Genetic diversity of stilbene metabolism in Vitis sylvestris
Journal of Experimental Botany
Genetic diversity of stilbene metabolism in Vitis sylvestris
Dong Duan 2
David Halter 1
Raymonde Baltenweck 1
Christine Tisch 0
Viktoria Tröster 2
Andreas Kortekamp 0
Philippe Hugueney 1
Peter Nick 2
0 DLR Rheinpfalz State Education and Research Center of Viticulture and Horticulture and Rural Development , Breitenweg 71, D-67435 Neustadt , Germany
1 Métabolisme Secondaire de la Vigne, UMR 1131, INRA, Université de Strasbourg , 28 rue de Herrlisheim, F-68021 Colmar , France
2 Molecular Cell Biology, Botanical Institute 1, Karlsruhe Institute of Technology , Kaiserstr. 2, 78133 Karlsruhe , Germany
Stilbenes, as important secondary metabolites of grapevine, represent central phytoalexins and therefore constitute an important element of basal immunity. In this study, potential genetic variation in Vitis vinifera ssp. sylvestris, the ancestor of cultivated grapevine, was sought with respect to their output of stilbenes and potential use for resistance breeding. Considerable variation in stilbene inducibility was identified in V. vinifera ssp. sylvestris. Genotypic differences in abundance and profiles of stilbenes that are induced in response to a UV-C pulse are shown. Two clusters of stilbene 'chemovars' emerged: one cluster showed quick and strong accumulation of stilbenes, almost exclusively in the form of non-glycosylated resveratrol and viniferin, while the second cluster accumulated fewer stilbenes and relatively high proportions of piceatannol and the glycosylated piceid. For all 86 genotypes, a time dependence of the stilbene pattern was observed: piceid, resveratrol, and piceatannol accumulated earlier, whereas the viniferins were found later. It was further observed that the genotypic differences in stilbene accumulation were preceded by differential accumulation of the transcripts for chalcone synthase (CHS) and stilbene-related genes: phenylalanine ammonium lyase (PAL), stilbene synthase (StSy), and resveratrol synthase (RS). A screen of the population with respect to susceptibility to downy mildew of grapevine (Plasmopara viticola) revealed considerable variability. The subpopulation of genotypes with high stilbene inducibility was significantly less susceptible as compared with lowstilbene genotypes, and for representative genotypes it could be shown that the inducibility of stilbene synthase by UV correlated with the inducibility by the pathogen.
Basal immunity; breeding; defence; genetic diversity; grapevine (V; sylvestris); stilbenes; UV-C
Stilbenes are a small family of plant secondary metabolites
derived from the phenylpropanoid pathway, which are found
in a limited number of plant species (Langcake and Pryce,
1976; Kodan et al., 2001; Yu et al., 2005). In the Vitaceae,
stilbenes are important phytoalexins, which accumulate in
response to various biotic and abiotic stresses such as
pathogen attack (Langcake and Pryce, 1976; Adrian et al., 1997;
Schnee et al., 2008), UV-C irradiation (Bais et al., 2000),
application of chemicals such as aluminium ions and ozone
(Rosemann et al., 1991; Adrian et al., 1996), or salinity stress
(Ismail et al., 2012). They can also be induced in response
to plant hormones, such as jasmonates and ethylene (Belhadj
et al., 2008a, b; D’Onofrio et al., 2009). In grapevine, the
stilbene trans-resveratrol (trans-3,5,4’,-trihydroxy-trans-stilbene)
© The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology.
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has attracted particular attention, not only because of its
antimicrobial activity, but also due to its possible
pharmacological benefits to humans. The relatively low incidence of
coronary disease in France despite a diet rich in saturated
fatty acids (popularized as the ‘French Paradox’) has been
attributed to regular intake of resveratrol associated with
moderate consumption of red wine (Siemann and Creasy,
1992). Accumulating evidence indicates that this natural
product can prevent some diseases, such as cardiovascular
diseases, cancers, obesity, diabetes, and neurodegenerative
diseases, and in addition can cause an extension of life span
(for reviews, see Baur and Sinclair, 2006; Roupe et al., 2006).
In a previous work, it was shown for cell cultures from
Vitis rupestris and V. vinifera cv. ‘Pinot Noir’ that stilbene
patterns differ depending on the genotype (Qiao et al., 2010;
Chang et al., 2011; Chang and Nick, 2012). Cell lines derived
from two distinct genotypes showed different responses to
elicitation with flg22 or Harpin. Whereas most of the early
defence responses overlapped in both cell lines, they differed
in the induction of pathogenesis-related (PR) genes,
synthesis and metabolism of stilbene phytoalexins, and the
execution of hypersensitive response (HR)-mediated cell death.
In the resistant V. rupestris, resveratrol was oxidized to toxic
δ-viniferin, whereas in the susceptible cv. ‘Pinot Noir’, it was
preferentially accumulated in form of its non-toxic glucoside
piceid. This suggests that there is genetic variation within the
genus Vitis with respect to stilbene profiles and, since
bioactive stilbenes such as resveratrol or δ-viniferin harbour
antimicrobial activity, this genetic variation might be exploited
for sustainable viticulture.
Crop wild relatives (CWRs) have shifted into the centre
of the attention of plant breeding and evolutionary
biology (Ellstrand et al., 2010), because they represent valuable
genetic resources for breeding. The cultivated grape
V. vinifera L. ssp. vinifera has played an important role with respect
to economy and culture over many centuries. It represents one
of the most important crops worldwide considering its global
distribution and its high economic value. However, its
ancestor and CWR species, the European wild grape V. vinifera
L. ssp. sylvestris Hegi, is close to extinction. In the frame of a
project designed to conserve this species ex situ, an extensive
collection of the European wild grape (for simplicity termed
V. sylvestris) representing a complete copy of the genetic
variation still present in Germany has been established (Nick,
2012). A closer analysis of this collection revealed that many
genotypes show good tolerance against several grapevine
diseases, such as downy mildew (Plasmopara viticola),
powdery mildew (Erysiphe necator), and black rot (Guignardia
bidwelli), which were all introduced only 150 years ago from
North America (Tisch et al., 2014). Plant immunity is made
up of two levels: an evolutionarily ancient basal immunity
is complemented by a more efficient and specific second line
of defence. This specific immunity has evolved during a long
arms race between pathogen and host plant. Since cultivated
grapevine (V. vinifera ssp. vinifera) did not evolve together
with these recently introduced pathogens, it represents a naive
host and, in contrast to North American wild species of Vitis,
lacks the efficient second layer of innate immunity against
these diseases. The fact that some genotypes of V. sylvestris
can withstand these diseases is likely to be due to a more
efficient basal immunity.
Since phytoalexins, such as the stilbenes, represent a
central element of basal immunity, the aim of this work is to
characterize the diversity of this V. sylvestris collection with
respect to its capacity for stilbene biosynthesis, which might
be exploited as a genetic resource for resistance breeding.
