Abstract
Dittrichia viscosa (L.) W. Greuter is a pioneer species belonging to
the Compositae family. It is widespread in the Mediterranean basin,
where it is considered invasive. It is a source of secondary
metabolites, playing an important ecological role. D. viscosa plant
extracts showed a phytotoxic activity on several physiological
processes of different species. In the current study, the allelopathic
potential of D. viscosa VOCs, released by its foliage, was evaluated on
seed germination and root growth of lettuce. The VOCs effect was also
studied on lettuce adult plants in microcosm systems, which better
mimicked the open field conditions. D. viscosa VOCs inhibited both seed
germination and root growth of lettuce. The VOCs composition revealed a
large presence of terpenoids, responsible of the effects observed.
Moreover, D. viscosa VOCs caused an alteration on plant water status
accompanied by oxidative damages and photoinhibition on lettuce adult
plants.
Introduction
Dittrichia viscosa (L.) W. Greuter (syn. Inula viscosa (L.) Aiton.,
Cupularia viscosa G. et G.) is an evergreen perennial shrubby-weed
belonging to the family Compositae. It is native to the Mediterranean
region and it is considered a ruderal species due to its abundance in
anthropic altered areas [[30]1], and in particular, in metal-polluted
sites [[31]2]. D. viscosa has a remarkable pioneer nature since it
colonizes different habitats in the Mediterranean basin where it often
creates large monospecific communities [[32]3]. In Australian and some
European countries, this species is considered an important
environmental weed for its high seed production and spreading, and for
its resistance/adaptation to adverse conditions [[33]3, [34]4]. D.
viscosa is characterized by a quite substantial root apparatus and the
ratio between below- and above-ground biomass is 0.24 [[35]5]. The
canopy is very dense reaching 150 cm of height and total leaf area per
plant comprises 200 cm^2 [[36]6]. Glandular hairs, which produce a
sticky resin from which derives “viscosa” name, cover the entire plant
conferring its strong typical fragrance [[37]3].
D. viscosa has allelopathic potential and, in particular, its extracts
caused phytotoxic effects on several species, inhibiting roots and
causing root anatomical abnormalities [[38]7]. Interestingly, these
extracts did not cause autotoxicity phenomenon conferring to this
species a competitive advantage over other species [[39]8]. Moreover,
leaf epicuticular substances were also considered strong allelopatic
agents for N[2]-fixing soil cyanobacteria, decreasing dramatically the
photosynthetic assimilation of CO[2] and increasing the
heterocyst-to-vegetative cell ratio and most likely the assimilation of
N[2] of the cyanobacteria [[40]9]. Finally, the effect of several
extracts was assayed on crops and weeds, pointing out that D. viscosa
allelopathic potential seems to be attributed mainly to leaf leachate
[[41]10]. This effect could be attributable to the presence of many
secondary metabolites such as flavonoids [[42]11], sesquiterpene
lactones and acids [[43]12–[44]14] and triterpenoids [[45]15, [46]16],
biologically active compounds. In particular, formulated leaf extracts
of D. viscosa exhibited nematicidal [[47]17, [48]18], insecticidal
[[49]19, [50]20] antifungal [[51]21, [52]22] activity.
Although many information is available regarding the in-vitro
phytotoxic potential of the D. viscosa extracts, the activity of
volatile organic compounds (VOCs), released by foliage, was never
assessed. The presence of allelochemicals in aromatic shrub has been
already established [[53]23] playing a pivotal role especially in arid
and semi-arid conditions where they act in the vapor phase [[54]23,
[55]24]. Several studies demonstrated that plant volatiles are potent
seed germination inhibitors, reducing seedling establishment and growth
in ecosystems [[56]25–[57]27]. For example, the VOCs produced by
Artemisia vulgaris [[58]26, [59]28], Calamintha nepeta or perennial
groundcovers [[60]29–[61]32] suppressed weed seedling growth.
The VOCs are generally composed by terpenes, which provide to species a
large number of ecological advantages [[62]33] including plant
reproduction, pollinator attractants, herbivores protection and
plant–plant communication. These features make these compounds
determinants for the vegetation patterning [[63]34, [64]35].
In the current paper, the allelopathic potential of D. viscosa VOCs,
naturally released from its foliage, was assessed on Lactuca sativa L.
The VOCs effect was assayed on seed germinatin and root growth of
lettuce. Furthermore, the response of lettuce adult plants to VOCs was
also studied in microcosm systems, in order to better mimic the open
field conditions. Furthermore, the metabolome profile of lettuce adult
plants, in response to VOCs released by a donor species, was here
analyzed for the first time.
Materials and Methods
Plant material
Aerial parts of D. viscosa were sampled on September 2015 in Calabria
(Southern Italy). The plant material was collected in experimental
fields belonging to the University Mediterranea of Reggio Calabria
(Italy) (latitude N 38°7’ 40.883”, longitude E 15°40’ 36.375”) and its
collection did not require any specific permission.
