Tim Hohm1, Emilie Demarsy2, Clément Quan2, Laure Allenbach Petrolati2, Tobias Preuten2, Teva Vernoux3, Sven Bergmann4, Christian Fankhauser5. 1. Department of Medical Genetics, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland Swiss Institute for Bioinformatics, Lausanne, Switzerland. 2. Centre for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland. 3. Laboratoire de Reproduction et Développement des Plantes, CNRS INRA ENS Lyon UCBL Université de Lyon, Lyon, France. 4. Department of Medical Genetics, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland Swiss Institute for Bioinformatics, Lausanne, Switzerland sven.bergmann@unil.ch christian.fankhauser@unil.ch. 5. Centre for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland sven.bergmann@unil.ch christian.fankhauser@unil.ch.
Abstract
Phototropism is a growth response allowing plants to align their photosynthetic organs toward incoming light and thereby to optimize photosynthetic activity. Formation of a lateral gradient of the phytohormone auxin is a key step to trigger asymmetric growth of the shoot leading to phototropic reorientation. To identify important regulators of auxin gradient formation, we developed an auxin flux model that enabled us to test in silico the impact of different morphological and biophysical parameters on gradient formation, including the contribution of the extracellular space (cell wall) or apoplast. Our model indicates that cell size, cell distributions, and apoplast thickness are all important factors affecting gradient formation. Among all tested variables, regulation of apoplastic pH was the most important to enable the formation of a lateral auxin gradient. To test this prediction, we interfered with the activity of plasma membrane H⁺ -ATPases that are required to control apoplastic pH. Our results show that H⁺ -ATPases are indeed important for the establishment of a lateral auxin gradient and phototropism. Moreover, we show that during phototropism, H⁺ -ATPase activity is regulated by the phototropin photoreceptors, providing a mechanism by which light influences apoplastic pH.
Phototropism is a growth response allowing plants to align their photosynthetic organs toward incoming light and thereby to optimize photosynthetic activity. Formation of a lateral gradient of the phytohormone auxin is a key step to trigger asymmetric growth of the shoot leading to phototropic reorientation. To identify important regulators of auxin gradient formation, we developed an auxin flux model that enabled us to test in silico the impact of different morphological and biophysical parameters on gradient formation, including the contribution of the extracellular space (cell wall) or apoplast. Our model indicates that cell size, cell distributions, and apoplast thickness are all important factors affecting gradient formation. Among all tested variables, regulation of apoplastic pH was the most important to enable the formation of a lateral auxin gradient. To test this prediction, we interfered with the activity of plasma membrane H⁺ -ATPases that are required to control apoplastic pH. Our results show that H⁺ -ATPases are indeed important for the establishment of a lateral auxin gradient and phototropism. Moreover, we show that during phototropism, H⁺ -ATPase activity is regulated by the phototropin photoreceptors, providing a mechanism by which light influences apoplastic pH.
The ability of plants to adjust their growth to the direction of incoming light already intrigued
Greek philosophers in ancient times (Whippo & Hangarter, 2006) and lost nothing of its fascination today. Several key steps of this process termed
phototropism starting with light perception and leading to directional growth are well understood
(Sakai & Haga, 2012; Christie & Murphy, 2013; Hohm et al, 2013). The formation of a lateral gradient of the phytohormone auxin across a unilaterally
irradiated hypocotyl (embryonic stem) is necessary and sufficient to cause asymmetric growth and
subsequent phototropic bending (Baskin et al, 1986; Friml et al, 2002; Haga
& Sakai, 2012). Yet, the mechanisms for forming this
gradient remain elusive. Several auxin carriers including members of the PIN-FORMED (PIN),
ATP-binding cassette transporters subfamily B (ABCB), and AUXIN-RESISTANT1 (AUX1) families have been
implicated in auxin gradient formation (Friml et al, 2002; Blakeslee et al, 2004;
Stone et al, 2008; Christie et
al, 2011; Ding et al, 2011; Willige et al, 2013). Light perception by the photoreceptor phototropin1 (phot1) leads to
inhibition of ABCB19 activity, which controls the basipetal flux of auxin in the hypocotyl and
thereby indirectly modulates lateral auxin gradient formation (Christie et al,
2011). The auxin transporters that have most prominently been
implicated in formation of a lateral auxin gradient are members of the PIN family (Ding et
al, 2011; Haga & Sakai, 2012; Willige et al, 2013).