Vitis sylvestris was therefore screened as the ancestral species
for genotypic differences in stilbene accumulation (stilbene
‘chemovars’). Since the response to pathogens is subject to
considerable variation and dependent on seasonal influences,
a short pulse of UV-C light was used as a well controllable
trigger. Using this approach, it is shown in the current study
that there is, in fact, considerable genetic variation in
V. sylvestris concerning stilbene output. A few V. vinifera cultivars
were included for reference. It is confirmed that different
stilbene patterns exist not only in cell lines, but also in the
‘real world’. In addition, V. sylvestris chemovars that produce
high levels of the bioactive viniferins are identified and it is
shown that these chemovars are less susceptible to infection
by downy mildew of grapevine (P. viticola).
Materials and methods
The Vitis vinifera ssp. sylvestris plants used in this study were
collected (as cuttings) from natural sites at the ‘Ketsch’ peninsula at
the Rhine River, in Southern Germany, which harbours the
largest natural population in Central Europe (these accessions are
indicated by ‘Ke’). Additionally, 25 V. sylvestris individuals
originating from different sites in the Upper Rhine Valley (from the
Hördt peninsula, indicated by ‘Hoe’) were included in this study;
details of the collection sites have been described (Ledesma-Krist
et al., 2014). Also included were six V. vinifera cultivars common in
German and French vineyards (Augster Weiss, Pinot Blanc, Pinot
Noir, Müller-Thurgau, Chardonnay, and Cabernet Sauvignon),
along with one American (V. rupestris), and one Chinese
(V. quinquangularis) species. All accessions are maintained as living
specimens in the grapevine collection of the Botanical Garden of the
Karlsruhe Institute of Technology, and have been
photographically documented, and re-determined using morphological keys
and ampelographic descriptors of the Organisation Internationale
de la Vigne et du Vin (Olmo, 1976). For stilbene analysis, leaves of
vineyard-grown plants were used over two subsequent years (2012
and 2013). For RNA extraction, the leaves were harvested from
greenhouse-grown plants cultivated at a temperature of 22 °C and
18 °C (day and night, respectively) and a photoperiod of 14 h light
and 10 h dark.
Preparation of leaf samples
To obtain fully expanded leaves of uniform size and comparable
developmental state, the fourth and fifth leaves, counted from the
apex, were excised from randomly selected individuals of the
respective genotype, subjected to UV-C stress as described below, and
incubated upside down on moist filter paper in large Petri dishes.
For the UV-C treatment, the abaxial surface of the entire leaf was
exposed to UV-C light (254 nm, 15 W, Germicidal, General Electric,
Japan) for 10 min at a distance of 12.5 cm. The leaves of the
different genotypes were harvested at different time points after the
treatment, immediately frozen in liquid nitrogen, and stored at –80 °C
until stilbene extraction and RNA analysis.
To test whether UV-C can induce stilbenes in a stable and reliable
manner, leaves of all accessions were collected at the indicated time
points: C (control fresh leaf, without UV-C treatment), 0 (just at the
end of the 10 min UV-C pulse), 3, 6, 24, 48, and 72 h, respectively,
immediately frozen in liquid nitrogen, and stored at –80 °C until
further analysis. The frozen tissue was ground in liquid nitrogen using
a pestle and mortar. A 300 mg aliquot of fresh weight of powdered
leaf tissue was mixed with 1 ml of 100% methanol and
homogenized for 10 min on a platform vortexer in order to maximize
uniform sampling and to ensure complete extraction of the stilbenes.
The homogenized samples were then centrifuged at 10 000 rpm for
10 min (Heraeus Biofuge Pico, Osterode, Germany). Before analysis,
the supernatant was filtered using a disposable syringe filter (pore
size, 0.2 μm; filter-Ø, 15mm; Macherey-Nagel, Düren, Germany).
All the experiments were performed under a green safelight (λmax
Stilbene analysis and quantification
For the initial experiments, the stilbenes extracted from V. rupestris
and V. quinquangularis were analysed using high-performance liquid
chromatography (HPLC; Agilent 1200 series, Waldbronn, Germany)
as described previously (Chang et al., 2011) with minor
modifications. To extend the analysis to the numerous cultivars of V.
sylvestris and V. vinifera, liquid chromatography–mass spectrometry
(LC-MS) analyses were performed at the metabolomics platform of
the Institut National de Recherche Agriculturel (INRA, Université
de Strasbourg, Colmar, France) after comparative studies with the
same samples had shown that the results between the methods were
identical. The analysis method was as follows. Acetonitrile and
formic acid of LC-MS grade were supplied by Thermo Fisher (San
Jose, CA, USA); water was provided by a Millipore water
purification system. Methanolic leaf extracts were analysed using a UHPLC
system (Dionex Ultimate 3000, Thermo Fisher Scientific) equipped
with a binary pump, an online degasser, a thermostated
autosampler, a thermostatically controlled column compartment, and a
diode array detector (DAD). Chromatographic separations were
performed on a Nucleodur C18 HTec column (50 × 2 mm, 1.8 μm
particle size; Macherey-Nagel) maintained at 20 °C. The mobile
phase consisted of acetonitrile/formic acid (0.1%, v/v) (eluent A)
and water/formic acid (0.1%, v/v) (eluent B) at a flow rate of 0.40ml
min–1. The gradient elution program was as follows: 0–1 min, 85%
B; 1–6 min, 85% to 5% B; 6–7 min, 5% to 85% B; and 7–8 min, 85%
B. The sample volume injected was 1 μl. The liquid
chromatography system was coupled to an Exactive Orbitrap mass spectrometer
(Thermo Fischer Scientific) equipped with an electrospray
ionization source operating in the negative mode. Parameters were set to
300 °C for ion transfer capillary temperature, and 2500 V for needle
voltage. Nebulization with nitrogen sheath gas and auxiliary gas was
maintained at 50 and 5 arbitrary units, respectively. The spectra were
acquired within the m/z mass range of 100–1000 atomic mass units
(amu), using a resolution of 50 000 at m/z 200 amu. The system was
calibrated externally using the Thermo Fischer calibration mixture
in the range of m/z 100–2000 amu, giving a mass accuracy better
than 2 ppm. Stilbenes were identified according to their mass
spectra, UV absorption spectra, and retention times, and compared with
those of authentic standards. The instruments were controlled using
the XCalibur software, and data were processed using the XCMS
software (Smith et al., 2006). Stilbene quantifications were based
on calibration curves obtained with the respective standards.
