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120 results for “plant mechanics”
Mind the Gap: Reach and Mechanical Diversity of Searcher Shoots in Climbing Plants
<p>This dataframe corresponds to the article Hattermann et al. "Mind the Gap: Reach and Mechanical Diversity of Searcher Shoots in Climbing Plants"</p> <table> <tbody> <tr> <td>Variable Abbreviation</td> <td>Description of the variable</td> <td>Type of variable</td> <td>Units</td> </tr> <tr> <td>ID</td> <td>Sample identification label at the shoot level</td> <td>Nominal variable</td> <td> </td> </tr> <tr> <td>Taxa</td> <td>Species name</td> <td>Nominal variable</td> <td> </td> </tr> <tr> <td>family</td> <td>Family name</td> <td>Nominal variable</td> <td> </td> </tr> <tr> <td>ds</td> <td>Biomes where shoots have been sampled - "temperate" corresponds to Montpellier, south of France and tropical corresponds to Sinnamary, French Guiana </td> <td>Nominal variable</td> <td> </td> </tr> <tr> <td>Leaf_expanded</td> <td>Indicates whether a shoot has been considered with at least one expanded leaf (1) or with no leaves (0)</td> <td>Discrete variable</td> <td> </td> </tr> <tr> <td>Group</td> <td>Functional group based on the climbing habit at the species level</td> <td>Nominal variable</td> <td> </td> </tr> <tr> <td>reach</td> <td>Distance in a straight line from the base to the apex of the searcher shoot (here called the “reach”)</td> <td>Continuous variable</td> <td>cm</td> </tr> <tr> <td>length</td> <td>Length of the searcher shoot</td> <td>Continuous variable</td> <td>cm</td> </tr> <tr> <td>A1_diam_basal</td> <td>Basal diameter of the searcher shoot (measured at the base of the searcher shoot)</td> <td>Continuous variable</td> <td>mm</td> </tr> <tr> <td>N_leaves</td> <td>Number of leaves</td> <td>Discrete variable</td> <td> </td> </tr> <tr> <td>seco_mom_I</td> <td>Second moment of area (I) of the measured basal segment (in 4-point bending) of the searcher shoot</td> <td>Continuous variable</td> <td>mm^4</td> </tr> <tr> <td>young_mod_E</td> <td>Structural Young's modulus (E) of the measured basal segment (in 4-point bending) of the searcher shoot from I and EI</td> <td>Continuous variable</td> <td>MN.m-2</td> </tr> <tr> <td>flex_rig_EI</td> <td>Flexural bending rigidity (EI) of the measured basal segment (in 4-point bending) of the searcher shoot</td> <td>Continuous variable</td> <td>N.mm^2</td> </tr> <tr> <td>total_freshmass</td> <td>Freshmass of the searcher shoot (including stems, laminas and petioles)</td> <td>Continuous variable</td> <td>g</td> </tr> <tr> <td>lam_freshmass</td> <td>Lamina freshmass borne by the searcher shoot</td> <td>Continuous variable</td> <td>g</td> </tr> <tr> <td>total_drymass</td> <td>Total drymass of the searcher shoot (including stems, laminas and petioles)</td> <td>Continuous variable</td> <td>g</td> </tr> <tr> <td>lam_drymass</td> <td>Lamina drymass borne by the searcher shoot</td> <td>Continuous variable</td> <td>g</td> </tr> <tr> <td>lam_area</td> <td>Lamina fresh area of the searcher shoot</td> <td>Continuous variable</td> <td>mm^2</td> </tr> <tr> <td>A_Pith</td> <td>Medullary parenchyma cross-sectional area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^2</td> </tr> <tr> <td>A_Pith_fibers</td> <td>Medullary fibre cross-sectional area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^2</td> </tr> <tr> <td>A_Xylem</td> <td>Xylem vessel and fibres cross-sectional area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^2</td> </tr> <tr> <td>A_Xylem_ray</td> <td>Xylem parenchymatous ray cross-sectional area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^2</td> </tr> <tr> <td>A_Phloem</td> <td>Phloem cross-sectional area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^2</td> </tr> <tr> <td>A_Cortex</td> <td>Cortical parenchyma cross-sectional area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^2</td> </tr> <tr> <td>A_Sclereids</td> <td>Cortical sclereids cross-sectional area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^2</td> </tr> <tr> <td>A_Cort_fibers</td> <td>Cortical fibre cross-sectional area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^2</td> </tr> <tr> <td>A_Collenchyma</td> <td>Collenchyma cross-sectional area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^2</td> </tr> <tr> <td>A_Periderm</td> <td>Periderm cross-sectional