Introduction
During
photosynthesis, the photoreaction drives the cyclic
electron transport of photosystem I (PSI) (Evans and Vogelmann
2010) The transference of photosynthetic electrons
into cyclic electron transporters is called CEF. (Takahashi et al. 2009;
Huang et al. 2015) .The PSI cyclic electron transfer has two known
pathways: The main pathway depends on proton gradient regulatory protein 5
(PGR5) (Munekage et al. 2002), while the
secondary pathway is regulated by a chloroplast NADH dehydrogenase-like (NDH)
complex (Eva et al. 2000). Compared with linear
electron transfer, cyclic electron transport only requires PSI to accompany
cytochrome b6/f complex during photochemical reactions. This is then
accompanied by proton transfer from the stroma to the lumen on the thylakoid
membrane (Okegawa et al. 2007), which generates a proton
gradient (Δ pH) (Shikanai 2007) across the
thylakoid membrane and drives ATP synthesis; however, this pathway does not
produce NADPH is present. This mechanism has long been found in light-energy
utilizing eukaryotes and enables plants to cope with fluctuating and
high-light environment (Munekage et al. 2004;
Tikkanen et al. 2010; Sugimoto et al. 2013; Kono et al. 2014).
Currently, the role of the PGR5-dependent CEF
in photosynthesis regulation has been widely studied. And it is generally
acknowledged that PGR5-dependent CEF is the main pathway of the photosynthetic
CEF. However, its magnitude is difficult to be accurately determined. A common
method to quantify the PGR5 CEF is in fact measuring the re-reduction rate of
P700+ after illuminating leaves with weak red light (Munekage et al. 2004; Okegawa et al. 2007).
However, this method has several disadvantages: 1) In leaves adapted to weak
far-red/direct red-light exposure, P700 will undergo incomplete oxidation, thus
not reaching its full potential; 2) PSІ of the thylakoid might not be
sufficiently activated under weak far-red light. For example, when a leaf is
illuminated from the adaxial side, upper chloroplasts are light saturated,
while lower chloroplasts are not (Terashima et al.
2009). Previous studies demonstrated that the re-oxidation rate of P700
obtained by direct light was lower than that obtained by first dark adaptation
and then light (Sergi et al. 2005). This is
the reason why far red light can fully oxidize PSІ but not PSII. After
dark adaptation, PSІ can be fully oxidized under far-red light. When the
far red light is tuned off, PSIIs only transfer few electrons to reduce P700+,
therefore the P700+ reduction is mainly caused by CEF (Burrows et
al. 1998).
Mulberry has been widely concerned in recent years. Mulberry leaves can
eliminate bacteria in the body and play an anti-inflammatory and bactericidal
role and so on. The signal amplitude of P700 determined by M-PEA can be
evaluated to determine the PGR5 CEF size. However, most of the
experiments conducted in China and abroad directly observed the P700 oxidation
level after illumination with far-red light (Fan et al. 2002;
Munekage et al. 2008; Suorsa et al. 2012; Sugimoto et al.
2013). Woody plants (mulberry) were used as material and the method was
improved based on the work of predecessors (Zhong et
al. 2018). Before exposing plants to far red-light radiation, plants were
dark adapted for 30 min. we determine the influence of different intensities of
far red light and different exposure durations on the PGR5 cyclic electron
transport. At the same time, the mathematical model and 3D graphics were
established, the response surface was observed, and the experiment was
optimized, to acquire a suitable optimization method for the determination of
the PGR5 CEF around PSI. This will provide information for future evaluation of
mulberry photosynthetic efficiency under stress.
Materials and Methods
Plant material and culture conditions
Mulberry plants (Morus alba, one-year-old seedlings) were used as
experimental materials, and were provided by the sericulture research institute
of Heilongjiang province. Mulberry seedlings were cultured in a mixture of lime
and vermiculite (volume ratio of 2:1) and were transplanted to the mixing
matrix when plants had a length of 50 cm and growth
chambers with the following environmental conditions: 12 h photoperiod,
temperature of 25°C/20°C (day/night) and PPFD of 600 µmol m-2 s-1.
Determination and Model
of the P700 absorbance change
A
light-intensity-time dependent experiment was determined by a plant efficiency
meter M-PEA (Hansatech, Norfolk, U.K.) and conducted to study the
PGR5-dependent CEF: the intensity of far red light was 20, 50 and 80%, which
were named LFR, MFR and HFR, respectively (the intensity of 100% is 1000 μmol m-2 s-1
λ= 735 ± 15 nm). The exposure times of far-red light were 20 s, 40 s, 60
s, 80 s, and 100 s. The time setting of the second curve is identical to that
of the first curve. The data in the light intensity and time free combination
analysis were manually quantified (Zhong et al.
