Introduction
Seagrass meadows rank amongst the most valuable ecosystems to
society in terms of the flow of services and values they support (Costanza et
al., 1997; Seitz et al., 2014). They form multidimensional habitats for
organisms directly participating in the trophic dynamics (Mazzella et al.,
1992) and are a primary food source for herbivores on coral reefs, lagoons,
and other shallow habitats (Orth et al., 2006). Seagrasses reduce sediment
resuspension and their roots enhance sediment accretion, thus maintaining
high water quality. Seagrass ecosystems also represent key sites for carbon
storage in the biosphere and are important as CO2 sinks (Mcleod et al.,
2011; Fourqurean et al., 2012; Pendleton et al., 2012; Pergent et al., 2012).
There is consensus that increased CO2 will not have negative effects on
seagrasses, which have even been predicted to extend their distribution,
locally replacing macroalgae (Harley et al., 2006). Nevertheless, there may be indirect effects on seagrasses associated
with increased CO2, as loss
of phenolic protective substances due to lowered pH (Arnold et al., 2012)
and light stress effects due to the modifications in the production and
biomass of epiphytic algae on seagrass leaves. Regarding epiphytes, opposing
light stress effects may be expected: shading, if non-calcifying epiphytes
respond positively to increased CO2 (Martínez-Crego et al., 2014),
or high light exposure, if calcifying epiphytes decline (Martin et al.,
2008). Experimental evidence for increased seagrass productivity as a
response to elevated CO2 levels is also inconclusive, and a recent
meta-analysis did not detect significant effects of ocean acidification on
seagrass photosynthesis (Kroeker et al., 2010). In a short-term experiment,
the seagrass Zostera marina was found to grow at increasing rates under CO2
enrichment (Thom, 1996). Similarly, Jiang et al. (2010) found an increase in
Thalassia hemprichii photosynthesis and leaf growth rate. Nonstructural carbohydrates increased
in belowground tissues, whereas in aboveground tissues the carbon content was
not affected by CO2 treatments. On the other hand, in a long-term
experiment, there was no effect of increasing CO2 levels on the
aboveground productivity of Zostera marina (Palacios and Zimmerman, 2007), as opposed to
belowground. Alexandre et al. (2012) showed that the net photosynthetic rate
of Zostera noltii was positively affected by the CO2 enrichment of the seawater, but
they did not observe an increase in leaf growth rates.
A problem with the above experimental approaches is that even the longest
experiments do not allow enough time for marine plants to adapt to high
CO2 conditions thus making it difficult to forecast how they will
perform in a future high CO2 ocean. This is the main argument to use
submarine volcanic vents as natural laboratories for the effects of CO2
as this gas is the main component of emissions and the emissions have been
happening for a long time (years to hundreds of years; Hall-Spencer et al.,
2008).
In the last decade, gene expression approaches have been frequently used to
assess the responses of marine organisms to ocean acidification (e.g., sea
urchins (Evans et al., 2013; Evans and Watson-Wynn, 2014), corals (Kaniewska
et al., 2012; Moya et al., 2012; Moya et al., 2015) and crustaceans (Harms et
al., 2014)) both in field or controlled/mesocosm conditions. Research into
natural gene expression variations within species in response to
environmental changes is growing (Granados-Cifuentes et al., 2013; Oleksiak
et al., 2002) due to its central role in the evolutionary adaptation
processes which act at population and at species level (Whitehead, 2006).
A highly promising approach is to investigate the expression of specific
genes involved in the response to stress (Granados-Cifuentes et al., 2013;
Oleksiak et al., 2002; Whitehead and Crawford, 2006). This approach will
provide insight for understanding how marine organisms maintain or
re-establish homeostatic metabolism in the face of varying physical or
chemical environmental variables (Ahuja et al., 2010). Organisms react to
environmental pressure by activating a series of conserved stress
enzymes/proteins, including redox
sensors (e.g., reactive oxygen species (ROS) sensors, antioxidants and
detoxification systems), macromolecule damage sensors (e.g., stress-inducible
heat shock proteins – HSPs) and/or condition-specific proteins that help to
adjust the cellular physiology and metabolism protecting against cell damage
or death.