Transpiceid, trans-resveratrol, and trans-pterostilbene standards were
purchased from Sigma-Aldrich (L’Isle d’Abeau, France). (+)-ε-viniferin
and (+)-δ-viniferin standards were purchased from Polyphenols
Biotech (Villenave d’Ornon, France). Cis forms of stilbenes were
obtained by photoisomerization under UV light of trans-stilbene
standard solutions. Solutions containing 0, 5, 10, 25, 50, and 100 μg
–1ml of the standards were used for calibrations, with good linearity
(r2 >0.95). Three independent biological replicates from subsequent
seasons were conducted, and all analyses were repeated twice.
RNA extraction and cDNA synthesis
The leaves of Augster Weiss, Hoe29, Ke53, and Ke83 were harvested
at 0, 0.5, 1, 3, 6, and 24 h after irradiation, as were those of
For controlled inoculation with downy mildew (P. viticola), a
suspension of 40 000 sporangia ml–1 was used, as described in detail
below, when the screening is described. To circumvent potential
modulation of gene expression by a wounding response, this
experiment was not conducted with leaf discs, but with entire leaves. The
controlled inoculation leaves of Augster Weiss, Hoe29, and Ke83
were harvested at C (control fresh leaf), 120 h-C (control leaf
incubated in the absence of P. viticola under the same conditions), and
120 h-S (the leaf was infected with P. viticola suspension and
incubated for 120 h), respectively, immediately frozen in liquid nitrogen,
and stored at –80 °C until RNA extraction.
Total RNA was isolated using a Spectrum™ Plant Total RNA Kit
(Sigma, Deisenhofen) according to the manufacturer’s protocol. The
extracted RNA was transcribed into cDNA as described previously
(Ismail et al., 2012). The amount of RNA template was 1 μg.
Semi-quantitative reverse transcription–PCR (RT–PCR) was
performed following 30 cycles of 30 s denaturation at 94 °C, 30 s
annealing at 60 °C, and 1 min synthesis at 68 °C in a conventional PCR
cycler (Biometra, Göttingen, Germany) as described previously
(Qiao et al., 2010; Chang et al., 2011; Chang and Nick, 2012), using
the following primers and the detailed information in Supplementary
Table S3 available at JXB online: elongation factor-1α (EF1-α)
(sense, 5′–3′ TGTCATGTTGTGTCGTGTCCT; antisense, 5′–3′
CCAAAATATCCGGAGTAAAAGA); phenylalanine ammonium
lyase (PAL) (sense, 5′–3′ TGCTGACTGGTGAAAAGGTG;
antisense, 5′–3′ CGTTCCAAGCACTGAGACAA); resveratrol synthase
(RS) (sense, 5′–3′ TGGAAGCAACTAGGCATGTG; antisense,
5′–3′ GTGGCTTTTTCCCCCTTTAG); stilbene synthase (StSy)
(sense, 5′–3′ CCCAATGTGCCCACTTTAAT; antisense, 5’–3’
CTGGGTGAGCAATCCAAAAT); and chalcone synthase (CHS)
(sense, 5′–3′ GGTGCTCCACAGTGTGTCTACT; antisense, 5′–3′
TACCAACAAGAGAAGGGGAAAA). The PCR was performed
with Taq polymerase from New England Biolabs (NEB, Frankfurt,
Germany) and ThermoPol buffer (NEB). The PCR products were
separated as described previously (Ismail et al., 2012).
Quantitative real-time PCR
Quantitative real-time PCR was performed as described (Svyatyna
et al., 2014). To compare the mRNA expression level among
different samples, the Ct values from each sample were normalized to the
value for EF1-α as internal standard obtained from the same sample.
This internal standard is widely used in studies on stilbenes due to its
stability and reliability (Reid et al., 2006; Polesani et al., 2008) and
was also found to be very stable in previous work under different
biotic and abiotic stress conditions (Qiao et al., 2010; Chang et al.,
2011; Chang and Nick, 2012; Ismail et al., 2012). Since actin, which
is often used as a housekeeping reference, did not show any
deviations from EF1-α (Gong and Nick, unpublished), it was decided to
calibrate expression data on this internal standard. For each
triplicate, these normalized Ct values were averaged. The difference
between the Ct values of the target gene X and those for the EF1-α
reference R were calculated as follows: ∆C t (X)=Ct (X)–Ct (R). The
final result was expressed as 2–∆Ct (X) .
Principal component analysis and statistical evaluation of
metabolomic and genetic data
Principal component analysis (PCA) was performed using the
princomp command functioning under R (R Core Team, 2013)
using the following argument (cor=T, scores=T). The
contribution of the stilbenes to the construction of the axis of the PCA
was obtained using R software and the methodology described
at http://www.R-project.org/. To infer phylogenetic relationships,
DNA was extracted from leaf tissue by a slightly modified
cetyltrimethylammonium bromide (CTAB) method (Doyle and Doyle,
1987) using ~25 mg of leaf tissue shock-frozen in liquid nitrogen
and homogenized. Samples were genotyped at nine
microsatellite loci located on different chromosomes (http://www.genres.
de/eccdb/vitis/) using the simple sequence repeat (SSR) markers
VVS2 (Thomas and Scott, 1993), VVMD07 (Bowers et al., 1996),
VVMD25, VVMD27, VVMD28, VVMD32 (Bowers et al., 1999),
VrZag62, and VrZag79 (Sefc et al., 1999); the phylogenetic
relationship was inferred using the UPGMA method (Sneath and
Sokal, 1973) using the software MEGA4 (Tamura et al., 2007)
with default settings.
Screening V. sylvestris for susceptibility to downy mildew
To screen differences in the susceptibility of the European wild
grape (V. sylvestris) accession to downy mildew (P. viticola), at least
seven leaf discs taken from the fourth to fifth fully expanded leaf
of each genotype cultivated in the greenhouse were transferred in
a randomized manner to Petri dishes containing 5 ml of sterile tap
water, inoculated with one droplet of a spore suspension (30 μl
for each leaf disc, 40 000 sporangia ml–1), which was removed
24 h post-inoculation, and incubated in a climate chamber at high
humidity and 21 °C (day–night cycle 12 h:12 h). Sporulation was
first evaluated visually according to Kortekamp (2006) and Genet
et al. (1997) at 7 days post-inoculation (dpi). In addition,
production of spores was scored: each leaf disc was transferred to a 1.5 ml
tube and complemented with 1 ml of 0.1% (v/v) Tween-80 in
distilled water. The tube was vigorously shaken (Vortex) to achieve a
homogenous suspension, and the concentration of sporangia was
determined using a haematocytometer (Fuchs-Rosenthal). The
data are means obtained from at least two different years. For all
experiments, an isolate was used that is routinely maintained on
Müller-Thurgau in the greenhouse of the State Education and
Research Center Rheinpfalz.
Determination of stomatal density
To evaluate stomatal density, glue imprints of fully expanded
healthy fresh leaves, harvested from plants grown in the
greenhouse of the Botanical Garden of the KIT, were used. Glue
imprints were obtained using the lower, abaxial, leaf surfaces
of four different leaves of each accession as template. A drop of
glue (UHU Hart Modellbaukleber 45510, UHU GmbH & Co.