However, how light affects PIN activity and the importance of intracellular localization of PIN
proteins upon phototropic stimuli are still a matter of debate (Christie et al,
2011; Ding et al, 2011; Sakai & Haga, 2012; Hohm
et al, 2013).In addition to being actively transported, protonated auxin is able to diffuse across the plasma
membrane (Krupinski & Jonsson, 2010). The protonated
fraction of the weak acid auxin [pKa 4.8, (Delbarre et al, 1996)] depends on the environmental pH. Because of
contrasted pH between cytoplasmic and apoplastic compartments (estimated at 7 and 5.5, respectively)
(Kurkdjian & Guern, 1989; Bibikova et
al, 1998; Yu et al, 2000; Kramer & Bennett, 2006; Krupinski & Jonsson, 2010), an auxin
fraction can be passively imported by the cell, while only active transport allows for auxin export.
Whether regulation of apoplastic pH is required for auxin gradient formation and phototropic
bending, to our knowledge, has not been thoroughly investigated so far. Regulation and maintenance
of the proton gradient across the plasma membrane and apoplastic pH requires the activity of plasma
membrane-localized proton pumps of the AHA family (H+-ATPases) (Palmgren, 2001). H+-ATPase activity is crucial for a large
variety of physiological processes such as stomatal opening, nutrient uptake, or hypocotyl and root
growth (Palmgren, 2001; Haruta et al, 2010; Haruta & Sussman, 2012). Interestingly, the role of H+-ATPases has been linked to cell
elongation by the acid growth theory (Rayle & Cleland, 1992; Hager, 2003; Cosgrove, 2005). It stipulates that cell elongation requires apoplastic acidification to
activate cell wall-loosening proteins (Hager, 2003).
Recently, it has been shown that auxin-induced cell elongation involves auxin-mediated regulation of
H+-ATPase activity by phosphorylation (Takahashi et al, 2012; Spartz et al, 2014). Therefore, regulation of H+-ATPase activity might play a
dual role during phototropism: to modulate the portion of protonated auxin and thus auxin influx,
and to promote cell wall acidification and thus cell elongation.To shed further light on auxin gradient formation during phototropism, we established an auxin
flux model based on the morphology of the hypocotyl of an Arabidopsis thaliana
seedling enabling us to test in silico the impact of various parameters: hypocotyl
topology, apoplast thickness, and apoplastic pH changes. Our model predicted that regulation of
apoplastic pH is a key step for the establishment of a lateral auxin gradient, a prediction that we
supported experimentally. Finally, we provide results suggesting a mechanism explaining how light
can regulate H+-ATPases and thereby potentially apoplastic pH at the molecular
level.
Results
An in silico model for auxin flux during hypocotyl phototropism
Overall, auxin fluxes include active and passive cellular efflux and influx, and free auxin
diffusion within the apoplastic compartment (Kramer, 2007;
Krupinski & Jonsson, 2010). While the apoplastic
diffusion distance depends on the actual apoplastic thickness and pH (Kramer, 2006), passive efflux and influx depend on compartmental pH and cell surface
(Krupinski & Jonsson, 2010). Moreover, active fluxes
are subject to carrier expression levels and localization.To test in silico the impact of these various contributions on auxin gradient
formation during phototropism, we used ordinary differential equations to build an auxin flux model.