In vitro VOCs bioassays
The in vitro volatiles bioassay was carried out as previously described
by Araniti et al. [[65]29], with some modifications. Freshly harvested
greenish branches were evaluated for the bioactive volatile activity
allowing only atmospheric contact between the test and the donor
species. The aerial parts (0, 25, 50, 100 and 200 g of entire branches)
of D. viscosa (donor species) were daily collected and immediately
placed on the bottom of a 4.5 L jar capped with a plastic net ([66]S1
Fig). A Petri dish (6 cm Ø) was filled with a double layer of filter
paper, moistened with 2 ml of sterile deionized water and gently laid
on a porous surface on the top of cut plant material ([67]S1 Fig). The
jar was then transferred in a ventilated climatic chamber settled with
a temperature of 25±1°C and a 16:8 (light:dark) photoperiod. For each
petri dish, 10 sterilized seeds of L. sativa L. (var. Parris Island
COS), were sown. Germinated seeds were counted every 6 hours for 48 hr,
considering germinated those seeds showing ≥ 1 mm of root protrusion
from seed coat. According to Chiapusio et al. (1997), at the end of the
observations, the total germination rate [G[T] (%)] and the average
speed of germination (S) were calculated as follow:
* Total germination rate:
[MATH:
GT (%<
/mi>)=100*(NT/N
) :MATH]
where T indicates the last observation and N is the total number of
seeds sown.
* Average speed of germination:
[MATH:
S=(N1*1)+ 1/2(N
2−N1
)+1/3 (N3−N2)+….+1/n (Nn−Nn−1) :MATH]
where N[1], N[2], N[3], N[n-1], N[n] is the number of germinated seeds
at each counting time.
Root growth [TRL (cm)] was evaluated on five pre-germinated seedlings,
grown as previously described for seed germination, after 48 hr of
treatment. D. viscosa plant material was daily changed to mimic field
conditions.
Head space GC-MS analysis of plant volatiles
The D. viscosa VOCs were chemically characterized using a Thermo Fisher
gas chromatograph apparatus (Trace 1310) equipped with a single
quadrupole mass spectrometer (ISQ LT). The capillary column was a
TG-5MS 30 m×0.25 mm×0.25μm the gas carrier was helium with a flow rate
of 1 ml/min. Injector and source were settled at 200°C and 260°C,
respectively. The sample (1 g of fresh plant material) was incubated
for 1 minute at 40° and 1 μl of the head space was injected in split
mode with a split ratio of 60. The following temperature was
programmed: isocratic for 7 minutes at 45°C, from 45°C to 80°C with a
rate of 10°C×min, from 80°C to 200°C with a rate of 20°C×min, then
isocratic for 3 minutes 200°C. Mass spectra were recorded in electronic
impact (EI) mode at 70 eV, scanning at 45–500 m/z range. Compounds
identification was carried out comparing the relative retention time
and mass spectra of molecules with those of the libraries (NIST 2005,
Wiley 7.0 etc.).
Bioassays on adult plants
VOCs bioassay on adult plants
The VOCs bioassay on lettuce adult plants was carried out as previously
described [[68]36]. Lettuce plants (30 days old) were exposed to D.
viscosa VOCs, produced by 50 g of living plant material, for 12 days.
During this period plants were daily irrigated with a half strength
Hoagland solution. As for germination and root growth bioassays, D.
viscosa plant material was daily renewed.
Photosynthetic pigments and Chlorophyll a fluorescence measurements
Chlorophyll a (Chl[a]), chlorophyll b (Chl[b]), and carotenoids (Ct)
content were determined according to Wellburn [[69]37]. In particular,
100 mg of frozen plant material were extracted with 1.5 ml of pure
methanol and centrifuged at 170 g at 4°C for 5 min. Five hundred μL of
supernatant were then collected and diluted with 500 μL of methanol.
The absorbance of the pigment extract was determined at 470, 653, 666
and 750 nm. Pigment content was evaluated according to Wellburn’s
equations [[70]37].
The fluorescence of the chlorophyll a emitted by plants (three per
treatment) exposed to VOCs was determined as described by Araniti et
al. [[71]36] with some modifications. Chlorophyll fluorescence was
monitored using the Maxi-Imaging-PAM Chlorophyll Fluorescence System
fluorometer (Walz, Effeltrich, Germany), and monitored every three days
for 12 days. The following parameters were calculated: the maximum
quantum efficiency of dark-adapted photosystem II (F[v]/F[m]); the
maximum quantum efficiency of lighted photosystem II (Φ[II]); the
regulated energy dissipation in the form of heat (Φ[NPQ]); the
nonregulated energy dissipation (Φ[NO], fluorescence emitted) and the
estimated electron transport rate (ETR). The photosynthetic response
was monitored for 5 min, and fifteen measurements were obtained for
each parameter at each measuring time.
In situ semi-quantitative determination of H[2]O[2]
Hydrogen peroxide was determined according to Araniti et al. [[72]38]
with some modifications. Four fully expanded leaves were cut and fixed
for 8 h in 3,3’-diaminobenzidine (DAB) (1 mg mL^-1) solution (pH 3.8).
The incubation was carried out in dark condition and pigments were
successively removed rinsing leaves twice in pure ethanol. Bleached
leaves were stored in 80% glycerol. Stained areas were determined by
image analysis with the software Image ProPlus v.6.0 (Media Cybernetics
Inc., Bethesda, MD, USA).
Lipid peroxidation
Lipid peroxidation was determined as described by Araniti et al.
[[73]36], measuring the increase of malondialdehyde (MDA) in the
sample. Liquid nitrogen powdered plant material (100 mg) was
homogenized in 80% cold ethanol solution (1 ml) and centrifuged at 3000
g for 10 minutes at 4°C. The supernatant was collected and incubated
for 25 minutes at 95°C with 20% trichloroacetic acid (TCA) containing
0.01% hydroxytoluenebutylate, with and without 0.5% thiobarbituric acid
(TBA). After incubation, the reaction was stopped in ice and the
samples were centrifuged at 3000 g at 15°C for 10 minutes. The
absorbance of the supernatant was measured at 440, 532 and 600 nm.