KG, Bühl, Germany) was placed on the respective leaf region
near the leaf base. To allow for high-quality imaging, intercostal
fields with a sufficiently planar surface were used in the region
between the midrib and lateral vein, and covered by a thin and
homogenous layer, distributing the glue with the finger tip. After
5–10 min, the glue has cured to a thin film, conserving an imprint
of the leaf surface. This imprint could then be removed using a
pair of tweezers and placed on an object slide in a drop of
distilled water. Grey-scale microscopic images were collected from
these glue imprints with differential interference contrast (DIC)
using a digital imaging system (Zeiss Axio Scope, equipped with
a CCD-camera AxioCam). Pictures were recorded at ×20
magnification with 2720× 2048 pixels and saved as RGB colour tif files
for evaluation with ImageJ. All stomata and epidermal cells on the
picture were quantified using the plugin Analyze–Cell Counter.
Stomatal density was defined as the ratio of the stomata of one
picture per epidermal cells of the same picture, a parameter that
was found to be independent of leaf expansion, leaf
differentiation, and year (Supplementary Table S4 at JXB online). Between
200 and 600 stomata were scored along with epidermal pavement
cells to determine the stomatal density. Values represent medians
from four independent samples collected over two subsequent
Stilbene accumulation can be triggered by UV-C
In order to compare stilbene inducibility in different
genotypes, a trigger is required that is easy to standardize and can
be applied to leaf tissue in a reliable manner. From
preliminary studies testing different candidate triggers such as methyl
jasmonate or inoculation with P. viticola, a short pulse of
UV-C (10 min) was found to produce the most reliable results
(Douillet-Breuil et al., 1999). The accumulation of
trans-resveratrol was first followed over time in response to this UV-C
pulse in representative genotypes using HPLC (Fig. 1A). As
representative examples, the data are shown for two wild
nonvinifera species (V. rupestris, a North American wild grape,
and V. quinquangularis, a Chinese wild grape), two V. vinifera
cultivars (‘Müller Thurgau’, a cultivar commonly grown in
the Upper Rhine Region, and ‘Augster Weiss’, a male-sterile
ancient variety, which is used for breeding), as well as two
V. sylvestris genotypes, Hoe29 and Ke53, falling into
different subclades of V. sylvestris. Prior to the treatment (control),
and immediately after the pulse (defined as 0h), the content
of trans-resveratrol was below the detection limit in all
genotypes. The abundance of trans-resveratrol increased from 3 h
after UV-C irradiation, reaching a maximum from 24 h to
48 h, followed by a decline till 72 h. However, the amplitude
of the response differed strongly between genotypes,
indicating that the accumulation was genotype dependent. For
instance, around three times more resveratrol accumulated in
V. rupestris compared with V. quinquangularis, whereas
cultivar Müller-Thurgau accumulated more than cultivar Augster
Weiss. However, these differences were minor compared with
the strong accumulation found in the two V. sylvestris
genotypes Hoe29 and Ke53. To compare stilbene accumulation
between different genotypes, control, 0, 6, and 24 h were used
as representative time points in the following experiments.
To visualize not only genotypic differences in the total
abundance of stilbenes but possibly differences in stilbene
profiles, the levels of trans-piceid, cis-piceid,
trans-resveratrol, cis-resveratrol, ε-viniferin, δ-viniferin, pterostilbene,
trans-piceatannol, and cis-piceatannol were quantified in
parallel for the different time points using LC-MS. As shown
for a selection of representative genotypes in Fig. 1B and C,
there was a large genotypic variation in stilbene inducibility.
Whereas UV-C induced a quick and strong accumulation
of stilbenes in the genotypes Pinot Blanc, Ke53, Ke83, and
Hoe29 (Fig. 1B), the same treatment produced hardly any
accumulation in the genotypes Augster Weiss, Ke89, Ke51,
and Ke78 (Fig. 1C), even at 24 h. Combined analysis of all
86 genotypes (Fig. 2) showed that accumulation of piceid,
resveratrol, and piceatannol was observed already 6 h after
UV-C exposure, whereas viniferins accumulated later and
were mostly detected 24 h after exposure. This time
dependence in the stilbene pattern is shown in Fig. 1B for Pinot
Blanc, Ke53, Ke83, and Hoe29. Here, the total stilbene
content increased significantly from 6h, which could be mainly
attributed to the accumulation of trans-resveratrol, whereas
at 24 h, resveratrol was complemented by viniferins. For
Fig. 1. Time courses of stilbene accumulation in different genotypes
in response to UV-C. (A) Time courses for the accumulation of
transresveratrol in V. rupestris, V. quinquangularis, Müller Thurgau, Augster
Weiss, Ke53, and Hoe29. Representative time courses for strong stilbene
accumulation in Pinot Blanc, Ke53, Ke83, and Hoe29 (B), and weak
accumulation in Augster Weiss, Ke89, Ke51, and Ke78 (C). Data represent
mean values and standard errors from three independent biological
example, in Ke53, 234 μg g–1 fresh weight (FW) of resveratrol
was measured at 6 h, with only low levels of viniferin (7 μg g–1
FW). In contrast, at 24 h, although the content of resveratrol
had significantly increased, by >3-fold, to 818 μg g–1 FW,
during the same time viniferin had increased even more, by
>40fold (333 μg g–1 FW). The total stilbene content was therefore
1230 μg g–1 FW and exceeded the UV-C-induced stilbene
accumulation in genotypes such as Ke89 by >25 times (e.g.
even at 24 h, the total stilbene content in Ke89 reached only
49 μg g–1 FW).
Genetic variation of stilbene accumulation
In order to evaluate the extent of the genetic variation in
defence metabolism present in V. sylvestris, stilbene
accumulation was followed in 86 genotypes over time in response
to UV-C. As shown in Fig. 2A–E, all analysed stilbenes
(cis- and trans-piceid, cis- and trans-resveratrol, viniferins,
pterostilbene, and cis- and trans-piceatannol) accumulated
significantly with increasing time. For piceid, resveratrol, and
piceatannol, the increases were observed at early stages (from
6 h after UV-C exposure). In contrast, the accumulation of the
downstream derivatives viniferins and pterostilbene occurred
later: at 6 h, these two stilbene species were still not
detectable, but had substantially increased at 24 h. In all genotypes,
resveratrol and viniferins were the predominant stilbenes, and
the abundance of viniferins and resveratrol was tightly
correlated (the correlations between different types of stilbenes
are given in Supplementary Fig. S1 and Supplementary Table
S1 at JXB online).