We considered active efflux contributions from both ABCBs and PINs (Supplementary Table S1), because
members of both transporter families have been proposed to control auxin gradient formation upon
phototropic stimulation (Christie et al, 2011; Ding et al, 2011; Haga
& Sakai, 2012; Willige et al, 2013). We also explicitly considered fluxes resulting not only from
passive influxes and effluxes in the cells but also from free diffusion in the apoplast. Concerning
active auxin transport, a starting modeling assumption in our model supported by experimental
evidence is that upon unilateral blue light irradiation, PIN3 is polar in the endodermal cells on
the lit side (Ding et al, 2011). In all
other tissues, PINs and ABCBs are expressed apolarly. We did not consider active IAA (auxinindole-3-acetic acid) influx contributions resulting from AUX1/LAX for the following reasons: (i) A
previous study showed that phototropism in the aux1lax1lax3 triple mutant is not
significantly different from the wild-type (Christie et al, 2011), (ii) this triple mutant lacks the expression of AUX1 and
LAX3, which were the most highly expressed members of the AUX1/LAX
family in the hypocotyl (Supplementary Fig S1), and (iii) we observed that different double, triple,
and the aux1lax1lax2lax3 quadruple mutant showed a normal final phototropic
response although in the quadruple mutant, there was a slight growth re-orientation delay
(Supplementary Fig S1). Possible implications of including an AUX1/LAX term in our model are further
evaluated in the discussion.In etiolated Arabidopsis seedlings, light sensing occurs at the site of
asymmetric growth, suggesting that formation of a lateral auxin gradient occurs locally (Iino, 2001; Preuten et al, 2013; Yamamoto et al, 2014). Thus, we assumed locality of gradient formation and used a realistic hypocotyl cross
section to model gradient formation (Fig 1A and B). We
tested the effect of a change in apoplastic pH, because small variations around the estimated
resting apoplastic pH of 5.5 have a big impact on the protonation state of auxin influencing passive
diffusion (the pKa of IAA is 4.8) (Kurkdjian & Guern, 1989; Bibikova et al, 1998; Yu
et al, 2000; Kramer & Bennett, 2006; Krupinski & Jonsson, 2010) (Fig 1C). In all our simulations, pH
modulation was treated as an exogenous variable, that is, a variable that is not affected by the
model. pH modulation during phototropism therefore was imposed manually by modifying the apoplastic
pH around cells on the shaded and/or lit side of the cross section. As we will discuss later on, a
potential mechanism to create such a pH modulation is a light-triggered and phototropin-mediated
modulation of H+-ATPase activity (see below).
Figure 1
Overview on model domain, formed gradients, topological parameters, and biophysical
parameters tested in the model
Modeled domain representing a cross section through the elongation zone of a 3-day-old etiolated
Arabidopsis thaliana seedling.
Example of an auxin concentration gradient formed within a cross section showing apoplastic auxin
gradient and cellular auxin gradient.
Dissociation curve for IAA based on its pKa of 4.8 showing protonated fractions for
different compartmental pH values.
Different topologies tested during model parameter exploration: a realistic cross section (T1), a
rotational symmetric cross section model with a cell size distribution over the different layers as
found in the realistic cross section (T2), a rotational symmetric cross section model with an
inverted cell size distribution (T3), and rotational symmetric cross section model where all cells
have the same size (either small (T4)-like cells found in epi- and endodermis or big (T5)-like cells
found in the cortex). Here, small cells have a diameter of approximately 15 μm, while big
cells have a diameter of approximately 30 μm.
Illustration of the exact localization of the different apoplast layers, outer epidermis (OE),
inner epidermis (IE), outer cortex (OC), inner cortex (IC), and endodermis (EN) and their measured
thicknesses for different elongation states as reported by Derbyshire and colleagues (Derbyshire
et al, 2007).
