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Cuticle thickness affects dynamics of volatile emission from petunia flowers

Nature Chemical Biology volume 17, pages 138–145 (2021)Cite this article

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Abstract

The plant cuticle is the final barrier for volatile organic compounds (VOCs) to cross for release to the atmosphere, yet its role in the emission process is poorly understood. Here, using a combination of reverse-genetic and chemical approaches, we demonstrate that the cuticle imposes substantial resistance to VOC mass transfer, acting as a sink/concentrator for VOCs and hence protecting cells from the potentially toxic internal accumulation of these hydrophobic compounds. Reduction in cuticle thickness has differential effects on individual VOCs depending on their volatility, and leads to their internal cellular redistribution, a shift in mass transfer resistance sources and altered VOC synthesis. These results reveal that the cuticle is not simply a passive diffusion barrier for VOCs to cross, but plays the aforementioned complex roles in the emission process as an integral member of the overall VOC network.

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Fig. 1: VOC distribution within cell and effect of PhABCG12 downregulation on total wax amount in petunia flowers.
Fig. 2: Effect of PhABCG12 downregulation on flower phenotype, cuticle properties and scent network in petunia flowers.
Fig. 3: Effect of PhABCG12 downregulation on VEFs, emission and biosynthetic fluxes of representative VOCs and cellular distribution of VOCs in 2-day-old petunia flowers.
Fig. 4: Effect of dewaxing on corolla wax levels, cuticle permeability, VOC internal pools and emissions in 2-day-old petunia flowers.
Fig. 5: Effect of dewaxing and Phe feeding on VEFs and cellular VOC distributions in 2-day-old petunia flowers.
Fig. 6: Schematic presentation of shift in the mass transfer resistance sources by reduction in cuticle thickness.

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Data availability

We declare that all the data supporting the funding of this study are available within the paper and its supplementary information files or from the corresponding author upon reasonable request. P. axillaris genomic data were obtained from http://solgenomics.net using the P. axillaris v.1.6.2 genome database. Source data are provided with this paper.

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Acknowledgements

This work was supported by grant from the National Science Foundation no. IOS-1655438 to N.D. and J.A.M. and by the USDA National Institute of Food and Agriculture Hatch Project no. 177845 to N.D. We acknowledge the use of the imaging facilities of the Bindley Bioscience Center, a core facility of the NIH-funded Indiana Clinical and Translational Sciences Institute, for collection of confocal microscopy images. We thank Y. Oshima (National Institute of Advanced Industrial Science and Technology, Japan) for providing pDONOR_P4PIR-InMYB1pro and R4pGWB5_stop_HSP vectors. We thank R. Seiler and L. Mueller for technical assistance on SEM and TEM, respectively.

Author information

Author notes

  1. Benoît Boachon

    Present address: BVpam FRE 3727, Université de Lyon, Université Jean Monnet Saint-Etienne, CNRS, Saint-Etienne, France

  2. These authors contributed equally: Pan Liao, Shaunak Ray.

Authors and Affiliations

  1. Department of Biochemistry, Purdue University, West Lafayette, IN, USA

    Pan Liao, Benoît Boachon, Joseph H. Lynch, John A. Morgan & Natalia Dudareva

  2. Davidson School of Chemical Engineering, Purdue University, West Lafayette, IN, USA

    Shaunak Ray, Arnav Deshpande & John A. Morgan

  3. Purdue Center for Plant Biology, Purdue University, West Lafayette, IN, USA

    Joseph H. Lynch, Scott McAdam & Natalia Dudareva

  4. Department of Botany and Plant Pathology, Purdue University, West Lafayette, IN, USA

    Scott McAdam

  5. Department of Horticulture and Landscape Architecture, Purdue University, West Lafayette, IN, USA

    Natalia Dudareva

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Contributions

B.B., J.A.M. and N.D. conceived the project and designed research. P.L. performed analysis of flower phenotypes, protein levels, seed production and germination rates, VOC emission and their internal pools, internal cellular VOC distribution over a 15 h period, toluidine and propidium iodide staining experiments, expression analysis and feeding experiments. S.R. performed wax profiling, VOC distribution and metabolic flux analyses, dewaxed experiments, water loss determination and analyzed rhythmicity of VOC production and accumulation. B.B. generated PhABCG12-RNAi lines and performed initial expression and metabolic profiling. J.H.L. performed analysis of sucrose and starch levels as well as flux through the shikimate pathway. A.D. run and analyzed samples for shikimate pathway flux experiments. S.M. analyzed respiration rate. P.L., S.R, B.B., J.H.L., A.D., S.M., J.A.M. and N.D. analyzed data. N.D. wrote the manuscript with contribution from all authors. All authors read and edited the manuscript.