2018).
The redox kinetic curve of P700+ was divided into four steps:
1) after dark adaptation of the leaves for 30 min, plants were irradiated with
far-red light to oxidize P700. This process only used a proton gradient as the
main driving force to promote the formation of ATP; therefore, the P700 signal
would significantly decrease; 2) the far-red light exposure was stopped, and
the P700 signal was restored to the level in dark due to the electron input
from CEF. 3) irradiate plants with far-red light with the same intensity that
was used during the first stage; 4) finally, a 1 s-saturated far-red light
exposure (100%, maximum intensity 1000 μmol
m-2 s-1 λ= 735 ± 15 nm) was used
to saturate plants and an effective supplementary light (white light, 5000 μmol m-2 s-1)
was turned on synchronously to determine the maximum signal (Pm) of P700 (Fig.
1A). The second section is the reduction degree of P700+, which can
be used as a qualitative representation of the size of CEF in the PGR5 pathway.
To avoid problems caused by the light absorbance difference among different
species and varieties, the ratio of the reduction degree of P700+
and Pm was used to characterize the PGR5 cyclic electron transport. Fig. 1B
shows an enlarged model of the P700+ reduction degree /Pm.
Equation model and
student-dependent residuals of the relationship between PGR5-dependent CEF and
each variable
Dark interval time between far-red illuminations at step two (20 s, 40 s,
60 s, 80 s, 100 s), far-red light illumination time at step one (20 s, 40 s, 60
s, 80 s, 100 s), far red-light intensity at step one
(20%, 50%, 80%) are independent variables, and CEF is the dependent variable. Box-behnken module is used to screen
out reasonable models. The
student-dependent residua are automatically given by the software.
Methods of data
processing and statistics
SPSS (22.0)
software was used for the statistical analysis of the data. Charts were plotted
with Excel (2016) and Origin 9.1(Origin Lab., US) was adopted to visualize a
three-dimensional (3D) plot of the light intensity and exposure time. One-way
analysis of variance (ANOVA) and least significant difference (LSD) were used
to compare the differences between groups. Box-Behnken of Design-Expert 8.0.6
Trian (Stat-Ease, U.S.) was used to simulate both the response surface and equation,
and to optimize the experimental scheme (Liu et al. 2011).
Results
Effects of different exposure time on signal oxidation of mulberry leaf
P700
Fig. 2A shows that the P700+
reduction degree under LFR (20%) oxidation is highest, followed by
MFR (50%) and HFR (80%). When far-red light was turned off after 20 s, 40 s,
60 s, 80 s, 100 s, respectively, LFR was higher than MFR and HFR. As shown in Fig. 2B, LFR exposure for 40 s and the time to
turn off the far-red light were not significantly related to the reduction
degree of P700+, and the difference between each point was not
significant. HFR exposure for 40 s showed no significant difference between
each point; however, the reduction degree of P700+ fluctuated. MFR
exposure for 40 s, the reduction degree of P700+ increases first and
then decreases. As shown in Fig. 2C, under irradiation for 60 s with
different intensities of the far-red light, the light intensity curves of each
intensity tended to flatten out and the difference between each point was not
significant with increasing closing time. The HFR curve showed a large
fluctuation range, with the highest reduction degree of P700+,
followed by MFR and the lowest was found for LFR. The curves of far-red light
irradiation for durations of 80 s and 60 s were similar. While the MFR and LFR
curves tended to flatten, HFR fluctuated (Fig. 2D). Under HFR exposure, the
P700 signal intensity was significantly higher than that of the other
intensities. The result of far red-light irradiation time of 100 s is the same
(Fig. 2E).
%201692-1698_files/image002.jpg)
Fig. 1 a): Kinetic curve of P700+ REDOX; b) Dark reduction kinetics curves of
P700+ with far red light off.
%201692-1698_files/image004.jpg)
Fig. 2: Effects of different closing time
and different percentage light intensity on P700 signals in 20 s, 40 s, 60 s,
80 s and 100 s (Correspond to Figure A, B, C, D
and E respectively) far-red light
irradiation in the oxidation stage. Where LFR is low intensity far-red
light (20%); MFR is medium intensity far-red light (50%); HFR is higher
intensity far-red light (80%). The time nodes of turning off the action light
were divided into 20 s, 40 s, 60 s, 80 s and 100 s. Data are means with error
bars indicating SD (n = 3 or 4). Different letters indicate significant
differences (P < 0.05) and very
different (P < 0.01) among the
treatments and refer to each subset of data within each sampling date. The same
below
%201692-1698_files/image006.jpg)
Fig.