Overview on model domain, formed gradients, topological parameters, and biophysical
parameters tested in the model
Modeled domain representing a cross section through the elongation zone of a 3-day-old etiolated
Arabidopsis thaliana seedling.Example of an auxin concentration gradient formed within a cross section showing apoplastic auxin
gradient and cellular auxin gradient.Dissociation curve for IAA based on its pKa of 4.8 showing protonated fractions for
different compartmental pH values.Different topologies tested during model parameter exploration: a realistic cross section (T1), a
rotational symmetric cross section model with a cell size distribution over the different layers as
found in the realistic cross section (T2), a rotational symmetric cross section model with an
inverted cell size distribution (T3), and rotational symmetric cross section model where all cells
have the same size (either small (T4)-like cells found in epi- and endodermis or big (T5)-like cells
found in the cortex). Here, small cells have a diameter of approximately 15 μm, while big
cells have a diameter of approximately 30 μm.Illustration of the exact localization of the different apoplast layers, outer epidermis (OE),
inner epidermis (IE), outer cortex (OC), inner cortex (IC), and endodermis (EN) and their measured
thicknesses for different elongation states as reported by Derbyshire and colleagues (Derbyshire
et al, 2007).Lastly, we took into account topological parameters like different apoplast thickness
distributions as observed during seedling elongation (Derbyshire et al, 2007) as well as modifications of the available cell surface for
the different cell layers (Fig 1D and E). The former was
tested because apoplast thickness impacts auxin travel distances in the apoplast, while the latter
is of interest since changes in size of the active interface between cells and apoplast modify
absolute auxin flux contributions via a membrane. The cell surface variation was realized by
modifying the classical cell size distribution of low-diameter endodermal and epidermal cells and
large-diameter cortical cells and thereby affecting the relation between cell volume and cell
surface (Fig 1D). We judged our models based on their
ability to generate an auxin concentration difference in epidermal cells of opposing sides because
the epidermis is considered as limiting for growth (Kutschera & Niklas, 2007; Savaldi-Goldstein et al, 2007) and auxin gradients were observed in the epidermis of photo-stimulated seedlings (Haga
& Iino, 2006). To calculate concentrations, we used
the cell and apoplast volumes and surfaces as obtained from a hypocotyl cross section (Fig 1D and E). We arbitrarily considered that a gradient was
established when more than 1% concentration difference between opposing sides was obtained in
the model.
Apoplastic pH modulation is necessary for auxin gradient formation
Among all variables tested, auxin gradient formation depended most critically on a modulation of
the pH in the apoplast. Gradients could only be formed when the apoplastic pH around epidermal cells
on the shaded side was lowered (Fig 2A; Supplementary Fig
S2). Before acidification, we assumed an initial apoplastic pH of 5.5 (Kurkdjian & Guern,
1989; Bibikova et al, 1998; Yu et al, 2000;
Kramer, 2006; Krupinski & Jonsson, 2010) and we assumed a drop in pH by 0.7 units. Such a drop in
apoplastic pH has been observed previously (Fasano et al, 2001; Boonsirichai et al, 2003; Monshausen et al, 2011).
Moreover, this has a serious impact on the protonation state of the naturally occurring IAA: While
at a resting pH of 5.5, only approximately 16% of the apoplastic auxin is protonated and is
therefore able to permeate cell membranes, after acidification (to pH 4.8), the protonated fraction
increases to 50%. Therefore, a drop in apoplastic pH creates a trap for apoplastic auxin and
boosts the intracellular auxin concentration of surrounding cells. On the contrary, simulation of
apoplast basification on the lit side was not sufficient to induce auxin gradient formation (Fig
2A). This might be explainable by the fact that increasing
the apoplastic pH is only able to affect the protonation state of the approximately 16% of
IAA already protonated (Fig 1C). We also modeled the effect
of basification of the apoplast on the lit side while lowering the initial pH in etiolated seedlings
from 5.5 to 4.8; however this did not increase the resulting gradients (Supplementary Fig S2).
Finally, concomitant apoplast acidification and basification on opposing sides enhanced the
gradients observed in the acidification-only scenario (Fig 2A).
Figure 2
Impact of different parameters on in silico auxin gradient formation
As base scenario for a realistic cross section with apoplast thickness distribution IIa
(corresponding to short cells), full PIN activity and concomitant acidification and basification
were used.
Impact of modulations in apoplast pH distributions. Here, only the subset of scenarios in which
we applied apoplast acidification shows lateral gradient formation.
Impact of different cell size distributions. Only the realistic, symmetrized realistic, and
only-small-cells topologies are able to form lateral gradients.
Impact of apoplast thickness on gradient formation. Tested apoplast thickness distributions were
distributions with relatively thick epidermal walls and thinner internal apoplast starting from very
thick (IIa) ranging over medium (IIb) to small (IIc) and homogeneous apoplast thicknesses of 800,
400 and 100 nm, respectively. Only scenarios IIa, 400 and 800 nm are able to form lateral
gradients.