In the frame of these general patterns, there was
considerable variation as represented by the width of the boxplot
bars and the position of the outliers. In some genotypes, such
as Pinot Noir, Pinot Blanc, Ke15, Ke20, Ke22, Ke28c, Ke39,
Ke53, Ke83, Ke84, Ke95, Ke96, Ke99, Ke103, Hoe17, and
Hoe29, much more resveratrol was produced than in the bulk
of the populations (Fig. 2B, see the dots on the top of the
boxplot at 24 h); among those, Ke28c, Ke39, Ke53, Ke84,
and Hoe29 also accumulated much more viniferins compared
with the bulk of the population (Fig. 2C, see the dots on the
top of the boxplot at 24 h).
Two types of stilbene ‘chemovars’
To understand the factors underlying stilbene variation in
V. sylvestris (also in relation to some cultivars common in the
Upper Rhine Valley and the two non-vinifera species from
North America and China), the metabolomics data of all 86
genotypes for all time points were subjected to a PCA. As
shown in Fig. 3A, the first two principal components could
explain 77.4% of the variation between the samples (the
contribution of each individual stilbene species to these two
principal components is given in Supplementary Table S2 at JXB
online). Hereby, the amount of stilbenes (Comp. 1) accounted
for 52.9% of the variation between the samples, which means
that the variation present at 24 h could be mainly attributed
to the overall content of stilbenes. In contrast to this
quantitative trait, Comp. 2 was rather qualitative and based on the
composition of the accumulating stilbenes. This explained
24.5% of the variation.
From the PCA at t=24 h, two clusters of genotypes
emerged, which differed in both quantitative and
qualitative parameters. The first (smaller) cluster is characterized
by the strong ability to accumulate stilbenes, especially in the
form of resveratrol and viniferins (Fig. 3A, blue circles). This
cluster comprises Pinot Noir, Pinot Blanc, Ke15, Ke20, Ke22,
Ke28c, Ke39, Ke53, Ke83, Ke84, Ke95, Ke96, Ke99, Ke103,
Hoe17, and Hoe29. The second (larger) cluster comprises
genotypes accumulating fewer stilbenes, which a relatively
high proportion of piceid and piceatannol.
To illustrate the conclusions from the PCA analysis that
the genotypes cluster with respect to the stilbene profile,
two representative genotypes arbitrarily selected from each
cluster are shown in Fig. 3B. Pinot Blanc and Ke53 belong
to the blue (high-stilbene type) cluster, whereas Augster
Weiss and Ke89 were chosen from the green (low-stilbene
type) cluster. In the controls, the overall abundance of
stilbenes was low (represented by the small size of the pie).
Those stilbenes that can be detected are almost exclusively
present as piceid—the glycosylated form of resveratrol
(Fig. 3B). In response to the UV-C pulse, all genotypes
accumulated the stilbene species resveratrol and its
oxidized form, the viniferins. However, the genotypes from the
green (low-stilbene type) cluster (Augster Weiss and Ke89)
also accumulated some piceid and piceatannol, which at
24 h accounted for ~50–60% of total stilbenes, whereas in
genotypes from the blue (high-stilbene type) cluster (Pinot
Blanc and Ke53), piceid and piceatannol remained below
7%. When this difference between ‘blue’ and ‘green’
genotypes was tested statistically (Supplementary Figs S2, S3 at
JXB online), the genotypes from the blue cluster were found
to contain significantly more resveratrol and viniferin
compared with those from the green cluster. In contrast, the
green cluster contained a significantly higher piceatannol/
total stilbene ratio.
These data show that there exist two stilbene ‘chemovars’
in V. sylvestris. The chemovars of the ‘blue’ cluster
accumulate high levels of stilbenes in non-glycosylated form, whereas
the chemovars of the ‘green’ cluster accumulate low levels
of stilbenes, with a relatively high proportion of piceid and
Strong stilbene inducibility is distributed in specific
clades of V. sylvestris
The genetic differences in stilbene inducibility represent an
interesting genetic resource for resistance breeding. It was
therefore decided to determine whether the genotypes of the
‘blue’ (high-stilbene type) cluster (Fig. 3A) are equally
distributed over all genotypes from the Ketsch peninsula, or
whether they are concentrated on specific clades. The
phylogenetic relationship between these genotypes was inferred
from microsatellite genotyping and integrated with published
data for those microsatellites to comprise a set of 361 taxa
of European V. sylvestris and V. vinifera, and non-European
Vitis for these nine SSR markers (Fig. 4; Ledesma-Krist
et al., 2014). These markers had been selected from the
literature, because they are the most informative to resolve
relationships in V. sylvestris. The topology of the tree was tested
by Bayesian clustering, and found to remain very robust after
including the first six markers (S. Schröder et al., unpublished
results). The accessions from the Ketsch peninsula formed a
separate cluster together with V. sylvestris from the Upper
Danube Valley and V. vinifera cultivars current in German
vineyards, whereas the V. sylvestris accessions from Spain, the
Rhône valley, and South East Europe formed a separate
cluster, and the non-vinifera accessions established a third cluster.
When those genotypes that had been analysed with respect to
their stilbene inducibility were mapped on this tree, the
genotypes of the ‘blue’ (high-stilbene type) cluster were found to
be distributed non-homogenously. For instance, among the
Fig. 4. Genetic relationships for stilbene-inducible genotypes of
V. sylvestris. The incidence of genotypes from the green (piceid-rich
chemovars) and the blue (viniferin-rich chemovars) clusters (as defined in
Fig. 3A) were plotted into an UPGMA tree over nine SSR markers for 361
taxa of European V. sylvestris and V. vinifera, and American non-vinifera.
The tree is drawn to scale, with branch lengths in the same units as those
of the evolutionary distances used to infer the phylogenetic tree. 1,
noninifera genotypes; 2, V. sylvestris genotypes from outside Central Europe;
3, German–Austrian V. sylvertris. (This figure is available in colour at JXB
15 genotypes where both data sets (SSR markers and stilbene
profiles) had been established, only four were found in
subcluster 3A, whereas 11 were found in subcluster 3B; within
subcluster 3B, five clustered into the right-most branch of
Piceid does not serve as a precursor for the
biosynthesis of non-glycosylated stilbenes
Some genotypes accumulate relatively high levels of piceid
(Fig. 2A, see the dots on the top of the xplots). The
glycosylation of piceid protects against oxidation into oxidative
dimers, such as viniferins and, therefore, piceid has been
proposed to act as the storage form for bioactive resveratrol
and viniferins (Regev-Shoshani et al., 2003). It was
therefore asked whether piceid might function as a precursor for
later release of resveratrol. To illustrate this as an illustration
for the UV-C response, the two strong piceid accumulators,
Ke28c and Ke10, were selected because these genotypes show
comparable resting levels of piceid and resveratrol/viniferin.
