Environmental morphing enables informed dispersal of the dandelion diaspore
- University of Oxford, United Kingdom
- University of Glasgow, United Kingdom
- Utrecht University, Netherlands
- Heriot-Watt University, United Kingdom
- University of Edinburgh, United Kingdom
- UK Centre for Ecology & Hydrology, United Kingdom
- Imperial College London, United Kingdom
Abstract
Animal migration is highly sensitised to environmental cues, but plant dispersal is considered largely passive. The common dandelion, Taraxacum officinale, bears an intricate haired pappus facilitating flight. The pappus enables the formation of a separated vortex ring during flight; however, the pappus structure is not static but reversibly changes shape by closing in response to moisture. We hypothesised that this leads to changed dispersal properties in response to environmental conditions. Using wind tunnel experiments for flow visualisation, particle image velocimetry, and flight tests we characterised the fluid mechanics effects of the pappus morphing. We also modelled dispersal to understand the impact of pappus morphing on diaspore distribution. Pappus morphing dramatically alters the fluid mechanics of diaspore flight. We found that when the pappus closes in moist conditions, the drag coefficient decreases and thus the falling velocity is greatly increased. Detachment of diaspores from the parent plant also substantially decreases. The change in detachment when the pappus closes increases dispersal distances by reducing diaspore release when wind speeds are low. We propose that moisture-dependent pappus-morphing is a form of informed dispersal allowing rapid responses to changing conditions.
Data availability
The Source data for all figures has been deposited to Zenodo, doi: 10.5281/zenodo.7038366
-
Environmental morphing enables informed dispersal of the dandelion diasporeZenodo, doi: 10.5281/zenodo.7038366.
Article and author information
Author details
Ignazio Maria Viola
Funding
Leverhulme Trust (RPG-2016-255)
- Enrico Mastropaolo
- Ignazio Maria Viola
- Naomi Nakayama
Leverhulme Trust (ECF-2019-424)
- Madeleine Seale
Biotechnology and Biological Sciences Research Council (P011586/1 and T006153/1)
- Michael R Blatt
European Commission (ERC-2020-COG 101001499)
- Ignazio Maria Viola
Royal Society (UF140640 and URF-R-201035)
- Naomi Nakayama
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2022, Seale et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 2,021
- views
-
- 248
- downloads
-
- 8
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Environmental morphing enables informed dispersal of the dandelion diaspore
eLife 11:e81962.
https://doi.org/10.7554/eLife.81962
Further reading
-
- Physics of Living Systems
Proteins containing prion-like low complexity domains (PLDs) are common drivers of the formation of biomolecular condensates and are prone to misregulation due to amino acid mutations. Here, we exploit the accuracy of our residue-resolution coarse-grained model, Mpipi, to quantify the impact of amino acid mutations on the stability of 140 PLD mutants from six proteins (hnRNPA1, TDP43, FUS, EWSR1, RBM14, and TIA1). Our simulations reveal the existence of scaling laws that quantify the range of change in the critical solution temperature of PLDs as a function of the number and type of amino acid sequence mutations. These rules are consistent with the physicochemical properties of the mutations and extend across the entire family tested, suggesting that scaling laws can be used as tools to predict changes in the stability of PLD condensates. Our work offers a quantitative lens into how the emergent behavior of PLD solutions vary in response to physicochemical changes of single PLD molecules.
-
- Cell Biology
- Physics of Living Systems
The regulation of cell physiology depends largely upon interactions of functionally distinct proteins and cellular components. These interactions may be transient or long-lived, but often affect protein motion. Measurement of protein dynamics within a cellular environment, particularly while perturbing protein function with small molecules, may enable dissection of key interactions and facilitate drug discovery; however, current approaches are limited by throughput with respect to data acquisition and analysis. As a result, studies using super-resolution imaging are typically drawing conclusions from tens of cells and a few experimental conditions tested. We addressed these limitations by developing a high-throughput single-molecule tracking (htSMT) platform for pharmacologic dissection of protein dynamics in living cells at an unprecedented scale (capable of imaging >106 cells/day and screening >104 compounds). We applied htSMT to measure the cellular dynamics of fluorescently tagged estrogen receptor (ER) and screened a diverse library to identify small molecules that perturbed ER function in real time. With this one experimental modality, we determined the potency, pathway selectivity, target engagement, and mechanism of action for identified hits. Kinetic htSMT experiments were capable of distinguishing between on-target and on-pathway modulators of ER signaling. Integrated pathway analysis recapitulated the network of known ER interaction partners and suggested potentially novel, kinase-mediated regulatory mechanisms. The sensitivity of htSMT revealed a new correlation between ER dynamics and the ability of ER antagonists to suppress cancer cell growth. Therefore, measuring protein motion at scale is a powerful method to investigate dynamic interactions among proteins and may facilitate the identification and characterization of novel therapeutics.