The equivalents of MDA were calculated using the equations proposed by
Hodges et al. [[74]39].
Total protein content
Total protein content of lettuce leaves exposed for 12 days to D.
viscosa VOCs was determined according to Bradford [[75]40], using
bovine serum albumin as standard. Protein content was expressed as
micrograms per gram of dry weight.
Fresh weight (FW), dry weight (DW), DW/FW ratio, leaf relative water content
(RWC), leaf osmotic potential [Ψ (π)] and leaf membrane stability index [MSI
(%)]
At the end of the experiment, four plants were collected and their FW
was evaluated. Plants were oven dried for one week at 60°C in order to
get DW and to calculate DW/FW ratio parameter.
Leaf relative water content (RWC) was estimated as previously reported
by Mullan and Pietragalla [[76]41] with some modifications. One leaf
for each replicate was weighted (FW) and incubated for 24 h at 4°C in
50 ml falcon tube filled with 15 ml of ultrapure water. After
incubation the turgid weight (TW) was taken and leaf samples were
transferred in an oven and dried at 60°C for 48 h and successively
weighted (DW). RWC parameter was evaluated using the following
equation:
[MATH: RWC=[(FW−DW)/(TW−DW)]*100 :MATH]
Leaf Ψπ was measured at the end of the experiment on four leaves per
treatment (0 and 50 g cut plant material) as described by Araniti et
al. [[77]36]. Lettuce leaves were collected and frozen at -20°C. After
24 hours, leaves were squeezed into a syringe (the first drop was
thrown away), the extract was collected and the Ψπ was measured with a
cryoscopic osmometer (Osmomat 030, Gonatec).
The MSI was determined indirectly as reported by Saìram et al. [[78]42]
with some modifications. Leaf discs with uniform size were transferred
in falcon tubes containing 10 ml of ultrapure water and heated at 30°C
for 30 minutes. Then electrical conductivity was measured (C1) and the
samples were immediately transferred at 100°C, for 30 minutes. Samples
were cooled in ice and the electric conductivity was newly measured
(C2). MSI index was obtained using the following equation:
[MATH: SI (%)=(<
/mo>1− C1/C2)*100 :MATH]
Extraction, identification and quantification of primary metabolites in
lettuce leaves
Extraction, identification, and quantification of metabolites from
lettuce leaves were performed as reported by Shi et al. [[79]43],
whereas sample derivatization were performed as Lisec et al. [[80]44].
The derivatizated extract was injected into a TG-5MS capillary column
using the single quadrupole gas chromatographer coupled to a mass
spectrometer (GC-MS) (Thermo Fisher), as previously described.
Injector and source were settled at 250°C and 260°C temperature,
respectively. One μl of sample was injected in splitless mode with a
flow of 1ml/min using the following programmed temperature: isothermal
5 min at 70°C followed by a 5°C/ min ramp to 350°C and a final 5 min
heating at 330°C. Mass spectra were recorded in electronic impact (EI)
mode at 70 eV, scanning at 45–500 m/z range.
The extracted metabolites were identified comparing every retention
time index-specific mass with reference spectra in mass spectral
libraries (NIST 2005, Wiley 7.0 etc.). Relative metabolites
quantification was based on a pre-added internal standard (ribitol at
0.02 mg/ml) added during the extraction process.
Experimental design and statistical analysis
A completely randomized design with four replications was applied in
all the experiments except for chlorophyll a fluorescence that was
replicated 3 times. Data were first checked for normality through the
Kolmogorov-Smirnov test and then tested for homogeneity of variances
with the Levene’s test. Differences among group means were
statistically evaluated by analysis of variance followed by Least
Significant Difference tests (LSD) in the case of homoscedastic data,
and by Tamhane’s T2 test in the case of heteroscedastic data (P ≤
0.05).
All statistical analyses were conducted using SPSS ver. 6.1 software
(Insightful Corporation, USA). Speed Germination, Total Germination and
Total Root Length responses to different doses of plant material were
evaluated by a nonlinear regression model using a log-logistic function
in order to calculate the ED[50] values as reported by Araniti et al.
[[81]45–[82]47].
Metabolite concentrations were checked for integrity and missing values
were replaced with a small positive value (the half of the minimum
positive number detected in the data). Data were successively
normalized by a pooled sample (Creating a pooled average sample from
control groups), transformed through “Log normalization” (to make the
metabolite concentration values more comparable among different
compounds) and scaled through Pareto-Scaling (mean-centered and divided
by the square root of standard deviation of each variable) [[83]48].
Data were then classified through Principal Component Analysis (PCA),
metabolite variations were presented and samples clusterized through a
heatmap. Differences between treatments were considered significant
when the P ≤ 0.05 (Student’s t-test).
Ingenuity pathway analysis was performed with MetPA, a web-based tool
for pathway analysis & visualization metabolomics. MetPA is a module of
Metaboanalyst that combines results from powerful pathway enrichment
analysis with the pathway topology analysis to help researchers in
identifying the most relevant pathways involved in the conditions under
study. Compound ID associations were determined by matching to HMDB,
PubChem and KEGG. Then, the pathway library, the algorithm for pathway
enrichment analysis, and the algorithm for topological analysis were
selected and performed to evaluate the possible biological impacts on
the perturbed pathways [[84]48].
Results
Experiments on lettuce seeds and seedlings
In vitro VOCs bioassay
The results pointed out a strong phytotoxic potential of D. viscosa
VOCs on both lettuce seeds germination and seedling growth. In
particular, chemicals released from plant material strongly reduced, in
a dose dependent manner, both speed (S) and total germination (G[T]).