3 a): Comparison
of the maximum P700+ reduction degree obtained by the far-red light irradiated
at different seconds in the first stage; the time nodes of irradiated far-red
light were divided into 20 s, 40 s, 60 s, 80 s and 100 s. b) Time - light intensity dependent 3D surface view. The redder the color, the
greater the value. FROn: Time to turn on the far-red light; FRoff
: Turn off the time of far-red light; HFR: high intensity far-red light;
MFR: medium intensity far-red light; LFR: low intensity far-red light. The same
to below
%201692-1698_files/image008.jpg)
Fig. 4 a): Tobacco light intensity-time
dependent test 3D layer; b) Mulberry
light intensity - time dependent test 3D layer
The optimal combination
of the P700+ reduction degree under different oxidation times
According
to the presented results, the following combinations of maximum P700+
reduction degree were obtained: 20 s LFR irradiation,
followed by darkness for 80 s (group 1); 40 s HFR irradiation, followed by
darkness for 60 s (group 2); 60 s HFR irradiation, followed by darkness for 80
s (group 3); 80 s HFR irradiation, followed by darkness for 80 s (group 4); 100
s HFR irradiation, followed by darkness for 20 s (group 5) (Fig. 3A). The
reduction degree of P700+ was smallest for group 1, while those of
groups 2–5 were higher compared with group 1. The maximum combinations of the
last four groups were all exposed to HFR, and no significant differences were
found between them. The 3D surface diagram (Fig. 3B),
which was simulated for each data point, shows that PGR5-dependent CEF under
HFR was the smallest, while LFR achieved the largest before and around 20 s of
the far-red light exposure; MFR was the largest.
Relationship model between PGR5-dependent CEF and each variable
Table S10 and Table S9 (supplementary
material) show the ANOVA comparison between the PGR5 CEF and various
fitting models with different parameters obtained by Design-Expert 8.0.6 Trian.
Table S8 (supplementary material) shows the results of
the confidence analysis of the quadratic model. The mean
square and test results of variance analysis of different models in Table S10
indicate that the fitting effect of the quadratic equation model is recommend.
Table S9 compares the complex correlation coefficients and the results of the
mean square error and folk square difference of each polynomial model that can
be fitted. The result indicated the quadratic polynomial model as optimal. Table S8 shows the results of the confidence analysis of
Design-Expert 8.0.6 Trian on the quadratic polynomial model and various
influencing factors of the model. The results showed that the effect of
fitting experimental data by the quadratic polynomial model is significant.
Furthermore, the interaction between far-red light and light intensity among
its parameters had the highest influence on PGR5 CEF. Under the interaction of
all three factors, their order of influence on CEF followed: (open far-red
light time * light intensity) > (open far-red light time * close far-red
light time) > (close far-red light time * light intensity). From the
perspective of a single factor, light intensity had the strongest impact on
CEF.
Quadratic equation
model and student-dependent residuals of the relationship between
PGR5-dependent CEF and each variable
Equations (1) and (2) present the quadratic
equation models of PGR5-dependent CEF. Each factor is expressed in factor code
form and actual factor value form. Fig. 2s (Supplementary Material) shows the
student-oriented residual distribution of the fitting model, which shows that 97% of the points of the residual are distributed between
-2 and 2, and lie almost on a straight line; consequently, the model
achieved a good fit.
Final equation in terms of coded factors
CEF = + 1.26
+ 0.34 * A - 0.029 * B + 0.36 * C - 0.010 * A * B + 0.49 * A * C - 0.025 * B *
C - 0.52 * A2 + 0.020 *B2 + 0.10 * C2 (1)
Final
equation in terms of actual factors
CEF = +
0.63972 + 0.015065 * A – 5.54996E – 004 * B – 0.61595 * C – 2.91266E – 006 * A
* B + 0.016216 * A * C – 8. 46677E – 004 * B * C – 1.44820E – 004 * A 2 +
5.62985E – 006 * B2 + 0.41330 * C2 (2)
Where A: Time when FR was turned on; B: Time the
FR was turned off (Dark time after turning off far-red light); C: The intensity
of exposure to far-red light.
Experimental scheme optimization
Based on
the analysis of the experimental results and model fitting, the experimental
parameters were further optimized by using Design-Expert 8.0.6 Trian. The
optimal scheme for the value of each parameter was thus obtained under the
condition of the optimum CEF. Table S11 (supplementary
material) shows the optimal scheme to obtain the optimum CEF. According to the
optimization results, the best CEF is obtained when HFR is turned on for 97 s
and turned off for 20 s, which is consistent with the optimal results in the
experimental data.