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Correspondence to Natalia Dudareva.

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Extended data

Extended Data Fig. 1 Effect of PhABCG12 downregulation on cuticle composition of 2-day-old petunia petals.

a, Wax composition by major constituent classes: fatty acids, primary alcohols, n-alkanes, and alkyl esters in 2-day-old flowers of wild type (WT), EV control and transgenic lines 7, 8, and 9 collected at 10 PM. Relative amount of each wax constituent is presented as a percentage of the total in their respective compound class. X axis represents the chain length (number of carbon atoms) for each constituent. Inset graphs show total amount of each class (µg/g DW). Data are means ± s.e.m. (n = 5 biological replicates). P values were determined by two-way ANOVA with the Tukey’s multiple comparisons test relative to the corresponding WT (black) and EV (blue) controls. b, Relative abundances of major constituent classes: fatty acids, primary alcohols, n-alkanes, and alkyl esters (shown in a) in wax of 2-day-old flowers of WT, EV control and transgenic lines 7, 8, and 9 collected at 10 PM. Data are means ± s.e.m. (n = 5 biological replicates).

Source data

Extended Data Fig. 2 Effect of PhABCG12 downregulation on petunia flower phenotype.

a, Representative 2-day-old flowers from wild type (WT), empty vector control (EV) and 3 independent PhABCG12-RNAi lines (7, 8 and 9). b, Corolla diameter, (c) flower weight and (d) corolla weight from WT, empty vector (EV)-transformed flowers and 3 independent PhABCG12-RNAi lines (7, 8 and 9). Data are means ± s.e.m. In b and c, n = 20 biological replicates for WT, n = 18 biological replicates for EV; and n = 9, 9 and 12 biological replicates for PhABCG12 lines 7, 8, and 9, respectively; in d, n = 19 biological replicates for WT, n = 14 biological replicates for EV; and n = 9, 7 and 9 biological replicates for PhABCG12 lines 7, 8, and 9, respectively. P values were determined by two-way ANOVA with the Tukey’s multiple comparisons test relative to the WT (black) and EV (blue) controls. Scale bar in a, 1 cm.

Source data

Extended Data Fig. 3 Histogram showing cuticle thickness distribution in wild-type and PhABCG12 petunia flowers.

Cuticle thickness probability distribution in epidermal cells of 2-day-old wild type (WT) and PhABCG12-RNAi line 9 flowers. To be consistent cuticle thickness was measured only in conical cells. The distribution is presented as the probability of different cuticle thickness values over 675 measurements. Data are means ± s.e.m. (n = 675 measurements). Measurements were taken from discreet locations in a minimum of 11 cells per genotype.

Source data

Extended Data Fig. 4 Effect of PhABCG12 downregulation on emissions and internal pools of individual benzenoid/phenylpropanoid volatiles in 2-day-old petunia flowers.

Emission rates (a) and internal pools (b) of individual VOCs in wild type (WT), empty vector (EV) control and three independent PhABCG12-RNAi lines (7, 8 and 9). Data are means ± s.e.m. (in a n = 6 biological replicates for all samples; and in b, n = 8 biological replicates for WT, n = 6 biological replicates for EV, PhABCG12-RNAi lines 7 and 8; and n = 9 biological replicates for PhABCG12-RNAi line 9). P values were determined by two-way ANOVA with the Tukey’s multiple comparisons test relative to the corresponding WT (black) and EV (blue) controls.

Source data

Extended Data Fig. 5 Metabolic flux analysis of benzenoid and phenylpropanoid VOCs from petunia flowers supplied with 150 mM 13C6-phenylalanine.

Metabolic flux maps of 2-day-old wild-type (a) and PhABCG12-9 (b) petunia petals fed with 150 mM 13C6-Phe. Fluxes were obtained from time-course measurements of label incorporation in the endogenous pools and headspace collections of Phe-derived VOCs. Arrow thickness reflects the relative value of fluxes normalized to the incoming flux (turnover of 13C6-Phe). BAlc, benzyl alcohol; BAld, benzaldehyde; BB, benzylbenzoate; Eug, eugenol; IEug, isoeugenol; MB, methylbenzoate; 2-PE, 2-phenylethanol; PEB, phenylethylbenzoate; and PhAld, phenylacetaldehyde. The total labeled biosynthetic (c) and emission (d) fluxes shown in (a) and (b). Flux values are given in nmol·g FW−1·h−1. Data are the mean ± s.e.m. of total biosynthetic and emission fluxes calculated from the regression of time-dependent VOC pools and emission collections. Regression was performed using all data points simultaneously from biological replicates to obtain flux distribution values. Standard error of calculated fluxes were determined based on the propagation of measurement standard errors (n = 3 biological replicates) and the model regression error. P value was determined by unpaired two-tailed Student’s t-test relative to wild type.