Impact of different parameters on in silico auxin gradient formation
As base scenario for a realistic cross section with apoplast thickness distribution IIa
(corresponding to short cells), full PIN activity and concomitant acidification and basification
were used.Impact of modulations in apoplast pH distributions. Here, only the subset of scenarios in which
we applied apoplast acidification shows lateral gradient formation.Impact of different cell size distributions. Only the realistic, symmetrized realistic, and
only-small-cells topologies are able to form lateral gradients.Impact of apoplast thickness on gradient formation. Tested apoplast thickness distributions were
distributions with relatively thick epidermal walls and thinner internal apoplast starting from very
thick (IIa) ranging over medium (IIb) to small (IIc) and homogeneous apoplast thicknesses of 800,
400 and 100 nm, respectively. Only scenarios IIa, 400 and 800 nm are able to form lateral
gradients.
Cellular topology has the potential to contribute to the formation of lateral auxin gradients for
the following reasons. To result in an equivalent change in auxin concentration, more auxin
molecules need to be transported in or out of a cell with a larger volume than a cell with a smaller
volume. In addition, for the nearly cylindrical cells found in etiolated hypocotyls, the ratio of
cell surface to cell volume decreases with increasing diameter. Considering that the cell surface is
the interface via which auxin has to be moved, small diameter cells can change their auxin
concentration more easily and faster. In addition, the cellular geometry impacts the apoplastic
volume (see below).We quantified the impact of hypocotyl morphology on gradient formation in our model. For
calculations of auxin concentrations, we used cell and apoplast volumes and surfaces determined from
the cross sections shown in Fig 1D. We found that
topological features indeed have a strong impact on gradient formation. For simplification, we only
considered cell size variations using idealized topologies (Fig 1D, topologies T2-4). When testing the impact of cell size distributions, we started with
the natural cell size distribution with small cells (∼15 μm in diameter) in epi- and
endodermis and big cells (∼30 μm in diameter) in the cortex (Fig 1D, topology T2) and tested inverted cell size distributions (Fig 1D, topology T3) as well as only small cells (Fig 1D, topology T4) and only big cells (Fig 1D, topology T5). According to these simulations, the natural cell size
distribution is beneficial for gradient formation (Fig 2B).Notably, the idealized topology with realistic cell size distribution yielded a relatively
similar gradient to the gradient simulated in the natural topology (Fig 2B), indicating that potential asymmetries in the realistic topology do not have
a strong influence on gradient formation. To test this further, we also simulated gradient formation
in a situation where light comes from a different side (rotated by 90 degrees) than in the original
simulations. As our hypocotyl cross section and others that we found in the literature (Gendreau
et al, 1997; Crowell et al,
2011) are not perfectly symmetric under (discrete) rotations,
different directions could have led to different outcomes in our model prediction. Yet, our
simulations showed that the observed differences were small (a few percent at most), indicating that
asymmetries in our cross section do not affect our results significantly (Supplementary Fig S3).In contrast, an inverted cell size distribution prevented gradient formation, as did a
distribution consisting of only big cells. On the other hand, formation of an auxin gradient was
possible using only small cells. In addition, we observed that further decreasing the cell volume
while maintaining the cell surface constant further enhanced the steepness of gradients. This is a
likely scenario in hypocotyl cells of etiolated seedlings that primarily consist of a large vacuole.