Here we analyzed the expression levels of selected genes of the seagrass
Posidonia oceanica in the vicinity of submerged volcanic vents located at the islands of
Ischia and Panarea (Italy), and compared them with those from control sites
away from the influence of the vents. Reverse-transcription quantitative polymerase chain reaction
(RT-qPCR) was used to characterize expression levels of genes involved in
stress responses, antioxidant activity, metal-related responses and defense
processes in P. oceanica in order to understand whether stress defense mechanisms are
activated in the vicinity of submarine volcanic vents. Our hypothesis is
that unknown factors are causing metabolic stress in P. oceanica in the vicinity of
natural CO2 vents, which may confound the putative effects attributed
to CO2 enrichment only.
In our analysis, target genes have been selected to include possible
mechanisms that P. oceanica may activate in face of abiotic stressors (Mittler, 2006).
We selected heat shock proteins (HSPs), genes from the primary metabolism
(the first and second line of defense), antioxidants and other stress-related
enzymes. HSPs are molecular chaperones that can be involved in protein
folding/unfolding, and degradation of misfolded or aggregated proteins
(Sorensen et al., 2003). They are activated in response to various
environmental stress factors (e.g., heat, hypoxia, UV radiation, CO2
enrichment, chemical exposure; Feder and Hofmann, 1999; Lauritano et
al., 2015; Sorensen et al., 2003). From the first line of defense we
analyzed a multixenobiotic resistance transporter or ATP-binding cassette
protein (MXR/ABC), which is involved in the efflux of a large number of
structurally and functionally diverse, moderately hydrophobic compounds,
including anthropogenic pollutants and natural toxins (Bard, 2000). The
second line of defense is characterized by detoxification reactions, such as
oxidation, reduction, hydrolysis, hydration and de-halogenation of compounds
to detoxify (e.g., cytochrome P450, or CYP450; Regoli and Giuliani, 2014). The
second line of defense also includes aldehyde dehydrogenases (ALDHs) that
detoxify a wide variety of endogenously produced and exogenous aldehydes
catalyzing their oxidation to the corresponding acids (Marchitti et al.,
2008). Reactive oxygen intermediates (ROIs), such as the superoxide anion,
hydrogen peroxide and the hydroxyl radical, are intermediates of many
physiological enzymatic reactions (e.g., mitochondrial respiration and redox
enzymes, such as uncoupled nitric oxide synthase, cytochrome P450 isoforms,
Lubos et al., 2011). They function as a signal for the activation of
stress responses and are rapidly converted to less reactive forms. They are
produced in higher amounts under stress conditions, such as drought stress,
desiccation, heat shock, heavy metals, air pollutants, nutrient deprivation,
mechanical stress and high light stress (Mittler, 2002). The accumulation of
high quantities of ROIs can be very damaging to DNA, RNA and proteins and may
activate programmed cell death (PDC). The free radical detoxification
enzymes catalase (CAT), superoxide dismutase (SOD), glutathione
peroxidase (GPX), ascorbate peroxidase (APX) and scavenger molecules such as
glutathione were analyzed here.
The over-accumulation of ROIs when antioxidant/defense systems are not able
to cope with stress may induce lipid peroxidation and PDC (Mittler, 2002).
This is the reason why we also analyzed the expression of a lipoxygenase
(LPX) involved in lipid peroxidation and a death-specific protein (DSP5)
involved in cell death (Bidle and Bender, 2008). Other enzymes analyzed here
have also antioxidant/protective properties. This is the case of
Peroxiredoxin Q, involved in free radical detoxification processes, and
germin-like proteins, involved in many different processes such as metal
stress response, fungal attack, osmotic regulation, cell wall restructuring
and superoxide dismutase activities (Carter and Thombur, 1999; Lamkemeyer et
al., 2006). In addition, other proteins/enzymes have been selected for their
involvement in heavy metal responses/detoxification (Hussain et al., 2004;
Ricachenevsky et al., 2013).
P. oceanica is endemic to the Mediterranean, providing a fundamental structural role and
key ecological services (Cullen-Unsworth et al., 2014). It is therefore
essential to understand which kinds of stresses the species are susceptible to
and how it responds to them. This is the first study analyzing key protein
activation in this species representing the first step for using
stress-related genes of seagrasses as indicators of environmental pressures
in a changing ocean.