Source data

Extended Data Fig. 6 Pool sizes and isotopic abundances of total endogenous (internal pools) and exogenous (emitted) VOCs in control and PhABCG12-9 line petunia petals fed with 150 mM 13C6-Phe.

Total internal pools (a) and emissions (b) of VOCs from wild-type (WT) and PhABCG12-9 petunia corollas supplied with 150 mM 13C6-Phe for 4 h. Isotopic labeling of internal pools (c) and emitted volatiles (d) over 4 h, from 6 PM till 10 PM. Data are means ± s.e.m. (n = 3 biological replicates).

Source data

Extended Data Fig. 7 Effect of PhABCG12 downregulation on emission and biosynthetic fluxes of individual benzenoid/phenylpropanoid VOCs.

Emission and biosynthetic fluxes for individual benzenoid/phenylpropanoid VOCs in 2-day-old wild-type (WT) (a) and PhABCG12-9 (b) petunia flowers. BAlc, benzyl alcohol; IEug, isoeugenol; 2-PE, 2-phenylethanol; PhAld, phenylacetaldehyde. Data are means ± s.e.m. (n = 3 biological replicates).

Source data

Extended Data Fig. 8 Effect of PhABCG12 downregulation on cellular distribution of individual benzenoid/phenylpropanoid VOCs in 2-day-old petunia flowers.

a, Distribution of individual VOCs in wild-type (WT), empty vector control (EV) and PhABCG12-RNAi lines 7, 8 and 9. VOCs are shown in order of increasing volatility (left to right). Data are means ± s.e.m. (n = 4 biological replicates). P values were determined by unpaired two-tailed Student’s t-test relative to corresponding wild type. b, c, Relationships between distribution of individual VOCs in the cuticle and their corresponding (b) vapor pressure and (c) octanol-water partitioning coefficient. Data are means ± s.e.m. (n = 4 biological replicates). In b and c, Pearson correlation coefficients (R2) and corresponding P values are shown. BAlc, benzyl alcohol; BAld, benzaldehyde; BB, benzylbenzoate; IEug, isoeugenol; MB, methylbenzoate; 2-PE, 2-phenylethanol; PhAld, phenylacetaldehyde.

Source data

Extended Data Fig. 9 Total internal pools, emissions and distribution in cuticle of benzenoid/phenylpropanoid VOCs in 2-day-old petunia flowers around peak of emission.

Total internal pools (a), emissions (b) and distribution in cuticle (c) of VOCs collected from wild-type (WT) and PhABCG12-9 flowers over 15 h period. Data are means ± s.e.m. (n = 3 biological replicates in a and b; and n = 6 biological replicates in c). In c, PhABCG12-9 VOC distribution in cuticle was statistically different (P < 0.0001) from WT based on two-way ANOVA.

Source data

Extended Data Fig. 10 Analysis of metabolic potential of petunia flowers after dewaxing.

a, PAL activity detected in nondewaxed and dewaxed 2-day-old wild-type flowers in the beginning (6 PM) and the end (10 PM) of scent collection period. Data are means ± s.e.m. (n = 3 biological replicates). PAL activity was not statistically different between nondewaxed and dewaxed petals (P = 0.1476 and 0.2824 for 6 PM and 10 PM, respectively, determined by two-tailed Student’s t-test). b, Volatile emission from nondewaxed and dewaxed wild-type flowers upon feeding different (0 - 150 mM) Phe concentrations. c, VOC biosynthetic fluxes in nondewaxed and dewaxed wild-type flowers fed with 150 mM Phe. d, Internal VOC pools in nondewaxed and dewaxed wild-type flowers upon feeding different (0 -150 mM) Phe concentrations. e, Fold-change in VOC internal pools from 6 PM to 10 PM in nondewaxed and dewaxed wild-type flowers upon feeding different (0 - 150 mM) Phe concentrations. P values were determined by unpaired two-tailed Student’s t-test relative to corresponding non-dewaxed samples. Data in b - e are means ± s.e.m. (n = 4 biological replicates).

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Liao, P., Ray, S., Boachon, B. et al. Cuticle thickness affects dynamics of volatile emission from petunia flowers. Nat Chem Biol 17, 138–145 (2021). https://doi.org/10.1038/s41589-020-00670-w

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