Assuming that auxin is excluded from the vacuoles and that vacuoles in fully pressurized hypocotyl
cells make up for at least 90% of the cell volume, simulations predict resulting gradients
reaching up to 12% difference between shaded and lit side opposed to 8% when ignoring
vacuoles and otherwise using the same settings. This corresponds to a 50% increase in
gradient strength by considering potential effects of compartmentalization of the cells.Apart from cell sizes and volumes, apoplast thickness also plays a potential role in auxin
gradient formation. This is due to the fact that the apoplast potentially provides a mode of
long-distance auxin transport depending on its diameter (Kramer, 2006, 2007). Considering that, depending on the
elongation status and thus on the cellular geometry of hypocotyl cells their surrounding, apoplast
thicknesses vary considerably (with apoplast thicknesses decreasing with increasing cell elongation)
(Derbyshire et al, 2007), cell elongation
and thickness might contribute to auxin gradient formation. To test this in our model, we compared
thickness distributions documented during different elongation states of hypocotyl cells (Derbyshire
et al, 2007). We particularly considered the
early stages of hypocotyl elongation that all show relatively thick outer epidermal apoplasts and
considerably thinner apoplasts on the inside. Using the thickness distributions reported by
Derbyshire and colleagues (Derbyshire et al, 2007), we considered non-elongated cells (IIa), partly elongated cells (IIb), and strongly
elongated cells (IIc) (Derbyshire et al, 2007) (Figs 2C and 1E). We contrasted these measured thicknesses with homogeneous thickness distributions
within the range of those measurements (Derbyshire et al, 2007) (Fig 2C and Supplementary Fig
S3).The strongest gradients were found in scenarios using thick apoplasts (IIa, 800 nm, and a bit
less in case of 400 nm) (Fig 2C). This supports the
hypothesis that the apoplast constitutes an important mode of long-distance auxin flux during
lateral gradient formation. Our analysis indicated that a thick epidermal layer was particularly
favorable for gradient formation since thickness distribution IIa features a very thick outer
epidermal apoplast (1,250 nm), but all the other layers are thinner than in the 400-nm scenario
(Figs 1E and 2C).
Despite thinner apoplast in the inner cell layers, gradients formed in scenario IIa were stronger
than in case of the homogeneous 400-nm apoplast.
Regulation of plasma membrane H+-ATPase activity is required for
phototropism
Our in silico study predicted that the apoplast, in particular apoplastic pH
regulation upon unilateral light perception, is a fundamental parameter for auxin gradient
establishment (Fig 2A). Apoplastic pH is regulated by the
activity of plasma membrane-localized H+-ATPases (Palmgren, 2001). To test this prediction experimentally, we first analyzed the kinetics of
phototropic bending in conditions with an altered regulation of the apoplastic pH, by modulating the
plasma membrane H+-ATPase activity. Treatment with increasing concentrations of
the proton pumps inhibitor dicyclohexylcarbodiimide (DCCD) progressively inhibited the phototropic
response in the wild-type (Fig 3A). Accordingly, we observed
a delayed phototropic response of mutants lacking the expression of the two most expressed AHA
proteins, aha1 and aha2 (Supplementary Fig S4). Inhibition of
H+-ATPase activity by genetic or pharmacological approaches resulted in reduction
of the hypocotyl growth rate (Supplementary Fig S5A and B), which could be the cause of reduced
phototropism. However, we note that in a previous study, the growth rate of decapitated seedlings
was similarly reduced as in seedlings treated with 50 μM DCCD, but decapitated seedlings
still showed robust phototropism while DCCD-treated seedlings did not (Fig 3A) (Preuten et al, 2013). This indicates that reduced growth rate alone is not the reason for phototropism
inhibition observed when H+-ATPase activity is reduced.
Figure 3
Regulation of H+-ATPase activity is required for optimal
phototropism
Inhibition of proton pump activity by the proton pump inhibitor dicyclohexylcarbodiimide (DCCD)
represses phototropism.
Enhancement of proton pump activity by fusicoccin (FC) treatment represses phototropism. Data
represent the rate of hypocotyl growth curvature upon unilateral blue light irradiation with a
fluence rate of 10 μmol m−2 s−1. Values are means
± 2×SE, n > 20.
Source data are available online for this figure.