Methods
Sampling
The study has been performed in the vicinity of submarine volcanic vents at
the islands of Ischia and Panarea, Tyrrhenian Sea, Italy. In both cases, the
hydrothermal vents are characterized by the emission into sea water of
thermal waters and gases, mainly CO2, inducing changes in the chemical
composition of the water column and associated community (Italiano and
Nuccio, 1991; Kerrison et al., 2011).
Ischia: The study was performed in a very small fringe of a
Posidonia oceanica meadow close to vent areas off the Castello
Aragonese isle (Ischia; 40∘43.849′ N, 13∘57.089′ E;
Naples, Italy). At this site, underwater CO2 vents occur in the
shallowest rocky bottoms, and a pH gradient is formed (Hall-Spencer et al.,
2008). Archaeological evidence suggests that vent sites around Castello
Aragonese in Ischia were above sea level in the fourth century BC, but that
the region underwent a tectonic lowering (bradyseism) and was flooded by
about AD 130–150 (de Alteriis and Toscano, 2003; Zucco, 2003). Thus, at
these sites, subsurface vent activity can be dated back to about
1800–1900 years (Lombardi et al., 2011). Three individual shoots of
P. oceanica were randomly collected at a control site at ambient pH
in Ischia (S1, about 8.14 pH) and at a site of low pH (S2, about 7.83 pH)
in dense and continuous meadows. Three additional shoots were collected from
a very isolated and confined site (about 10 m2) of P. oceanica
in conditions of extremely low pH (S3, about 6.57 pH). The depth range
varies from 3.5 to 1 m along the pH gradient.
Panarea: The CO2 vents of Panarea originated from recent volcanic
activity that occurred in 2002, which resulted in a series of gas bursts (Tassi et al.,
2009). Sampling was conducted at two separate sites off the Island
(38∘38′00′′ N, 15∘04′00′′ E) – a control site with pH 8.17 (the islet of Bottaro) and a relatively acidified site with pH 7.91 (Formiche
shoals), both at 12 m depth. At each sampling site, six adult shoots of
P. oceanica were collected.
For both sites, tissue from the youngest fully mature leaves of the shoots
(usually the second-rank leaf) was collected and rapidly cleaned from
epiphytes with a razor blade, towel-dried and immediately stored in
RNAlater® tissue collection solution (Ambion, Life Technologies).
Samples were then transported to the laboratory, preserved one night at
4 ∘C and stored at -20 ∘C until RNA extraction.
Sample genotyping
Samples collected for RT-qPCR analysis were also genotyped using
species-specific microsatellite markers. About 50–70 mg of dried
tissue from individual samples was ground in a Mixer Mill MM300 (Qiagen).
Subsequent DNA extraction was carried out using the
NucleoSpin® 96 Plant II kit (Macherey-Nagel) as in Tomasello
et al. (2009). Individual multilocus genotypes were assessed by a total of
29 microsatellites (SSRs): 13 P. oceanica-specific anonymous loci that are putatively neutral
and widely employed to assess neutral genetic variation (e.g., Procaccini and
Waycott, 1998; Alberto et al., 2003; Migliaccio et al., 2005; Serra et al.,
2010) and 16 loci representing a subset of the new EST-linked
microsatellites developed from two existing P. oceanica EST libraries (Arranz et al.,
2013). PCR conditions were designed based on Arranz et al. (2013). Multiplex
amplification reactions were performed using multiplex PCR buffer (Qiagen
Multiplex PCR Master Mix).
PCR products were analyzed on an automated capillary electrophoresis
sequencer (3730 DNA analyzer, Applied Biosystems). Electropherogram profiles
were visualized and analyzed using the software PeakScanner (Applied
Biosystems). Individual multilocus genotypes were determined using the
software Gimlet (Valière, 2002).