Both genotypes showed high basal levels of piceid
compared with other genotypes (Fig. 2A). If these high basal
levels of piceid were a storage form to produce the bioactive,
non-glycosylated, stilbenes, Ke28c and Ke10 should show
elevated induction of non-glycosylated stilbenes. However, when
they were exposed to UV-C, these two genotypes produced
completely different results with respect to stilbene
accumulation. Although almost the same amounts of piceid (Fig. 5A)
Fig. 5. Variation in stilbene inducibility of piceid accumulators. Amounts of
piceid (A) and non-glycosylated stilbenes (B) under control conditions and
24 h after a UV-C pulse in Ke28c and Ke10. Data represent mean values
and standard error from three independent replicates.
and total stilbenes (Fig. 5B) were measured in the controls, in
Ke10, while showing only slightly increased levels of piceid,
around >20 times more non-glycosylated stilbenes were
induced as compared with the basal level. In contrast, Ke28c
accumulated, upon UV-C induction, >3 times the amount of
piceid as compared with Ke10, but >6 times the amount of
non-glycosylated stilbenes as compared with Ke10.
Therefore, it can be concluded that some of the genotypes
with higher basal levels of pre-formed piceid also produce
more stilbenes upon induction, but some do not. Even in Ke10,
the level of non-glycosylated stilbenes found at 24 h exceed
the resting level of piceid by >20-fold, which means that the
vast majority of induced bioactive stilbenes must be
synthesized de novo rather than being released from a glycosylated
precursor. For the genotypes of the blue cluster, the high
levels of resveratrol (Fig. 2B, the dots on the top of the boxplot
at 24 h) that, in the case of Ke39, Ke53, Ke84, and Hoe29,
are accompanied by high amounts of viniferins (Fig. 2C, the
dots on the top of the boxplot at 24 h) all show only very low
resting levels of piceid in control conditions. This means that
these genotypes produce their strong induction of stilbenes
completely through de novo synthesis. Release of resveratrol
from pre-formed piceid does not play any role in this
induction. To follow the metabolic flow through stilbene formation
directly, pulse labelling with radioactive precursors (such as
phenylalanine) might be a strategy.
Response of stilbene-related genes to UV-C
To investigate whether the observed genotypic differences in
stilbene accumulation can be correlated with a
corresponding transcriptional response, the transcript level of key genes
was followed in representative genotypes by semi-quantitative
RT–PCR and quantitative real-time PCR. As shown by the
simplified stilbene biosynthetic pathway in Fig. 6A, the
general activation of the phenylpropanoid pathway was
monitored by probing PAL, the stilbene branch of the pathway by
probing for StSy and RS, and the competing flavonoid branch
via CHS. EF1-α was used as an internal standard. It should
be kept in mind that the stilbene synthase family in grapevine
is extremely expanded, with numerous members that are very
similar, often even identical in their open reading frames, but
differ with respect to their promotors (for reviews, see Parage
et al., 2012; Vannozzi et al., 2012). The transcripts picked
up by the StSy and RS oligonucleotide primers are therefore
likely to stem from different members of this family, and differ
partially in their expression patterns (e.g. Qiao et al. 2010). In
the following, the operational denominators ‘StSy’ and ‘RS’
will be used. As strong stilbene accumulators, Hoe29, Ke53,
and Ke83 were chosen as representative of three different
phylogenetic clades of V. sylvestris (Fig. 4), whereas Augster Weiss
(an ancient cultivar, which is male sterile and therefore often
used for molecular breeding) was selected as a representative
for the weakly accumulating genotypes.
As shown in Fig. 6B, hardly any transcripts could be
detected for the controls and the time point just at the end of
the 10 min UV-C pulse, irrespective of the genotype,
indicating that the basal steady-state levels of these genes are very
low. In all strong stilbene accumulators, PAL transcripts were
found to be induced already 30 min after the pulse treatment,
whereas in Augster Weiss, the induction of PAL transcripts
was delayed by 30 min and did not reach the same
amplitude. The induction of PAL transcripts was accompanied by
almost simultaneous induction of StSy transcripts, whereas
RS transcripts followed 1–2 h later. Again, the response in
Augster Weiss was delayed and less pronounced as
compared with the strong stilbene accumulators. Interestingly,
for Hoe29 and Ke83, the induction of StSy did not differ
from Augster Weiss, indicating that different stilbene
synthase genes can differ in their regulatory pattern (Fig. 6E).
Although in these strong stilbene accumulators PAL
transcripts as well as StSy transcripts were induced rapidly, the
induction of CHS as a key step for the flavonoid pathway
remained transient and was shut off between 30 min and
60 min after the UV-C pulse.
These patterns were then verified by quantitative real-time
PCR in the same genotypes. For RS transcripts (Fig. 6C), no
significant transcript accumulations can be detected under
control conditions for any of the tested genotypes. However,
already as early as 0.5 h, these transcripts had been clearly
induced, with the response of Hoe29, Ke53, and Ke83 being
stronger than that of Augster Weiss, and this difference had
magnified to an almost 2-fold difference at 6h, when the
induction in Ke53 is compared with Augster Weiss.
The basal levels for CHS transcripts (Fig. 6D) were higher
in Augster Weiss and Ke83 compared with Hoe29 and
Ke53. Irrespective of this initial difference, transcript levels
increased transiently for 0.5 h in all genotypes, but this
transient increase became significant only in th ecase of Ke53. In
all genotypes, the transcript levels had dropped back at 6 h,
for Hoe29, Ke53, and Ke83 even to a level lower than in the
control. In the case of Ke53, the transcripts almost vanished.
The pattern for StSy induction (Fig. 6E) resembled that for
RS transcripts (Fig. 6C), but here the induction was already
quite pronounced at 0.5 h. Again, the StSy transcripts
increased more strongly and more rapidly in Ke53 than in
Augster Weiss. At 6 h, this difference had expanded to a level
where the expression of StSy in Ke53 was nearly 2-fold that
observed in Augster Weiss.
Expression of StSy, RS, and CHS genes in response to
In the previous experiments, genetic differences were found in
the inducibility of stilbene that were accompanied by
differences in the expression of stilbene synthase genes using UV-C
as the trigger. Since the motivation of this work was related
to defence, it was important to clarify whether the observed
induction by UV-C correlated with an induction by downy
mildew. For this purpose, the transcript levels of StSy, RS,
and CHS were investigated by quantitative real-time PCR in
three representative genotypes: Augster Weiss (a cultivated
variety with weak stilbene induction in response to UV), and
the two V. sylvestris genotypes Hoe29 and Ke83 that showed
a strong stilbene response to UV.
For RS transcripts (Fig. 7A), for all three genotypes, no
significant transcript accumulation was detected either in the
freshly excised leaf (C) or in leaves that had been incubated
for 5^d (120 h-C) without inoculation. However, 5 dpi with
downy mildew, the expression of RS in Hoe29 was strongly
induced (by 131-fold compared with the control). This
response was >14-fold greater compared with Augster Weiss;
in Ke83, this induction was still nearly 6-fold higher than in
The pattern of StSy (Fig. 7B) was similar to that for RS
(Fig. 7A); here the expression of StSy in Hoe29 was 70-fold
greater compared with the control and >15-fold greater
compared with Augster Weiss, and in Ke83 was nearly 5-fold
greater that observed in Augster Weiss.