Interestingly, the S parameter was significantly inhibited (≈ 12%) even
at the lower treatment (12.5 g), increasing up to 86% at 100 g of plant
material ([85]Fig 1). Conversely, the lowest treatments (12.5 and 25 g)
did not affect the G[T] parameter, while 50 g treatment caused 18% of
inhibition, reaching the 82% at 100 g and 100% at the highest
concentration ([86]Fig 1). The nonlinear regression fit of both S and
G[T] raw data gave 69.02 g and 71.98 g ED[50] values, respectively
([87]Fig 1).
Fig 1. Effects of Dittrichia viscosa volatiles on germination and root
growth.
[88]Fig 1
[89]Open in a new tab
Effects of D. viscosa VOCs on Total Germination [G[T] (%)], Speed
Germination (S) and Total Root Length [TRL (cm)] of L. sativa. The
nonlinear regression fitting of all the dose-response curves pointed
out a significance level of P < 0.001. Different letters along the
curve indicate statistical differences with P ≤ 0.05 (LSD). AU =
arbitrary units. N = 4.
A stimulation of TRL in lettuce root seedlings, at the lowest
concentration (12.5 g), was observed, whereas 25 g did not affect this
parameter. On the contrary, higher doses strongly affected lettuce root
growth causing 41%, 81% and 85% of inhibition at 50 g, 100 g and 200 g
of plant material treatment, respectively. The non linear regression
fit of TRL raw data pointed out 51.33 g ED[50] value ([90]Fig 1).
Head space GC-MS analysis of plant VOCs
The VOCs characterization released by Dittrichia viscosa leaves allowed
the identification of 39 compounds, most of which belong to the
terpenoids class ([91]Table 1). In particular 4 aldehyde, 2 alcohols
and 1 ester were identified ([92]Table 1). Among terpenes, 16
monoterpenes (among them one monoterpenic ester and three monoterpenic
alcohols), 1 homoterpene and 15 sesquiterpenes were identified
([93]Table 1).
Table 1. Chemical characterization of Dittrichia viscosa VOCs.
Dittrichia viscosa VOCs characterization. Aldehydes: 1–4; alcohols:
5–6; monoterpenes: 7–17, 19, 21–24; homoterpene: 20; sesquiterpenes:
25–39.
[94]^aRT Compound Class [95]^bRAP%
1 2.58 Isovaleraldehyde Aldehyde 0.33
2 2.68 α-Methylbutanal Aldehyde 0.56
3 5.53 n-Hexanal Aldehyde 0.18
4 8 Leaf aldehyde Aldehyde 0.39
5 8.26 3-Hexen-1-ol Alcohol 0.52
6 8.82 3-Methylpentanol Alcohol 0.17
7 10.2 α-Thujene Monoterpene 3.26
8 10.37 α-Pinene Monoterpene 9.88
9 10.78 Camphene Monoterpene 0.3
10 11.38 Sabinene Monoterpene 6.83
11 11.43 ß-Pinene Monoterpene 3.37
12 11.74 Myrcene Monoterpene 0.81
13 11.88 1,8-Cineole Monoterpene 0.89
14 12.31 o-Cymene Monoterpene 1.31
15 12.53 Eucalyptol [96]Monoterpene 43.24
16 12.82 γ-Terpinene [97]Monoterpene 1.47
17 13.05 cis-Sabinene hydrate [98]Monoterpene 0.93
18 13.36 Methyl benzoate Ester 0.08
19 13.46 4-Terpinenyl acetate Monoterpene esters 0.47
20 13.51 (3E)-4,8-Dimethyl-1,3,7-nonatriene homoterpene 0.18
21 13.7 p-Menth-2-en-1-ol Monoterpene alcohol 0.06
22 13.98 Camphor Monoterpene 0.18
23 14.26 L-terpinen-4-ol Monoterpene alcohol 0.3
24 14.4 α-Terpineol Monoterpene alcohol 0.11
25 15.86 Ylangene Sesquiterpene 1.84
26 15.9 α-Copaene Sesquiterpene 1.36
27 15.94 α-Panasinsen Sesquiterpene 0.44
28 16.03 Sativen Sesquiterpene 0.12
29 16.24 (E)-Caryophyllene Sesquiterpene 1.72
30 16.29 Isolongifolene Sesquiterpene 0.14
31 16.37 Guaia-6,9-diene Sesquiterpene 2.63
32 16.42 α-Gurjunene Sesquiterpene 0.22
33 16.48 α-Humulene Sesquiterpene 0.34
34 16.53 Alloaromadendrene Sesquiterpene 0.22
35 16.62 α-Muurolene Sesquiterpene 1.01
36 16.69 α-Cadinene Sesquiterpene 2.99
37 16.76 α-Selinene Sesquiterpene 0.2
38 16.9 Δ-Cadinene Sesquiterpene 0.1
39 17.11 (E)-Nerolidol Sesquiterpene 0.51
[99]Open in a new tab
^a RT: retention time.
^b RAP% (Relative area percentage, peak area relative to total peak
area %).