RNA extraction and cDNA synthesis
Portions of seagrass leaf tissue were ground into a fine powder using a mortar
and pestle and liquid nitrogen. About 100 mg of powered tissue was
used for the RNA extraction using an Aurum™ Total RNA Mini Kit (BIO-RAD)
as in Mazzuca et al. (2013). After lysis solution, samples were homogenized
using a Qiagen TissueLyser and tungsten carbide beads (3 mm) (Qiagen) for
3 min at 20.1 Hz. RNA quantity was assured by a NanoDrop ND-1000 UV–visible
spectrophotometer (NanoDrop Technologies), monitoring the absorbance at 260 nm; purity was determined by monitoring the 260 / 280 nm and 260 / 230 nm ratios
using the same instrument. Both ratios were about 2.0. All samples were free
of protein and organic solvents used during RNA extraction. RNA quality
was evaluated by agarose gel electrophoresis that showed intact RNA, with
sharp ribosomal bands. Total RNA (500 ng) was retro-transcribed into cDNA
with the iScript™ cDNA synthesis kit (BIO-RAD) following the standard
protocol, using the GeneAmp PCR System 9700 (Perkin Elmer). The reaction was
carried out in 20 µL final volume with 4 µL 5×
iScript reaction mix, 1 µL iScript reverse transcriptase and
DNase-free H2O. The mix was first incubated for 5 min at 25 ∘C,
followed by 30 min at 42 ∘C and finally heated to 85 ∘C
for 5 min.
Oligo design and PCR (polymerase chain reaction) optimization
Primers for genes of interest (GOI) were designed considering sequences from
the seagrass EST database Dr. Zompo (Wissler et al., 2009), unpublished
sequences from the transcriptome of P. oceanica (D'Esposito et al.,
2015) or from the generic online database GenBank (http://www.ncbi.nlm.nih.gov/genbank/; Table 2). Primers were designed
using the software Primer3 v0.4.0 (http://frodo.wi.mit.edu/primer3/).
Table 1 lists selected GOI, their functions, primers' sequences and amplicon
sizes. Primers were optimized as in Serra et al. (2012). The sequences are
deposited in GenBank under the accession numbers shown in Table 1.
List of selected genes of interest, with their
abbreviations and functions.
Abbreviation
Gene name
Function
HSP90
HSP90
Stress protein
DNAJ
Chaperone protein DNAJ
Stress protein
HSP83
HSP83
Stress protein
OzSP
Ozone stress protein
Stress protein
DehSP
Dehydra stress protein
Stress protein
SHSP
SH stress protein
Stress protein
HSFA5
Heat shock factor A5
Heat shock protein transcription factor
LBP
Luminal binding protein LBP
Stress protein
ABC
ABC_MDH
Transporter protein
CYP
Cytochrome P450
Primary metabolism/detoxification
ALDH
Aldehyde dehydrogenase
Primary metabolism/detoxification
CAT
Catalase
Free radical detoxification
SODCP
Superoxide dismutase [Cu–Zn], chloroplastic
Free radical detoxification
CSD1
Cu–Zn superoxide dismutase, cytosolic
Free radical detoxification
FSD
Chloroplast iron superoxide dismutase
Free radical detoxification
MSD
Manganese superoxide dismutase
Free radical detoxification
GST
Glutathione S-transferase
Antioxidants
GPX
Glutathione peroxidase
Antioxidants
GSH-S
Glutathione synthase
Antioxidants
GR
Glutathione reductase
Antioxidants
AR
Ascorbate reductase
Antioxidants
APX
Ascorbate peroxidase, microsomal
Antioxidants
CAPX
Ascorbate peroxidase, chloroplastic (stromal)
Antioxidants
Prx Q
Peroxiredoxin Q
Antioxidants
GLP
Germin-like protein
Antioxidants
DSP5
Death-specific protein 5
Apoptosis
LPX
Lipooxygenase
Lipid metabolism
FtsH2
ATP-dependent zinc metalloprotease
Metal-related gene
HMA
Heavy metal transport detoxification domain
Heavy metal domain
NRAMP1
Root-specific metal transporter
Heavy metal transporter
HMATPase
Heavy metal p-type ATPase
Heavy metal ATPase
HMATPase5
Heavy metal ATPase 5 protein gene
Heavy metal ATPase
MT3
Metallothionein-3
Heavy metal stress response
Fe-SP
Iron-stress-related protein
Heavy metal stress response
MTP
Metal tolerance protein
Heavy-metal-related gene
Best reference gene (RG) assessment
In order to analyze the expression levels of specific GOI, a panel of seven
putative reference genes (RGs) was first screened to find the most stable
genes in the seagrass P. oceanica at both natural CO2-enriched sampling sites. The
screened panel included the eukaryotic initiation factor-4A (eIF4A) (F
5'-TTCTGCAAGGGTCTTGACGT-3' and R 5'-TCACACCCAAGTAGTCACCAAG-3'; E= 1.85;
R2= 0.99) as well as the ones already published in Serra et al. (2012): ubiquitin
(UBI), ribosomal protein L23 (L23), elongation factor 1-alpha (EF1A),
glyceraldehyde 3-phosphate dehydrogenase (GAPDH), ribosomal RNA 18S (18S)
and ubiquitin-conjugating enzyme (NTUBC2). Three different algorithms were
utilized to identify the best RGs in our experimental design: BestKeeper
(Pfaffl et al., 2004), geNorm (Vandesompele et al., 2002) and NormFinder
(Andersen et al., 2004).