Discussion
Cyclic
electron transport around PSІ remains one of the mysteries of
photosynthesis. An important reason for the existence of this problem is that
it is difficult to directly measure because the cycle has no net electron flow (Zhang
et al. 2018). As an index, the P700+ level is direct and
sensitive and measures the capability of receiving electrons in PSІ.
Under far-red light irradiation, the fast components of the P700+
decay are derived from cyclic electron transport (PGR5-dependent pathway). It
has been shown that Arabidopsis
mutants without PGR5 exhibit responses to high light levels (Nandha et al. 2007; DalCorso et al.
2008; Okegawa et al. 2010; Tikkanen et al. 2014),
fluctuating light (Tikkanen et al. 2010), high
temperature (Zhang and Sharkey 2009) and
low CO2 concentration (Munekage et
al. 2008); hence, the CEF of the PGR5 pathway is particularly
important. Depending on the PGR5 PSІ, CEF is crucial for the
acidification around the thylakoid lumen. Okegawa et al. (2007) used transgenic mutants and
reported that overexpression of the PGR5 protein led to a delayed development
of plant chloroplasts. Suorsa et al.
(2012) showed that inhibition of the PGR5 gene expression increased the
intracavity pH, which interfered with the down-regulation of the Cyt b6/f
complex, thus resulting in the accumulation of excessive electrons in PSI,
which in turn resulted in a reduction of P700.
According to prior research, on the basis of chlorophyll, the chloroplast
at the bottom of leaf absorbs about 10–20% of the green light (λ= 530 ± 15
nm) that is absorbed by the green leaves at the top (Fan et al. 2002),
however, the fraction is much smaller for strongly absorbed wavelengths, such
as red and blue ( Katsumi 1976; Fan et al.
2002). This is consistent with the obtained experimental results (Fig. 2). To
further stimulate the photosystem in the lower chloroplasts, the irradiation
time has to be extended or the light intensity increased. The far-red light
treatment is more irradiating and can therefore increase the content of
chlorophyll b in the leaves. The antenna pigment chlorophyll b promotes the
absorption and transmission of light energy, which can improve the net
photosynthetic rate, and exerts a positive impact on photosynthesis (Cheng et
al. 2018).
The equation model between CEF and light intensity time suggested by
Design-Expert software is a quadratic mathematical equation. To test the
fitting degree of this equation, the following diagnosis is necessary (eg: normal
probability plot of the studentized residuals to test for normality of
residuals). The diagnostic results showed that all model statistics and
diagnostic graphs were satisfactory, and can therefore be used as the
determination equation of the mulberry PGR5-dependent CEF.
Design-Expert software was used for the optimization process to identify
the optimal combination of factors (Liu et al. 2011). Both response
factor and process input factor remained within the scope of the requirements.
In this experiment, the digital optimization method was used to optimize the
equation by selecting the expected target of each factor and response. CEF was
set to the condition that the maximum is the optimal combination. The simulated
results showed that the maximum CEF per unit Pm can be obtained by turning the
light off for 20 s after 97 s of far-red light irradiation. This is almost
consistent with the results obtained by the intensity-time dependent test.
To
test the effectiveness of this method in different plants, the model plant
tobacco was used. Most of the times and light intensities were selected to
determine the reduction degree of P700+ (supplementary data Tables S1–S3),
origin 9.1 and Design-Expert 8.0.6 Trian were used to simulate 3D layers (Fig. 4A)
and surface equations (Formula (3), please see below), respectively. To control
the variables used to explore the consistency of the results measured by this
method between mulberry and tobacco, the experimental data was selected that
was consistent with the results of mulberry and tobacco. The 3D layer (Fig. 4B)
was repeated as was the surface equation {Formula (3)}. Fig. 4 shows that the
trend of the tobacco 3D layer is consistent with that of the mulberry 3D layer,
namely HFR > MFR > LFR. Formulas (3) and (4) represent the curved surface
equations of tobacco and mulberry, respectively, and the coding factor equation
coefficient of both was used for significance analysis in SPSS22.0 (Table 12s,
supplementary materials). Furthermore, a comprehensive analysis of the tobacco
data was conducted with Design-Expert. Supplementary data Tables S4–S6 showed
that the tobacco equation was a quadratic polynomial simulation equation with
good simulation effect (Fig. 1s), and the optimal combination was consistent
with the mulberry experiment (Table S7). These results showed that the simple
correlation coefficient between mulberry and tobacco
was 0.952, indicating a strong positive correlation between them, which
testifies the feasibility of this method for tobacco. In conclusion, the
experimental method can be applied for the determination of the PGR5 cyclic
electron transport between different plants.