In contrast, the abundance of CHS transcripts (Fig. 7C),
irrespective of the initial difference, decreased compared
with the C and 120 h-C for all genotypes. This was most
pronounced in Hoe29 and in Ke83, where CHS transcripts were
more abundant under control conditions. For Augster Weiss,
the control levels were lower and thus the decrease was less
prominent. Thus, the response CHS transcripts represented
a mirror image of the situation observed for RS and StSy.
Susceptibility to downy mildew is inversely correlated
with stilbene inducibility
For the tested representative genotypes, the responses of RS,
StSy, and CHS to inoculation with downy mildew (Fig. 7)
correlated with the response of these transcripts to UV-C
(Fig. 6). Therefore, a potential correlation between stilbene
inducibility by UV-C and the susceptibility to infection by
downy mildew in the population was investigated.
Plasmopara viticola infects through the stomata, and
differences in stomatal density might therefore contribute to
variations of infection success. Therefore, the wild V. vinifera ssp.
sylvestris Ketsch population was screened for stomatal
density. Preliminary studies had shown that the relative incidence
of stomata over the entire population of epidermal cells was
a more reliable marker than absolute density (as stomata per
area), because this relative value excludes variations caused
by differences in cell expansion due to environmental
fluctuations (Supplementary Table S4 at JXB online). In fact, the
values for this relative stomatal density were found to be very
stable over two vegetation periods, independent of lighting
conditions, and dependent on the genotype.
The entire population was now split into a (larger, n=59)
subset where stilbene contents were lower than average and
a (smaller, n=20) subset where stilbene contents were higher
than average. As a reference, the total abundance of
resveratrol and viniferins at 24 h after induction was used. When the
concentration of sporangia was scored as readout for
susceptibility and plotted over these stilbene subsets (Fig. 8A, upper
row), there was no significant difference of infections if
transresveratrol and viniferin were considered alone. Since
resveratrol can also be oxidized to viniferins non-enzymatically
during transport and storage of samples, the correlation of
infection with the sum of resveratrol and viniferins was being
analysed because this value should be more robust against
experimental fluctuations. Here, it was found that the subset
of high-stilbene producers had significantly fewer infections
compared with the subset of low-stilbene producers. The
significance of this finding is at the 99% level.
Since genotypes with a low stomatal density are expected
to suffer fewer penetration events, the population was also
grouped into two subsets with respect to stomatal density,
irrespective of stilbene inducibility (Fig. 8B), and it was
found that there was a significantly reduced infection in the
group with low stomatal density compared with the average
of the entire population and with the high stomatal density
group (significance is at the 99% level). No correlation was
seen between stomatal density and stilbene inducibility; both
traits seemed to be completely uncoupled.
Since the inverse correlation between stilbene levels and
infection success was obscured by the fact that genotypes with
low stomatal density are less infected even when they perform
poorly with respect to stilbene induction, the correlation
between infection and stilbene levels was tested separately for
those genotypes with high stomatal density (Fig. 8A, middle
row) and low stomatal density (Fig. 8A, lower row). Within
this subset (Fig. 8A, middle row), the reduction of
susceptibility in the high-stilbene producers was even more pronounced.
These data show that both high stilbene inducibility and
low stomatal density confer a reduced susceptibility to downy
mildew in the V. sylvestris population. For high stomatal
density, the stilbene content is clearly limiting for infection
success, whereas for low stomatal density, the infection success is
mostly independent of stilbene content.
Stilbenes, as important phytoalexins, are a central factor for
basal immunity of grapevine. In the current study, potential
genetic variation in V. sylvestris, the ancestor of cultivated
grapevine, was probed for with respect to stilbene
biosynthetic capacities, for potential use for resistance breeding.
Genotypic differences in abundance and profiles of the
stilbenes induced in response to a UV-C pulse were shown. Two
clusters of genotypes emerged: one cluster with quick and
strong accumulation of stilbenes, almost exclusively in the
form of the non-glycosylated resveratrol and viniferins, and
Fig. 7. Response of key transcripts of the phenylpropanoid pathway to infection with downy mildew. (A–C) Quantification of transcripts of resveratrol
synthase (RS), stilbene synthase (StSy), and chalcone synthase (CHS) by quantitative real-time PCR normalized to the expression of elongation factor
EF1-α. * and ** indicate differences that are statistically significant at the P <0.05 and P <0.01 level, respectively. Data represent mean values from three
independent experimental series; error bars represent standard errors.
the second cluster which accumulated fewer stilbenes and
a relatively high proportion of piceatannol and the
glycosylated piceid. For all 86 genotypes, a time dependence of
the stilbene pattern was observed: piceid, resveratrol, and
piceatannol accumulated earlier, whereas the viniferins were
found later, consistent with a mode of action where
resveratrol acts as a precursor for the viniferins. It was further
observed that the genotypic differences in stilbene
accumulation were preceded by differential accumulation of the
transcripts for PAL, StSy, RS, and CHS. Taken together, these
observations provide evidence for stilbene ‘chemovars’ in
V. sylvestris (and possibly also in the few vinifera cultivars
tested in this study) that differ with respect to the induction
of bioactive viniferins correlated with a difference in the
inducibility of stilbene synthase.
On what level is stilbene accumulation controlled?
In the present study, the genotypes from the ‘blue’
(high-stilbene type) cluster (Fig. 3A), such as Pinot Noir, Pinot Blanc,
Ke15, Ke20, Ke22, Ke39, Ke53, Ke83, Ke84, Ke95, Ke96,
Ke99, Ke103, Hoe17, and Hoe29, accumulate high levels of
stilbenes in response to a UV-C pulse (Fig. 2B, C, the dots
on the top of the boxplot at 24 h), but all show only very low
basal levels of stilbenes in control conditions. This means that
these genotypes produce their strong induction of stilbenes
completely through de novo synthesis.