Reverse-transcription quantitative polymerase chain reaction
(RT-qPCR)
Expression level analyses were then performed for specific GOIs related to
antioxidant activity, stress and detoxification processes (Table 1 and Table
1S). Primer efficiencies were calculated for each oligo pair generating
standard curves with five dilution points by using the cycle threshold (Ct)
value versus the logarithm of each dilution factor and using the equation
E = 10-1/slope. RT-qPCR was performed as in Dattolo et
al. (2014). Control sites (S1 pH 8.14 and 8.17, for Ischia and Panarea,
respectively) were used as reference conditions. Statistical analyses were
performed using the statistical software Prism v4.00 (GraphPad Software).
Statistical significant gene regulation was considered at
p < 0.05.
Results
Best reference gene (RG) assessment for Ischia and Panarea
According to the mathematical approach of BestKeeper, the most stable genes
were L23, GAPDH and UBI for Ischia and 18S, L23 and UBI for Panarea (Figs. S1a
and S2a in the Supplement). NormFinder indicated elF4a, NTUBC2 and UBI for Ischia and L23,
NTUBC2 and EF1A for Panarea as best candidate reference genes (Figs. S1b
and S2b in the Supplement). According to geNorm analysis, the two most stable genes were eIF4A
and NTUBC2 in Ischia (Fig. S1c in the Supplement) and L23 and UBI in Panarea (Fig. S2c in the Supplement). All
these genes were below the threshold M value of 1.5, which indicates that a
gene can be considered suitable as a RG (Figs. S1c and S2c in the Supplement). The approach
implemented in geNorm also allowed inferring the minimum number of necessary
genes to be used as RGs in given data set. Pair-wise variation values were
always < 0.15 at both sampling sites (V value; Figs. S1d and S2d in the Supplement),
indicating that only two genes were sufficient for the analysis.
Nevertheless, when results were not consistent among the different
approaches utilized, we also included a third RG in the analysis. The best
RGs identified for each statistical approach and utilized for normalizing
GOI expression levels at the two sampling sites were L23, elF4a and NTUBC2
in Ischia and L23, 18S and UBI in Panarea (Table 2).
Best reference genes as given by BestKeeper, NormFinder and geNorm
analyses, for each sampling location (Ischia and Panarea). Genes are ranked
from the most stable (in bold) to the least stable.
Rank
BestKeeper
NormFinder
geNorm
Ischia (S2 and S3)
1
L23
elF4a
elF4a-NTUBC2
2
GAPDH
NTUBC2
UBI
3
UBI/elF4a/NTUBC2
EF1A
EF1A
4
EF1A
UBI
GAPDH
5
18S
L23
L23
6
GAPDH
18S
7
18S
Panarea
1
18S
L23
L23/UBI
2
L23
NTUBC2
NTUBC2
3
UBI/NTUBC2
EF1A/UBI
18S
4
elF4A
18S
EF1A
5
GAPDH
elF4A
elF4A
6
EF1A
GAPDH
GAPDH
Reverse-transcription quantitative polymerase chain reaction
(RT-qPCR)
P. oceanica samples collected for gene expression analyses were previously genotyped
using microsatellite markers, assuring that there were at least three distinct
genotypes for each gene expression replicate. Results obtained from all
distinct genotypes, using the site with normal pH as control, show that a
different gene category or specific gene functions have different behavior
at the two sampling sites.
Opposite patterns of expression levels between the two sites were observed
for many HSPs (Fig. 1a). At Ischia, many HSPs were significantly
down-regulated. In particular, HSP90, HSP83 and the transcription factor
HSFA5 were 2-fold down-regulated at both site S2 and S3 (p < 0.001),
while DNAJ was significantly down-regulated only at S3 (p < 0.001). However, HSP83 (p < 0.05) and DehSP (p < 0.01)
were significantly up-regulated at the Panarea site (Fig. 1a). The other
HSPs did not show significant changes.