Final equation in terms of actual factors for
tobacco
CEF = +
0.57355 + 0.016740 * A - 5.42860E - 004B - 0.81237 * C - 3.76860E – 006 * AB +
0.014717 * A * C - 1.83021E – 003 * B * C - 1.44382E – 004 * A2 +
1.43193E – 005 * B2 + 1.00331 * C2 (3)
Final equation in terms of actual factors for
mulberry
CEF = +
0.84479 + 0.011839 * A - 2.88142E – 003 * B - 1.12897 * C + 1.54509E – 006 * A
* B + 0.016695 * A * C + 2.89548E – 004 * B * C - 1.19048E – 004 * A2 +
2.02159E – 005 * B2 + 0.85650 * C2 (4)
Conclusion
HFR can
effectively stimulate PGR5-dependent cyclic electron flow. In addition, cyclic
electron flow measured by the cyclic electron flow method per unit Pm can be
used for the qualitative estimation of cyclic electron flow in different
plants. The results of Design-Expert 8.0.6 Trian were consistent with the
experimental results, and the optimal combination was: HFR turned on for 97 s,
followed by turning off the far-red light for 20 s, and HFR irradiation for 60
s. Finally, far-red light of 100% (1000 µmol
m-2 s-1) and saturated light (5000 µmol m-2 s-1) were used at the same time for
1 s. The mathematical model between PGR5 and switching far-red light time and
light intensity can be expressed according to Equation (2).
Acknowledgments
This
research was funded by the National Natural Science Foundation of China, grant
number 31870373.
Conceptualization, Y-H.C., and G-Y. S.; methodology, H-R.W., and Y.W.; software, H-R.W., and Y-H.C.;
validation. Y.W.; investigation, Y-H.C.; data curation, Y-H.C., and H-R.W.;
project administration, Y-H.C., and G-Y.S.; writing-original draft preparation, Y-H.C.; writing-review and editing, Y-H.C, and G-Y.S.;
writing-discussion, Y-H.C., H-R.W., and G-Y.S.; funding acquisition, G-Y.S.;
All authors have read and agreed to the published version of the manuscript
Burrows PA, LA Sazanov, Z Svab, P Maliga, PJ Nixon (1998).
Identification of a functional respiratory complex in chloroplasts through
analysis of tobacco mutants containing disrupted plastid ndh genes. EMBO J 17:868‒876
DalCorso
G, P Pesaresi, S Masiero, E Aseeva, D Schünemann, G Finazzi, P Joliot, R Barbato,
D Leister (2008). A complex containing PGRL1 and PGR5 is involved in the
switch between linear and cyclic electron flow in Arabidopsis. Cell 132:273‒285
Fan
DY, Q Wang, M Li, GM Zhang, RF Gao (2002). The len effect of the epidermic cell
layer of the leaf of euonymus Japonicus T. on the light gradients within leaf. Acta Phytoecol Sin
26:594‒598
Huang W, YJ Yang, H Hu, SB Zhang (2015). Different roles of cyclic electron
flow around photosystem I under sub-saturating and saturating light intensities
in tobacco leaves. Front Plant Sci 6; Article 923
Katsumi
I (1976). Action spectra for photosynthesis in higher plants. Plant Cell
Physiol 17:355‒365
Munekage Y, M Hojo, J Meurer, T Endo, M Tasaka, T
Shikanai (2002). PGR5 is involved in cyclic electron flow around photosystem I
and is essential for photoprotection in Arabidopsis. Cell
110:361‒371
Sergi MB, T Shikanai, K Asada (2005). Enhanced
ferredoxin-dependent cyclic electron flow around photosystem I and
alpha-tocopherol quinone accumulation in water-stressed ndhB-inactivated
tobacco mutants. Planta 222:502‒511
Shikanai
T (2007). Cyclic electron transport arouncd photosystem I. Annu Rev Plant
Biol 58:199‒217
Takahashi
S, SE Milward, DY Fan, WS Chow, MR Badger (2009). How does cyclic electron flow
alleviate photoinhibition in Arabidopsis. Plant Physiol 149:1560‒1567
Tikkanen M, M Grieco, S Kangasjärvi, EM Aro (2010).
Thylakoid protein phosphorylation in higher plant chloroplasts optimizes
electron transfer under fluctuating light. Plant Physiol 152:723‒735