Experiments on lettuce adult plants
In vivo Chlorophyll a fluorescence measurements and photosynthetic pigment
content
The monitoring of chlorophyll a fluorescence, emitted by lettuce adult
plants exposed to D. viscosa VOC, pointed out strong inhibitory effects
on photosynthetic activity (Figs [100]2–[101]4). In particular, plants
treated showed a high significant reduction on the photochemical
quenching Φ[II] from day 4 (T[2]) onwards ([102]Fig 2), whereas Φ[NPQ]
parameter was significantly reduced only from day 6 (T[3]) until the
end of the treatment (T[4]) ([103]Fig 2). Conversely, the fluorescence
parameter Φ[NO] was significantly stimulated after 4 day (T[2]) of
treatment ([104]Fig 2). Finally, both F[v]/F[m] and ETR parameters were
significantly reduced after 4 days (T[2]) of treatment onwards
([105]Fig 3). Interestingly, in the treated plants the F[v]/F[m]
clearly declined in the older peripheral leaves, which viability was
irreversibly compromised, while the central vascular bundles and the
youngest leaves were not affected ([106]Fig 4A–4D).
Fig 2. Effects of Dittrichia viscosa volatiles on photochemical quantum yield
of the PSII, the quantum yield of light-induced nonphotochemical quenching
and chlorophyll fluorescence.
[107]Fig 2
[108]Open in a new tab
Values of the effective photochemical quantum yield of the light
adapted PSII Φ[II], the quantum yield of light-induced nonphotochemical
quenching Φ[NPQ] and chlorophyll fluorescence Φ[NO] in whole lettuce
plants after D. viscosa VOCs exposition (50 g of plant material).
Asterisks along the curves indicate statistical differences with (P ≤
0.05). * p < 0.05; ** p < 0.01; *** p < 0.001. T[0] –T[4] = days of
treatment. AU = Arbitrary Units. N = 3.
Fig 4. Pseudo-colour images of maximum quantum efficiency of dark-adapted
PSII after the treatments of the plants with Dittrichia viscosa volatiles and
their effects on pigments content.
[109]Fig 4
[110]Open in a new tab
Pseudo-colour images of maximum quantum efficiency of dark-adapted PSII
(Fv/Fm) in adult plants of lettuce after D. viscosa VOCs exposition.
Images were taken at the beginning (T0) and at the end of the
experiment (T4). A) Control plant at T0; B) control plant at T4; C)
treated plant at T0; D) treated plant at T4. Images of the various
fluorescence parameters are depicted in false colors coding from 0.0
(black) to 1.0 (purple). N = 3. E) Pigments content [μg/DW(g)]:
Chlorophyll a (Chla), Chlorophyll b (Chlb), Carotenoids (Car). Data are
given in percentage compared to the control and were analyzed trough
LSD test. (p < 0.05). * p < 0.05; ** p < 0.01; *** p < 0.001. N = 3,
for pseudo-color images; N = 4, for pigment content determination.
Fig 3. Effects of Dittrichia viscosa VOCs on maximum quantum efficiency of
dark-adapted PSII and apparent electron transport rate.
[111]Fig 3
[112]Open in a new tab
Values of maximum quantum efficiency of dark-adapted PSII (Fv/Fm) and
apparent electron transport rate (ETR) in whole lettuce plants after D.
viscosa VOCs exposition (50 g of plant material). Asterisks along the
curves indicate statistical differences with (P ≤ 0.05). * p < 0.05; **
p < 0.01; *** p < 0.001. T[0] –T[4] = days of treatment. AU = Arbitrary
Units. N = 3.
Furthermore, 12 days of VOCs exposition caused a significant reduction
of all the pigments content ([113]Fig 4E). In particular, chlorophyll a
and b were reduced by 23% and 30%, respectively. Interestingly,
carotenoids were the most affected by VOCs exposition with 35% of
reduction ([114]Fig 4E).
FW, DW, DW/FW ratio, RWC, leaf Ψ (π), MSI (%), MDA (%), in situ
semi-quantitative determination of H[2]O[2] and protein quantification
Treatment of lettuce adult plants with D. viscosa VOCs (from 50 g plant
material), for 12 days, caused 19% of FW reduction but did not
significantly affect DW parameter ([115]Fig 5A and 5B). Conversely, the
DW/FW ratio significantly increased in treated plants (21%) ([116]Fig
5C). Furthermore, the treated plants showed 22%, 32%, and 43% of
reduction in RWC, protein content and MSI compared to control,
respectively ([117]Fig 5D, 5F and 5H). However, the Ψ(π) parameter was
significantly stimulated (18%) ([118]Fig 5E) as well as the lipid
peroxidation (≈ 24%), indirectly determined by the increase of
malondialdehyde (MDA) ([119]Fig 5G). Finally, a high accumulation of
H[2]O[2,] which was present on almost the 44% of leaf surface, was
observed ([120]Fig 6).
Fig 5. Effects of Dittrichia viscosa VOCs on several morphological and
physiological parameters.
[121]Fig 5
[122]Open in a new tab
Effects of D. viscosa VOCs on lettuce adult plants. A) Fresh weight
(FW); B) dry weight (DW); C) DW/FW ratio; D) relative water content
(RWC); E) leaf osmotic potential [Ψ(π)]; F) membrane stability index
(MSI); G) lipid peroxidation (MDA) (nmol/mL/g[DW]); H) total protein
content (μg of protein /g DW). Data are given in percentage compared to
the control and were analyzed through LSD test. (P < 0.05). * P < 0.05;
** P < 0.01; *** P < 0.001. N = 4.
Fig 6. Semiquantitative determination of H[2]O[2] in plants treated with
Dittrichia viscosa volatiles.
[123]Fig 6
[124]Open in a new tab
Lettuce leaves exposed to D. viscosa VOCs for 12 days showing the
localization of the hydrogen peroxide on leaf surface after DAB
staining: A) Control leaf; B) treated leaf; C) percentage of the
Integrated Optical Density (IOD) obtained through image analysis
carried on the in situ semi-quantitative determination of H[2]O[2]. In
dark grey is reported the unaffected (Unaff) area of the leaf, whereas
in bright grey the leaf surface interested by H[2]O[2] accumulation
(Aff). The area affected is expressed as percentage of the total area.