area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^2</td> </tr> <tr> <td>I_Pith</td> <td>Medullary parenchyma second moment of area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^4</td> </tr> <tr> <td>I_Pith_fibers</td> <td>Medullary fibre second moment of area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^4</td> </tr> <tr> <td>I_Xylem</td> <td>Xylem vessel and fibres second moment of area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^4</td> </tr> <tr> <td>I_Xylem_ray</td> <td>Xylem parenchymatous ray second moment of area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^4</td> </tr> <tr> <td>I_Phloem</td> <td>Phloem second moment of area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^4</td> </tr> <tr> <td>I_Cortex</td> <td>Cortical parenchyma second moment of area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^4</td> </tr> <tr> <td>I_Cort_fibers</td> <td>Cortical sclereid second moment of area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^4</td> </tr> <tr> <td>I_Sclerites</td> <td>Cortical fibre second moment of area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^4</td> </tr> <tr> <td>I_Collenchyma</td> <td>Collenchyma second moment of area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^4</td> </tr> <tr> <td>I_Periderm</td> <td>Periderm second moment of area at the base of the searcher shoot</td> <td>Continuous variable</td> <td>mm^4</td> </tr> </tbody> </table>
Cross-species interactome analysis uncovers a conserved selective autophagy mechanism for protein quality control in plants
<p>This is all the source data associated with the manuscript which has the same title with this dataset.</p> <p>The abstract and the authors of the manuscripts are below:</p> <p><strong><span>Cross-species interactome analysis uncovers a conserved </span></strong></p> <p><strong><span>selective autophagy mechanism for protein quality control in plants</span></strong></p> <p><span> </span></p> <p><span>Víctor Sánchez de Medina Hernández<sup>1,2*</sup>, Marintia Mayola Nava García<sup>1,2*</sup>, Marion Clavel<sup>1,3</sup>, Ranjith K. Papareddy<sup>1</sup>, Veselin I. Andreev<sup>1</sup>, Varsha Mathur<sup>1</sup>, Azadeh Mohseni</span><sup><span>1,4</span></sup><span>, Marta García-León</span><sup><span>1</span></sup><span>, Peng Gao</span><sup><span>1</span></sup><span>, Juan Carlos de la Concepción</span><sup><span>1</span></sup><span>, </span><span>Lorenzo Picchianti<sup>1</sup><span>, Nenad Grujic<sup>1</sup>, Roksolana Kobylinska</span><sup>1</sup><span>, Alibek Abdrakhmanov</span><sup>1,2</sup><span>, Héloïse Duvergé</span><sup>1</sup><span>, Gaurav Anand</span><sup>5</sup><span>, Nils Leibrock</span><sup>1,4</sup><span>, Anita Bianchi</span><sup>1</sup><span>, Margot Raffeiner</span><sup>6</sup><span>, Timothy Scott Crawford<sup>7</sup>, Luca Argirò</span><sup>1</sup><span>, Mateusz Matuszkiewicz</span><sup>1,8</sup><span>, Cheuk-Ling Wun</span><sup>1</sup><span>, Jakob Valdbjørn Kanne</span><sup>9</sup><span>, Anton Meinhart</span><sup>10</sup><span>, Elisabeth Roitinger<sup>1</sup>, Isabel Bäurle<sup>7</sup>, Byung Ho Kang<sup>11</sup>, Morten Petersen</span><sup>9</sup><span>, Suayib Üstün</span><sup>6</sup><span>, Yogesh Kulathu</span><sup>5</sup><span>, Tim Clausen</span><sup>10</sup><span>, Silvia Ramundo<sup>1</sup>, Yasin Dagdas<sup>1</sup></span></span></p> <p><sup><span>1 </span></sup><span>Gregor Mendel Institute (GMI), Austrian Academy of Sciences, Vienna BioCenter (VBC), Vienna, Austria.</span></p> <p><sup><span>2 </span></sup><span>Vienna BioCenter PhD Program, Doctoral School of the University of Vienna and Medical University of Vienna, A-1030, Vienna, Austria.</span></p> <p><sup><span>3</span></sup><span> </span><span>Max-Planck-Institut für Molekulare Pflanzenphysiologie, Potsdam-Golm, Germany.</span></p> <p><sup><span>4</span></sup><span> Department of Applied Genetics and Cell Biology, Institute of Molecular Plant Biology, BOKU University, Vienna, Austria.</span></p> <p><sup><span>5</span></sup><span> MRC Protein Phosphorylation and Ubiquitylation Unit, University of Dundee, Dundee, UK.</span></p> <p><sup><span>6 </span></sup><span>Faculty of Biology & Biotechnology, Ruhr-University of Bochum, 44780 Bochum, Germany.</span></p> <p><sup><span>7</span></sup><span> Institute for Biochemistry and Biology, University of Potsdam, Potsdam, Germany.