Expression levels of P. oceanica heat shock
protein (a) and primary metabolism genes (b) from plants
collected at Ischia (S2 and S3 sites, with pH 7.83 and 6.57,
respectively) in relation to the control site
(pH 8.14), and at Panarea (pH 7.91) in relation to its control site
(pH 8.17).
For the primary metabolism genes, ABC and CYP were significantly up-regulated
at the Panarea site (p < 0.01 for both), while CYP was
down-regulated only at the Ischia S2 site (p < 0.01). ABC did not
show significant expression level changes in Ischia, and ALDH did not show
significants changes at both Ischia and Panarea
(Fig. 1b).
Regarding genes involved in the antioxidant response (Fig. 2a), CAT did not
show significant changes in either Ischia or Panarea, while among the SOD
isoforms analyzed (SODCP, CSD1, FSD and MSD), only the Cu–Zn chloroplastic
one (SODCP) was down-regulated at the Ischia S3 site (p < 0.001)
and up-regulated at Panarea (p < 0.01). For the
glutathione-related enzymes (GST, GPX, GSH-S and GR), GST was significantly
down-regulated only at the Ischia S3 site (p < 0.001), GPX was
up-regulated at all sites (p < 0.05 for Ischia S2,
p < 0.01 for Ischia S3 and Panarea), GSH-S did not show
significant variations, and GR was down-regulated at both Ischia sites
(p < 0.001 for both) and up-regulated at the Panarea site
(p < 0.01). Regarding the ascorbate-related enzymes (AR, APX3 and
CAPX), AR did not show significant changes, APX3 was only significantly
down-regulated at the Ischia S2 site (p < 0.001), and CAPX was
down-regulated at the Ischia S2 site (p < 0.001) and up-regulated
at Panarea (p < 0.01). Finally, Prx Q was up-regulated at all the
sites (p < 0.05), while GLP was down-regulated at both the Ischia
S3 site and the Panarea site (p < 0.001). DSP5 and LPX did not change significantly.
Expression levels of P. oceanica antioxidant (a) and
heavy-metal-related genes (b) from plants collected at Ischia (S2 and S3
sites with pH 7.83 and 6.57) in relation to the control site (pH 8.14), and
at Panarea (pH 7.91) in relation to its control site (pH 8.17).
Control sites are represented by x axis.
For the metal-related genes (Fig. 2b), HMA was down-expressed at both Ischia and Panarea
(p < 0.001) and NRAMP1 only at the Ischia sites
(p < 0.001 for S2 and p < 0.01 for S3), while
HMATPase5 was down-regulated at S2 and up-regulated at S3
(p < 0.05 for both). The other genes did not change
significantly.
Discussion
To our knowledge, there are no published data on gene expression patterns in
seagrasses in the vicinity of submarine volcanic vents. Here we analyzed the
expression of 35 genes of the Mediterranean engineering seagrass species
Posidonia oceanica, in high-CO2, low-pH sites, in relation to control sites. Genes involved in
different phases of plant response to stress were selected. Fifty-one percent
of genes analyzed in this study showed significant expression changes at
either the two sites of Ischia, at Panarea, or at both locations (summarized
in Fig. 2). A consistent gene response at the three sites was observed for
three genes – heavy-metal-associated (HMA) domain, glutathione peroxidase
(GPX) and peroxiredoxin Q (Prx Q). HMA was significantly down-regulated at
both Ischia and Panarea, showing that plants do not increase the synthesis of
heavy metal detoxification proteins in proximity to volcanic emissions
compared to the control site. This was further supported by the consistent
pattern observed at both Ischia and Panarea of the down-regulation of most
metal detoxification genes examined, suggesting that the putative heavy metal
emissions from the vents at Ischia and Panarea do not cause stress on
P. oceanica plants. The bioavailability of heavy metals, which
depends on pH and redox potential, may be low at the sites where plants grow,
as Vizzini et al. (2013) pointed out for the volcanic vents of the island of
Vulcano, Italy.