(P < 0.05). * P < 0.05; ** P < 0.01; *** P < 0.001. N = 4.
Metabolomic experiments
To gain more insights into the modulation of metabolic homeostasis
caused by D. viscosa VOCs exposition, GC-MS analysis were performed to
identify differentially expressed metabolites. Fifty-four metabolites,
including 10 amino acids, 23 organic acids, 9 sugars, 1 sugar acid, 5
sugar alcohols, 3 amines, 2 fatty acid and 1 glycan were examined in
non-treated and treated plants.
Metabolomic data were then analyzed through principal component
analysis (PCA). In [125]Fig 7A is reported the PCA score plot, which
allowed samples separation and outliers detection basing on their
metabolite profiles, whereas in [126]Fig 7B is reported the PCA loading
plot that allowed the identification of metabolites that contributes to
the separation of samples reported on the score plot. This separation
between control and treated samples was achieved using the principal
components (PCs) PC1 vs PC2, which explained a total variance of 81.9%.
In particular, PC1 explained the 71.6% of the variance while PC2 the
10.3%.
Fig 7. PCA analysis carried on the metabolite identified and quantified after
Dittrichia viscosa VOCs treatment.
[127]Fig 7
[128]Open in a new tab
A) Principal Component Analysis model scores A) and loading plot B) of
metabolite profile of control plants (Contr_1 –Contr_4, replicates of
control samples) and plants exposed to D. viscosa VOCs (Treated_1
–Treated_4, replicates of the treated samples). Both score and loading
plots were generated using the first two PCs, PC1 vs PC2, with the
explained variances shown in brackets; C) Overlay heat map of
metabolite profiles in plants exposed to D. viscosa VOCs released by
fresh aerial parts in comparison with control plants. Each square
represents the effect of plant VOCs on the amount of every metabolite
using a false-color scale. Red or green regions indicate increased or
decreased metabolite content, respectively.
The PCA loading plot in [129]Fig 7B shows that PC1 was dominated by
D-Glucose, L-Aspartic acid and Palmitic acid, whereas PC2 was dominated
largely by 3-α-Mannobiose.
PCA and heatmap visualization of metabolomic data showed distinct
segregation between the control and the treated plants ([130]Fig 7).
Finally, the t-test analysis revealed 35 out of 55 significantly
different metabolites between treated and non-treated samples ([131]S1
Table).
A detailed analysis concerning the pathways and networks affected by
the VOCs treatment was performed by MetPa. The “pathway analysis” of
the results allowed to identify treatment impact on plant metabolism.
Interestingly, several pathways were significantly affected ([132]S2
Table), but the most effective and recurrent effects were mainly
related to amino acids and sugars metabolism ([133]S2 Table and Figs
[134]8 and [135]9). In particular, L-aspartic (Asp) and L-glutamic
(Glu) acids were reduced by 80.5% and 67.5%, respectively ([136]Fig 8).
Conversely, all the other amino acids were highly stimulated by VOCs
exposition ([137]Fig 8). In particular, L-leucine (Leu) and serine
(Ser) content was ~ 80% higher than control, whereas an increase ranged
between 40% and 63% of isoleucine (Ile), L-threonine (Thr),
γ-aminobutiric acid (GABA) and L-valine (Val) content was observed.
Finally, proline (Pro) was the most stimulated amino acids reaching
values 1.8 folds higher than control ([138]Fig 8). Among the sugars,
sucrose (Suc) and glucose (D-Gu) content were reduced by ≈ 37% and 82%,
respectively ([139]Fig 9). Similarly, arabinose (25%), β-gentiobiose
(3%), D-xylose (23%) and myoinositol (55%) where significantly reduced
by the treatment ([140]Fig 9), whereas D-lactose (140%) and Galactinol
(5%) content was stimulated ([141]Fig 9).
Fig 8. Effects of Dittrichia viscosa volatiles on amino acids content.
[142]Fig 8
[143]Open in a new tab
The effects of the exposition for 12 days to D. viscosa VOCs on lettuce
leaf amino acids abundance. Asp (aspartic acid); Glu (glutamic acid);
Leu (leucine); Thr (threonine); Val (valine); Ser (serine); GABA
(γ-aminobutiric acid); Ile (isoleucine); Pro (proline). Data were
analyzed through t-test (P≤0.05) (data from [144]S1 Table). * P < 0.05;
** P < 0.01; *** P < 0.001. N = 4.
Fig 9. Effects of Dittrichia viscosa volatiles on sugars content.
[145]Fig 9
[146]Open in a new tab
The effects of the exposition for 12 days to D. viscosa VOCs on lettuce
leaf sugars abundance. Suc (Sucrose); D-Glu (D-Glucose); D-Lac
(D-Lactose); Ara (Arabinose); β-Gentiobiose (β-Gen); D-Xyl (D-Xylose);
Myo (Myoinositol); Gal (Galactinol). Data were analyzed through t-test
(P ≤ 0.05) (data from [147]S1 Table). * P < 0.05; ** P < 0.01; *** P <
0.001. N = 4.
Discussion
Consistent with previous results [[148]9], the allelopathic potential
of D. viscosa was confirmed through a bioassay that imitated natural
environmental conditions of allelochemical VOCs release. For this
reason, lettuce seeds, seedlings and adult plants were placed in open
containers included in a ventilated growth chamber, and exposed to D.
viscosa VOCs, directly released by plant parts. In particular, the
effects of D. viscosa VOCs were demonstrated on lettuce seed
germination and root growth, physiological processes largely employed
to establish the secondary metabolites phytotoxicity [[149]49] and the
allelopathic potential of species [[150]50].