Regulation of H+-ATPase activity is required for optimal
phototropism
Inhibition of proton pump activity by the proton pump inhibitor dicyclohexylcarbodiimide (DCCD)
represses phototropism.Enhancement of proton pump activity by fusicoccin (FC) treatment represses phototropism. Data
represent the rate of hypocotyl growth curvature upon unilateral blue light irradiation with a
fluence rate of 10 μmol m−2 s−1. Values are means
± 2×SE, n > 20.Source data are available online for this figure.To further investigate the role of H+-ATPases, we treated seedlings with the
specific activator fusicoccin (FC). General activation of H+-ATPase activity upon
FC treatment increased hypocotyl growth rate, but reduced phototropism (Fig 3B and Supplementary Fig S5C). The fact that both inhibition and activation of
H+-ATPases during unilateral light treatment affect the amplitude of hypocotyl
bending suggests that regulation of H+-ATPase activity is required for optimal
phototropism.
H+-ATPase regulation is necessary for auxin gradient establishment
We then tested whether H+-ATPase regulation is required for auxin gradient
establishment during phototropism. We evaluated the distribution of auxin across the hypocotyl upon
phototropic stimulation using the auxin sensor DII-Venus, a synthetic protein degraded directly upon
auxin perception (Brunoud et al, 2012). The
signal of DII-Venus was homogeneously distributed in the hypocotyl before phototropic stimulation.
Following a 1-h unilateral blue light treatment, which precedes phototropic re-orientation in our
conditions, we observed an asymmetric DII-Venus signal across the hypocotyl (Fig 4A and Supplementary Fig S6). The signal was stronger on the lit
side compared to the shaded side, indicating a higher accumulation of auxin on the shaded side (Fig
4A and B). Treating seedlings with the auxin efflux
inhibitor NPA completely abolished the formation of the gradient (Fig 4 and Supplementary Fig S6). Importantly, FC treatment strongly impaired auxin
gradient establishment (Fig 4 and Supplementary Fig S6),
demonstrating that misregulation of H+-ATPase activity and consequently
misregulation of apoplastic pH during phototropic stimulation prevent auxin relocalization.
Figure 4
Regulation of H+-ATPase activity is required for lateral auxin gradient
formation
DII-Venus signal in hypocotyls was examined before (left) or after (right) 1 h blue light (BL)
irradiation with a fluence rate of 10 μmol m−2 s−1.
General activation of H+-ATPases and inhibition of auxin transport prevent
auxin gradient formation. Seedlings treated with DMSO, NPA, or FC were analyzed as in (A).
Quantification of DII-Venus signal was performed on 11–13 seedlings for each treatment, and
data represent the ratio of the DII-Venus fluorescence signal between the lit side and the shaded
side. Values are means, and error bars represent standard errors.
Source data are available online for this figure.
Regulation of H+-ATPase activity is required for lateral auxin gradient
formation
DII-Venus signal in hypocotyls was examined before (left) or after (right) 1 h blue light (BL)
irradiation with a fluence rate of 10 μmol m−2 s−1.General activation of H+-ATPases and inhibition of auxin transport prevent
auxin gradient formation. Seedlings treated with DMSO, NPA, or FC were analyzed as in (A).
Quantification of DII-Venus signal was performed on 11–13 seedlings for each treatment, and
data represent the ratio of the DII-Venus fluorescence signal between the lit side and the shaded
side. Values are means, and error bars represent standard errors.Source data are available online for this figure.
Phototropins regulate plasma membrane H+-ATPase phosphorylation during
phototropism
Since regulation of H+-ATPase activity is required for auxin gradient formation
preceding phototropic bending, we examined how AHA proteins are regulated upon light perception in
hypocotyls. Phosphorylation of H+-ATPases occurs at multiple sites and is an
important mechanism regulating their activity (Duby & Boutry, 2009; Rudashevskaya et al, 2012).
Phosphorylation at the penultimate residue, a threonine (Thr947 in ArabidopsisAHA2), is a primary step for the activation of H+-ATPases (Duby & Boutry,
2009). To evaluate the activity of
H+-ATPases in hypocotyls upon light perception, H+-ATPases
phosphorylation levels were analyzed by immunoblotting using an antibody recognizing the catalytic
region of H+-ATPases and an antibody specifically recognizing the phosphorylated
threonine (pThr947). These antibodies recognize several members of the AHA family (Hayashi
et al, 2010). A decreased phosphorylation of
H+-ATPases was detected in dissected hypocotyls when the seedlings were irradiated
unilaterally with blue light (Fig 5A and Supplementary Fig
S7). Importantly, while the level of H+-ATPase phosphorylation at the penultimate
amino acid was similar between wild-type and the phot1phot2 mutant in the dark, we
did not observe any blue light regulation of H+-ATPase phosphorylation in the
absence of phototropins (Fig 5B). Altogether, our data
indicate that phototropins regulate H+-ATPase activity in the hypocotyl during
phototropism. Consequently, these data provide a potential molecular explanation for the need of
specific regulation of H+-ATPase activity during phototropism and the
stimulus-induced pH modulation predicted by our model.