</span></p> <p><sup><span>8 </span></sup><span>Department of Plant Genetics, Breeding and Biotechnology, Institute of Biology, Warsaw University of Life Sciences, Warsaw, Poland.</span></p> <p><sup><span>9 </span></sup><span>Functional Genomic Section, Department of Biology, University of Copenhagen, Copenhagen, Denmark.</span></p> <p><sup><span>10</span></sup><span> Research Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Vienna, Austria.</span></p> <p><sup><span>11</span></sup><span> School of Life Sciences, Centre for Cell & Developmental Biology and State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China.</span></p> <p><span> </span></p> <p><span>*These authors contributed equally to this work</span></p> <p><span> </span></p> <p><span>Correspondence: Yasin Dagdas, </span><span><a href="mailto:yasin.dagdas@gmi.oeaw.ac.at"><span>yasin.dagdas@gmi.oeaw.ac.at</span></a></span></p> <p><strong><span> </span></strong></p> <p><strong><span>Abstract</span></strong></p> <p><span>Selective autophagy is a fundamental protein quality control pathway that safeguards proteostasis by degrading damaged or surplus cellular components, particularly under stress. This process is orchestrated by selective autophagy receptors (SARs) that direct specific cargo for degradation. While significant strides have been made in understanding the molecular framework of selective autophagy, the diversity of SAR repertoires across species remain largely unexplored. Through a comparative interactome analysis across five model organisms, we identified a suite of conserved and lineage-specific SAR candidates. Among these, we validated CESAR as a conserved SAR critical for proteostasis under proteotoxic stress. CESAR specifically facilitates the degradation of hydrophobic, ubiquitinated protein aggregates and is indispensable for heat stress tolerance. Our study offers a rich resource for SAR discovery and positions CESAR as a pivotal regulator of proteostasis, with broad implications for improving stress resilience in plants.</span></p>
Data for: Mechanisms of fire-maintained plant species diversity in species-rich wet pine savannas
<p><span>Temperate savannas and grasslands maintained by frequent, low-intensity disturbances such as fire contain among the most species-rich plant communities in the world. Precisely how these disturbances maintain such high fine-scale diversity is poorly understood. This study examined the effects of the frequency of simulated fire (clipping combined with litter removal) and the relative importance of recruitment and survival on species diversity and trait and species composition at each of two pine savannas in southeastern Mississippi (USA) that had not been recently burned. Ten 2 </span><span>×</span><span> 2 m plots at each site were clipped/cleared annually from 2014 to 2019 and again in spring 2021 (annual frequency). The other 10 clipping plots were not clipped from 2018 to 2020 (reduced frequency). Vegetation in small subplots in annual frequency and reduced frequency plots was compared in August 2021 to test the effects of a short period without clipping on diversity and composition. To test the relative importance of recruitment and survival on diversity and composition, four 0.25 </span><span>×</span><span> 0.25 m quarter plots were established within each of 10 annual-frequency plots per site following a clipping treatment in fall 2019 and assigned a 2 </span><span>×</span><span> 2 factorial arrangement of transplantation of sods from long-unburned areas and herbicide application. Reducing the frequency of clipping reduced plant diversity and altered composition at both sites. A comparison of diversity and trait composition responses to transplant and herbicide treatments revealed how recruitment and survival combined to affect species diversity. Partial or complete recovery of diversity following clipping and litter removal at both sites was driven by rapid increases in short-lived, resilient species that show fire-stimulated emergence from a seed bank and the persistence of long-lived species capable of surviving the prolonged period without fire or clipping. Species with reduced resilience and persistence were more likely to be lost in the reduced frequency treatment. Results are consistent with a model of short-term coexistence of maximum species diversity maintained by the most frequent fire regimes fuels will permit.</span></p>
