for investigating plant movement dynamics, laying the foundation for future studies on mitigating the economic impacts of parasitic plants.
Competing Interests: Declarations Conflict of interest All authors declare that they have no conflicts of interest.
(© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)
Databáze: MEDLINE
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