Since stilbenes are derived from the phenylpropanoid
pathway (Fig. 6A), the general activation of this pathway was
monitored by probing for PAL. During evolution, the stilbene
branch of the pathway has branched from flavonoid
biosynthesis by duplication of the gene encoding CHS followed
by mutation in the active centre, giving rise to StSy/RS
(Tropf et al., 1994). These enzymes triggering the competing
branches of stilbene versus flavonoid biosynthesis are very
similar, with only one amino acid difference in the active
centre, and the substrate of StSy/RS is also used by CHS, such
that both pathways compete for the same precursor. As shown
for representative genotypes in Fig. 6B, in all strong stilbene
accumulators tested, the induction of PAL transcripts was
accompanied by an almost simultaneous induction of StSy
transcripts, whereas RS transcripts followed 1–2 h later. In
contrast, this response was delayed in Augster Weiss and
was less pronounced as compared with the strong stilbene
accumulators. This indicates that the genotypic differences
in the accumulation of stilbenes (Fig. 6) are correlated with
the induction of PAL transcription as a key regulator of the
entire phenylpropanoid pathway. Interestingly, in these strong
stilbene accumulators, CHS, encoding the key enzyme for the
flavonoid pathway, although initially also slightly induced by
UV-C, was subsequently down-regulated. This indicates that
the phenylpropanoid pathway is, upon activation by UV-C,
channelled towards the synthesis of stilbenes, whereas the
flavonoid pathway, although initially activated, is rapidly shut
down. This might be linked with differential recruitment of
MYB transcription factors to the CHS and StSy promotors
(Höll et al., 2013).
Although there is a clear correlation between differential
activation of StSy transcription and the accumulation of
stilbenes, it is also clear that the differential induction of StSy
transcripts (not exceeding a factor of 2–3) cannot account for
the much larger differences in the induction of stilbenes (up
to a factor of 20). This indicates that transcriptional
regulation must be complemented by (still unknown)
post-transcriptional mechanisms consistent with findings from elicited
grapevine cell lines, where activation of basal immunity by the
PAMP flg22 produced a strong accumulation of StSy
transcripts that was not followed by accumulation of stilbenes
(Chang and Nick, 2012). In contrast, the bacterial elicitor
Harpin, triggering a cell death-related version of immunity,
induced StSy transcripts to a similar level, but in addition
caused a strong accumulation of stilbenes. An important role
for post-transcriptional regulation is also suggested by the
fact that a cell culture of Pinot Noir, a genotype belonging
to the high-stilbene-type cluster, upon induction of defence
preferentially produces the glycosylated piceid (Chang et al.,
2011), indicating that epigenetic mechanisms modulate the
Is stilbene inducibility by UV-C a predictor for the
response to downy mildew?
To analyse stilbene inducibility on a comparative scale, a
pulse of UV-C was used as a reliable and standardized input.
However, the motivation for the current study was to explore
the potential of V. sylvestris as a genetic resource for resistance
breeding. This required probing for potential correlations
between the UV-C response and the response to a pathogen,
such as downy mildew. This correlation is supported by two
lines of evidence. (i) The patterns for the induction of stilbene
synthesis transcripts (RS, StSy) along with the competing
flavonoid pathway (probed by CHS) are highly congruent,
irrespective of whether UV-C or inoculation with P. viticola are
used as the trigger. (ii) Those genotypes that produce high
levels of stilbenes in response to UV-C are also found to be
significantly less susceptible to infection with downy mildew
as compared with those genotypes with low UV
inducibility of stilbenes. This correlation becomes even tighter when
genotypes with high stomatal density are considered. Thus,
the inducibility of stilbene synthesis by a UV-C pulse can be
used as a predictor for (partial) resistance to infection with
Outlook: potential for sustainable viticulture
In grapevine, stilbenes are central to the defence response,
with resveratrol in particular effectively preventing pathogen
attack (Adrian et al., 1997; Jeandet et al., 2002). Resveratrol
is complemented by other metabolic compounds, which
harbour efficient antimicrobial activities and are also induced in
grapevine as a result of infection or stress (Langcake, 1981;
Pezet et al., 2004). Among all stilbenes, oxidized resveratrol
oligomers, so-called viniferins, are even more toxic than
resveratrol itself and have been shown to inhibit zoospore
mobility of P. viticola. In contrast, piceid—the glycosylated form of
resveratrol—shows no or little toxicity and no antimicrobial
activity (Celimene et al., 2001; Pezet et al., 2004). Although
stilbenes were induced in all 86 genotypes in response to the
UV-C pulse, the genotypes from the blue cluster (Fig. 3A)
differed from those of the green cluster not only in
accumulating higher levels of stilbenes, but also in producing the
non-glycosylated bioactive stilbenes resveratrol and viniferin.
The performance of the V. sylvestris genotypes after
inoculation with different grapevine pathogens such as P. viticola,
E. necator, or G. bidwellii are currently being explored and
statistically significant correlations have been found between
stilbene accumulation and suppression of disease symptoms.
The fact that it is possible to induce stilbene accumulation
via an abiotic stress factor (a pulse of UV light) opens up the
interesting possibility that immunity might be stimulated by
appropriate pre-treatments with abiotic factors. The
induction of tolerance to a certain type of stress by a controlled
induction of a different stress pathway is termed ‘stress
priming’ and has attracted considerable attention in the context of
improving agronomical performance under adverse conditions
(Beckers and Conrath, 2007). The present study demonstrates
that genetic factors enabling strong stilbene inducibility are still
present in V. sylvestris, and might be reintroduced into
cultivated grapes. Since viticulture is not targeted to provide staple
food, but a high-quality, high-priced product, quality has clear
priority over bulk production. The expected (slight, because
inducible) costs for growth and yield expected upon
reinstalment of stilbene inducibility would be more than compensated
by the reduced costs for chemical plant protection, reduced
loss by pathogens, and improved sustainability. Since the
‘blue’ (high-stilbene type) genotypes seem to cluster to specific
branches of the phylogenetic tree constructed for the European
wild grape, it is also planned to explore the possibility of using
the ancestor of cultivated grapevine as a genetic resource for
marker-assisted breeding for improved basal immunity.
Supplementary data are available at JXB online.
Figure S1. Correlations between the amounts of piceid,
resveratrol, viniferins, piceatannol, and pterostilbene.
Figure S2. Boxplots of the amounts of each stilbene in the
blue (B) and in the green (G) cluster.
Figure S3. Boxplots of the piceatannol/total stilbene ratio
in the blue and green cluster.
Table S1. Correlations between the amounts of piceid,
resveratrol, viniferins, piceatannol, and pterostilbene.
Table S2. The construction of the stilbenes for each
component in principal component analysis.
Table S3. Primer list and literature references used for
semiquantitative RT–PCR and quantitative real-time PCR for
Table S4. Data on developmental and environmental
stability of relative stomata incidence.
This work was supported by the BACCHUS Interreg IV Upper Rhine
project co-financed by the European Union/European Regional Development
Fund (ERDF), the German Federal Agency for Agriculture (Programme
for Sustainable Agriculture, BÖLN), and by a fellowship from the Chinese
Scholarship Council to Dong Duan. We gratefully acknowledge Joachim
Daumann and Kerstin Huber (Karlsruhe Institute of Technology) for
taking care of plants in the Botanical garden, Yue He (KarlsruheInstitute of
Technology) for measuring the transcript levels of StSy, RS, and CHS in
response to downy mildew, and Anne Alais (INRA, Colmar) for help with
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