Nitrogen enrichment and foliar fungal pathogens affect the mechanisms of multispecies plant coexistence
<p>This is the data and code repository for the manuscript entitled "Nitrogen enrichment and foliar fungal pathogens affect the mechanisms of multispecies plant coexistence".</p> <p>DATA:</p> <p><strong>data.txt</strong></p> <p>Dataset collected in the PaNDiv experiment, a large field experiment in Münchenbuchsee (near Bern) which investigates the mechanisms by which nitrogen enrichment affects ecosystem functioning. The dataset is composed by the following elements:</p> <ul> <li><em>year </em>--- 2017 or 2018</li> <li><em>block </em>--- experimental block in the PaNDiv experiment (1, 2, 3 or 4)</li> <li><em>plot </em>--- experimental plot in the PaNDiv experiment (from 1 to 336)</li> <li><em>nitrogen </em>--- addition of nitrogen to the soil (0 = no, 1 = yes)</li> <li><em>fungicide </em>--- application of fungicide to the vegetation (0 = no, 1 = yes)</li> <li><em>treatment</em> --- control, nitrogen addition, fungicide application, and their combined effect</li> <li><em>number</em> --- replicate number of the focal species; numbers are repeated because it restarts with each target focal-neighbour species combination (not shown)</li> <li><em>focal_sp</em> --- 8 possible species: <ul> <li>tar_off = <em>Taraxacum officinale</em></li> <li>cre_bie = <em>Crepis biennis</em></li> <li>rum_ace = <em>Rumex acetosa</em></li> <li>dac_glo = <em>Dactylis glomerata</em></li> <li>ant_odo = <em>Anthoxanthum odoratum</em></li> <li>cen_jac = <em>Centaurea jacea</em></li> <li>sal_pra = <em>Salvia pratensis</em></li> <li>pla_med = <em>Plantago media</em></li> </ul> </li> <li><em>biomass_i </em>--- initial biomass of the focal plant (start of the growing season; February/March)</li> <li><em>biomass_f</em> --- final biomass of the focal plant (end of the growing season; June)</li> <li><em>tar_off</em> --- visually estimated cover for this species as a neighbour</li> <li><em>cre_bie</em> --- visually estimated cover for this species as a neighbour</li> <li><em>rum_ace</em> --- visually estimated cover for this species as a neighbour</li> <li><em>dac_glo</em> --- visually estimated cover for this species as a neighbour</li> <li><em>ant_odo</em> --- visually estimated cover for this species as a neighbour</li> <li><em>cen_jac</em> --- visually estimated cover for this species as a neighbour</li> <li><em>sal_pra</em> --- visually estimated cover for this species as a neighbour</li> <li><em>pla_med</em> --- visually estimated cover for this species as a neighbour</li> <li><em>herbs </em>--- visually estimated cover for non-target herb species in the PaNDiv experiment</li> <li><em>grasses </em>--- visually estimated cover for non-target grass species in the PaNDiv experiment</li> <li><em>legumes </em>--- visually estimated cover for non-target legume species in the PaNDiv experiment</li> </ul> <p> </p> <p>CODE:</p> <p><strong>001-optimx.R</strong></p> <p>Code that uses maximum likelihood to fit population models to the data. Produces several datasets with model coefficients and AIC values.</p> <p> </p> <p><strong>002-model_sel_coefs.R</strong></p> <p>Code to select the coefficients based on the best model and add the size effect of the focal plants when needed. Creates all interaction matrices and intrinsic growth rate vectors.</p> <p> </p> <p><strong>003-final_matrices.R</strong></p> <p>Code to adjust the matrices for coexistence computing.</p> <p> </p> <p><strong>004-coexistence.R</strong></p> <p>Computes structural coexistence outputs. Provides a clean dataset with structural niche differences, structural fitness differences, and other multispecies coexistence metrics.</p>
LC-HRAM-MS data for "Emergence of a proton exchange-based isomerization and lactonization mechanism in the plant coumarin synthase COSY"
<p>LC-HRAM-MS data underlying Figures 2b and 3b for "Emergence of a proton exchange-based isomerization and lactonization mechanism in the plant coumarin synthase COSY"</p>
Fig. 7 in Sites of biosynthesis and storage of Taxol in Taxus media (Rehder) plants: Mechanism of accumulation
Fig. 7. Model summarizes the dynamic production of Taxol in Taxus plant stem sections suggesting wood as the site of Taxol biosynthesis, and phloem and outer bark as the sites of storage.