In vitro results showed that D. viscosa VOCs had a strong inhibitory
activity on both seed germination and root growth of lettuce resulting
in low ED[50] values. Similar effects were previously reported with
Calamintha nepeta VOCs on germination and root growth of both crops and
weeds [[151]29], with Salvia leucophylla VOCs on root apical meristem
of Brassica campestris [[152]24] and with VOCs released by several
selected ground covers on seeds [[153]31]. Moreover, in agreement with
several authors [[154]51–[155]53] the results clearly demonstrated that
the seedlings establishment is more sensitive than germination to
allelochemicals.
The effects of D. viscosa VOCs on seed germination were also analyzed
comparing G[T] (%) and S indexes. In particular, the G[T] (%) parameter
indicated that VOCs inhibited lettuce germination at relatively high
concentrations. Conversely, the S index was significantly affected even
at low concentrations. Juglone and trans-cinnamic acid caused similar
effects on A. thaliana seeds [[156]50]. The S reduction, which
indicates a seed germination delay after VOCs exposure, is an important
ecological effect because it represents a competitive advantageous
strategy for D. viscosa in an ecosystem [[157]54]. In fact, the
germination delay could compromise, in the early stages of the
seedlings life, the survival of the neighboring species. At this stage,
a short period of inhibition could strongly reduce the ability of
species to compete with others on their establishment [[158]55,
[159]56]. This could explain the ability of D. viscosa to create
monospecific communities in its habitat.
Phytochemical analysis of D. viscosa VOCs revealed a strong presence of
monoterpenes and sesquiterpenes, well known as allelopathic compounds,
able to affect plant growth generally causing oxidative stress followed
by a cascade effect on many physiological processes of receptor plants
[[160]57]. Both of them affected mitochondrial respiration [[161]58,
[162]59] and microtubule distribution and organization [[163]38,
[164]60], destroyed cell membranes [[165]61] and altered hormone
balance and plant water status [[166]36, [167]62]. The sesquiterpenes
trans-caryophyllene was able to affect the germination and growth of
several weeds as well as of Arabidopsis adult plants inducing the
alteration of plant water status [[168]36]. Graña et al. [[169]62]
observed similar effects with the monoterpene citral. Singh et al.
[[170]63] reported that α-Pinene was able to inhibit root growth of
several weeds causing oxidative stress and destroying cell membrane
integrity. Moreover, Hussain et al. [[171]64] demonstrated that the
terpenoid artemisinin was able to inhibit photosynthetic efficiency, to
cause oxidative stress and lipid peroxidation in roots as well as to
interfere with calcium and nitrogen content in Arabidopsis.
Moreover, terpenoids, at non-phytotoxic concentrations, might act
synergistically and become extremely phytotoxic [[172]65],
corroborating the hypothesis that allelopathic phenomenon is due to the
combined action of different molecules, and underlining the complexity
of plant interactions in natural- and agro-ecosystems.
Interestingly, the D. viscosa VOCs affected plant bio-membranes through
the induction of lipid peroxidation resulting in a reduction of
membrane stability (reduced MSI) and the semi-quantitative analysis of
H[2]O[2] further confirmed the presence of the oxidative damages. These
effects were generally induced by allelochemicals, which inhibited the
antioxidant enzymes activity increasing the level of free radicals, and
consequently causing membrane lipid peroxidation and membrane potential
alteration [[173]66–[174]70].
Under allelochemicals exposure, the oxidative stress was induced by
plant water status alteration [[175]36, [176]62]. For example, menthol
and camphor, two terpenoids, enhanced the transpiration of Arabidopsis
thaliana fully developed rosette dewaxing the lipophilic layers at leaf
surface. As consequence, plants showed a dramatic effect characterized
by water loss, necrosis and plant death, demonstrating that the
lipophilic layers of leaf surface and stomata were primary targets of
these monoterpenes [[177]71]. Conversely, lettuce plants exposed to D.
viscosa VOCs were extremely damaged without showing necrosis and/or
plant death. This milder effect could be due to the different growth
conditions, which ensured a greater air movement to plants avoiding
VOCs accumulation.
Nevertheless, as suggested by Shultz et al. [[178]71], high content and
variability on terpenoids released by D. viscosa VOCs could affect leaf
water status of lettuce, FW, DW/FW ratio, accompanied by the RWC
reduction and the increase of Ψπ, typical of water status alteration.
The metabolomic profile of treated plants further confirmed this
hypothesis, showing a high impact on amino acidic pathways, which
results in an increment of several amino acids content, involved in
osmotic adjustment. Among them, quaternary ammonium compounds
[[179]72–[180]74] and amino acids such as proline, asparagine and
γ-aminobutyric acid (GABA) [[181]75–[182]77] play a pivotal role in the
recovery of plants from stress [[183]77] such as osmotic stress
[[184]78–[185]80]. In particular, proline accumulates to high levels in
species adapted to arid and saline environments, in plant tissues
withstanding severe desiccation, in response to allelochemicals
[[186]36, [187]62, [188]81, [189]82] and in cellular redox regulation,
protecting proteins and membranes and scavenging reactive oxygen
species [[190]83, [191]84]. As well as proline, GABA, involved in many
plant responses to stress, such as nitrogen storage, pH regulation,
plant defense and osmotic adjustments [[192]85], increased in treated
plants. High increment of both proline and GABA could be correlated
with the reduction of glutamic acid, a precursor of their synthesis
[[193]85, [194]86]. Indeed, previous experiments carried out with
labeled (^14C) gluthamic acid pointed out that water stressed shoots of
bermuda grass readily accumulated much more proline newly synthesized
from glutamic acid [[195]87]. As well as glutamic acid, the aspartic
acid content was also significantly reduced in plants exposed to D.
viscosa VOCs, while a significant increment of its derivative threonine
and isoleucine was observed. Previous studies demonstrated that
aspartic acid and the derivative lysine, threonine and isoleucine
represented building blocks for stress-specific proteins
[[196]88–[197]90], allowing to justify their fluctuation in treated
plants.