Glutathione peroxidase (GPX) and Peroxiredoxin Q (Prx Q), involved in free
radical detoxification, were significantly up-regulated at both sites in
Ischia and Panarea in relation to control sites, suggesting that P. oceanica plants
are activating similar antioxidant protective mechanisms. Peroxiredoxins are
ubiquitous thioredoxin- or glutaredoxin-dependent peroxidases, the function
of which is to destroy peroxides (Rouhier et al., 2004), while GPX is
important for reducing cytotoxic hydroperoxides (Lubos et al., 2011). In
contrast, the activity of another antioxidant gene, the germin-like protein
(GLP; Gucciardo et al., 2007), was down-regulated at both sites in Ischia
(although in S2, pH 7.83, it was not significant) as well as in Panarea,
indicating that this antioxidant defence system was not active in plants at
the vicinity of vents.
Many contrasting patterns in the expression of the studied genes were
observed between Ischia and Panarea, indicating that different environmental
stressors are at play. Fourteen out of the 18 genes exhibiting significant
expression changes were different between Panarea and Ischia. Unlike in the
control, plants collected in the Panarea acidified site activated antioxidant
enzymes such as SODCP, GR, CAPX, and detoxification proteins, such as CYP and
ABC. Moreover, and by contrast with the Panarea plants, for the plants
collected in the Ischia acidified sites these enzymes were down-expressed or
did not show any significant change. Most of these genes are also activated
after various types of biotic and abiotic stressors in different plants
species (see Vranovà et al., 2002, for a review). Our results indicate
that, in contrast with Ischia, P. oceanica at Panarea faces
stressors near the vents that result in the production of reactive oxygen
species that trigger antioxidant responses. There are only few published
studies on the occurrence of antioxidant responses in seagrasses, mostly
based on indirect observations of photosynthetic parameters derived from
chlorophyll a fluorescence (Ralph et al., 1998; Campbell et al., 2006), and
our work is the first one to show the expression of genes associated with the
antioxidant responses in P. oceanica.
The activation of heat shock protein genes such as HSP83 and DehSP in Panarea
and the significant down-regulation of HSP90, DNAJ, HSP83 and HSFA5 in Ischia
plants is also worthy of attention. HSPs play an essential role as molecular
chaperones by assisting the correct folding of nascent and stress-accumulated
misfolded proteins, and by preventing their aggregation. HSPs' induction and
synthesis are not only a response to high temperature, which does not occur
in Panarea, but also to many different types of stress, including exposure of
cells to toxins or nitrogen deficiency (Santoro, 2000). As HSPs are very
sensitive to even minor damage, they are suitable as
an early-warning bio-indicator of cellular hazard (Bergmann et al., 2010;
Gupta et al., 2010). Our observation that HSPs were down-regulated at Ischia
and up-regulated at Panarea supports the overall finding that relevant
environmental differences exist between the two volcanic sites. An
alternative hypothesis is that P. oceanica gene expression responses
at Panarea are still going through the initial phase of acclimation, whereas
at Ischia the species has already adapted to existing environmental
conditions. Thus, the natural gene expression differences revealed in this
work may be a component of the species homeostatic evolutionary compensation.
The volcanic vent in Ischia could in fact be as old as about 2000 years, as
indicated by archaeological evidence (Lombardi et al., 2011), whereas the
vent in Panarea is only about 10 years old. It is quite possible that some of
the Ischia genotypes of P. oceanica have been there since the onset
of the volcanic vents as it has been recently revealed that the longevity of
this species can be up to thousands of years (Arnaud-Haond et al., 2012).
This is the first time that a gene expression study has been performed in
marine plants in the vicinity of submarine volcanic vents, which are generally assumed to be good natural laboratories for investigating the effects of increased CO2 and ocean acidification on marine organisms. In our analysis, we identified a subset of genes that were
coherently expressed at both sites and that could be further explored for
suggesting their use as early-warning indicators of low-pH conditions in
photosynthetic marine organisms. Nevertheless, caution should be taken when
using only natural volcanic vents as a proxy for future ocean acidification
scenario, and experimental work in controlled laboratory conditions is
necessary to unambiguously test organismal response to increased CO2 and
low-pH conditions. Our results call for careful consideration of other
factors that can cause stress to seagrasses and other organisms near the
vents and that may confound the effects of CO2 and acidification. In
order to clarify/predict seagrass stress responses to environmental stimuli,
the study of general stress-coping, stress-avoiding, and tolerance mechanisms
is needed, as is the analysis of more than one gene category.