Fig. 6 in Sites of biosynthesis and storage of Taxol in Taxus media (Rehder) plants: Mechanism of accumulation
Fig. 6. In situ immuno-labelling of TS enzyme and Taxol in Taxus stem transverse sections. (A) Control stem section received no primary Abs compared to (B) a section that received anti-TS Ab and (C) a section that received anti-Taxol Ab.
Fig. 5 in Sites of biosynthesis and storage of Taxol in Taxus media (Rehder) plants: Mechanism of accumulation
Fig. 5. Comparison between Taxus plant (A-G) tissues, (H–N) organs and (O–W) age on the contents of (A, H, O) Taxol (B, I, P) baccatin III, (C, J, Q) polyphenols, (D, K, R) HB and the expression of (E, L, S) TS, (F, M, T) PAL and (G, N, W) PAM genes. In case of (D) the comparison was between wood and phloem only, since the bark did not show HB. The data are displayed as the mean ± standard error of the mean. The statistical significance was calculated with a Student-T-test and oneway ANOVA, and the significance level indicated by asterisks. P-value <0.05 was considered significant.
Fig. 4 in Sites of biosynthesis and storage of Taxol in Taxus media (Rehder) plants: Mechanism of accumulation
Fig. 4. Comparison between intact plant and plant callus culture (TC) in terms of (A) taxoid contents (Taxol versus baccatin III), number of HB (indicated as red droplets) in (B) TC and (C) intact plant stem sections, and expression of (D and E) TS, (F) PAL and (G) PAM genes. The data are displayed as the mean ± standard error of the mean. The statistical significance was calculated with the Student-t-test and the significance level indicated by asterisks. P-value <0.05 was considered significant. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 2 in Sites of biosynthesis and storage of Taxol in Taxus media (Rehder) plants: Mechanism of accumulation
Fig. 2. Taxol localization and storage. (A) Transverse section of a Taxus plant stem showing the location of Taxol-containing HB (red-stained droplets) within the wood and phloem in comparison to (B) close up view in the vascular bundle (VB) of a root section and (C) close up view in the vascular bundle (VB) of a needle (Taxus leaf) section. (D) and (E) Close up views in the wood and phloem, respectively, to show the distribution of Taxol-containing HB within Taxus stem sections. (F) Pearson's correlation between Taxol content and the number of HB within different plant samples (Pearson's correlation, r2 = 0.77). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 3 in Sites of biosynthesis and storage of Taxol in Taxus media (Rehder) plants: Mechanism of accumulation
Fig. 3. Correlation of Taxol accumulation to (A) baccatin III accumulation (Pearson's correlation, r2 = 0.12), (B) polyphenol accumulation (Pearson's correlation, r2 = 0.95) and (C) TS gene expression (Pearson's correlation, r2 = 0.07). (D) Correlation of baccatin III to TS gene expression (Pearson's correlation, r2 = 0.80). The data were analyzed using Pearson's correlation and the data were considered to have a normal distribution. P value <0.05 was considered as significant.
Data from: A novel mechanism for grazing lawn formation: large herbivore-induced modification of the plant-soil water balance
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The temporal dimension of plant-soil microbe interactions: mechanisms promoting feedback between generations
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Data from: Mechanisms of plant–plant interactions: concealment from herbivores is more important than abiotic-stress mediation in an African savannah
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Data for: Mechanisms of fire-maintained plant species diversity in species-rich wet pine savannas
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Data from: Multiple mechanisms confer stability to isolated populations of a rare endemic plant
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Mechanisms of dietary resource partitioning in large-herbivore assemblages: a plant-trait-based approach
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Data from: Beyond plant-soil feedbacks: mechanisms driving plant community shifts due to land-use legacies in post-agricultural forests
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Data from: Diplostigmaty in plants: a novel mechanism that provides reproductive assurance
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Spatiotemporal niche-based mechanisms support a stable coexistence of ants and spiders in an extrafloral nectary-bearing plant community
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