Interestingly, significant increase in leucine, valine concentration as
well as in isoleucine, observed in treated plants, generally occurred
under protein degradation, as in aged leaves before abscission or in
plant cell resting cultures [[198]91, [199]92].
Finally, oxidative stress, sucrose content reduction and strong
increase of serine level in leaf suggested that plants are experiencing
with the photorespiration rate increase as suggested by Bourguignon et
al. [[200]93]. In particular, serine was strongly involved in the
photorespiratory cycle [[201]93].
Plants exposed to D. viscosa VOCs reduced the levels of chlorophyll a
and b as well as carotenoids, which are known to be accessory pigments
with the important role as free radical scavengers protecting plants
from photoinhibition [[202]94]. The reduction of these pigments could
enhance the ROS-mediated photodegradation of chlorophyll and the
induction of photoinhibition [[203]94, [204]95]. Therefore, plants, in
order to protect the photosynthetic apparatus from photoinhibition,
could adopt two strategies: first, the thermal dissipation of the
energy in excess in the PSII antennae (nonphotochemical quenching), and
second, the ability of PSII to transfer electrons to various acceptors
within the chloroplast (photochemical quenching) [[205]96]. If plants
are not able to apply at least one of the two strategies,
photoinhibition occurs. The monitoring of some photosynthetic
parameters supported this hypothesis. In fact, plants exposed to D.
viscosa VOCs reduced the light adapted photosystem II efficiency
(Φ[II]) accompanied by an increase in the emission of non-regulated
energy dissipation (Φ[NO]) and a reduction of the ETR. Moreover,
treated plants showed a strong reduction in nonphotochemical quenching
(Φ[NPQ]), which suggested that plants were not able to dissipate the
energy in heat form [[206]97]. Finally, the progressive reduction of
the parameter Fv/Fm suggested a physical damage to the antenna complex,
probably due to the high presence of ROS and lipid peroxidation.
Taken together these results suggested that both photochemical and
biosynthetic phases of photosynthesis were directly affected by VOCs
[[207]97] and the confirmation was given by the sharp alteration of
sugars metabolism and, in particular, by the reduction in sucrose and
glucose content observed after treatment. In particular, the reduction
in glucose, sucrose content was already observed in Arabidopsis cells
exposed to oxidative stress [[208]98] and in Aegilops geniculate plants
treated with ferulic and p-coumaric acids [[209]99], largely known for
affecting photosynthesis [[210]100].
Conclusions
The results gave the first evidence of the allelopathic potential of D.
viscosa through a bioassay that mimed natural environmental conditions
of VOCs release. The effects of VOCs on plant-plant interaction and
communication were studied through a physiological and metabolomic
approach, for the first time.
D. viscosa VOCs have a strong inhibitory activity on both germination
and root growth of L. sativa as well as on lettuce adult plants, where
strongly affected their metabolism. High production of ROS accompanied
by lipid peroxidation, membrane leakage and water status alteration
were observed. Interestingly, plants tried to cope with this stress
activating metabolic pathways involved in osmotic adjustment and
radical scavenging activity. Nevertheless, lettuce plants exposed to
VOCs suffered severe damages in the photosynthetic apparatus. In
particular, damage to the antenna complex, pigment degradation,
reduction of light adapted photosystem II efficiency, reduction of both
electron transport rate and nonphotochemical quenching and increment in
chlorophyll a fluorescence were caused by VOCs exposure on lettuce
plants.
Taken together, these results suggested that plants exposed to D.
viscosa VOCs were subjected to a cascade of events involving oxidative
stress, photosynthesis machinery and process, water status, to which
plant tried to cope by activating defense mechanisms including change
in amino acidic metabolism.
In conclusion, D. viscosa is an allelopathic species that can induce
net changes in its natural environment affecting nearby plants, and
thus contribute to define plant community in the longer term.
Supporting Information
S1 Fig. Scheme of the in-vitro bioassay.
Schematic representation of the experiments carried on seeds, seedlings
and adult plants of lettuce.
(TIF)
[211]Click here for additional data file.^ (3.5MB, tif)
S1 Table. Quantification and statistical significance of the
metabolites identified in control and treated plants.
Chemical compounds isolated and quantified through GC-MS and
significantly affected by the exposition for 12 days to D. viscosa
volatiles. Data are expressed in nanograms/100mg of fresh plant
material.
(DOCX)
[212]Click here for additional data file.^ (17.1KB, docx)
S2 Table. Impact of Dittrichia viscosa volatiles on plant metabolism.
Result from “Pathway Analysis” carried on the concentrations of
metabolite identified in lettuce plants treated for 12 days with D.
viscosa VOC.
(DOCX)
[213]Click here for additional data file.^ (15.2KB, docx)
Acknowledgments