Figure 5
Phototropins regulate H+-ATPase phosphorylation in hypocotyls upon light
perception
Unilateral blue light decreases H+-ATPase phosphorylation levels in hypocotyls.
Three-day-old (WT) seedlings were either kept in darkness (0) or irradiated with 10 μmol
m−2 s−1 unilateral blue light for the indicated time. Total
proteins from dissected hypocotyls were separated by SDS–PAGE and transferred onto
nitrocellulose membrane. Accumulation of total H+-ATPases and
H+-ATPases phosphorylated at the penultimate amino acid was analyzed by
immunoblotting using anti-H+-ATPases (H+-ATPases) and
anti-phosphorylated-threonine-947 (pThr947) antibodies, respectively. Quantifications of pThr947
signal relative to the H+-ATPases total signal were performed on three biological
replicates. Values are means, and error bars represent standard errors. * indicates
significant difference between means of light-treated samples compared to dark control
(P < 0.05).
Regulation of H+-ATPase phosphorylation levels at pThr947 depends on
phototropins. Three-day-old seedlings of Col-0 (WT) or phot1phot2 mutant were
either kept in darkness (0) or irradiated with 10 μmol m−2
s−1 unilateral blue light for 30 min. Proteins were analyzed as described in (A).
*indicates significant difference between means of light-treated samples compared to dark
control (P < 0.05).
Source data are available online for this figure.
Phototropins regulate H+-ATPase phosphorylation in hypocotyls upon light
perception
Unilateral blue light decreases H+-ATPase phosphorylation levels in hypocotyls.
Three-day-old (WT) seedlings were either kept in darkness (0) or irradiated with 10 μmol
m−2 s−1 unilateral blue light for the indicated time. Total
proteins from dissected hypocotyls were separated by SDS–PAGE and transferred onto
nitrocellulose membrane. Accumulation of total H+-ATPases and
H+-ATPases phosphorylated at the penultimate amino acid was analyzed by
immunoblotting using anti-H+-ATPases (H+-ATPases) and
anti-phosphorylated-threonine-947 (pThr947) antibodies, respectively. Quantifications of pThr947
signal relative to the H+-ATPases total signal were performed on three biological
replicates. Values are means, and error bars represent standard errors. * indicates
significant difference between means of light-treated samples compared to dark control
(P < 0.05).Regulation of H+-ATPase phosphorylation levels at pThr947 depends on
phototropins. Three-day-old seedlings of Col-0 (WT) or phot1phot2 mutant were
either kept in darkness (0) or irradiated with 10 μmol m−2
s−1 unilateral blue light for 30 min. Proteins were analyzed as described in (A).
*indicates significant difference between means of light-treated samples compared to dark
control (P < 0.05).Source data are available online for this figure.
Discussion
We investigated the importance of different factors on lateral auxin gradient formation
in silico by modeling auxin fluxes in an Arabidopsis thalianahypocotyl cross section. We thereby assume locality of perception and response, which was recently
demonstrated in Arabidopsis (Iino, 2001;
Preuten et al, 2013; Yamamoto et
al, 2014). The cross section used represents a
natural topology including the apoplastic space surrounding the cells, which was explicitly
represented because it provides a potentially important aspect of auxin transport (Kramer, 2007) and has also commonly been neglected in otherwise comparable
models (Grieneisen et al, 2007; Wabnik
et al, 2010; Santuari et
al, 2011).
Impact of morphological parameters on auxin gradient formation
Phototropic bending happens in the short hypocotyl cells in the elongation zone, and it is
usually assumed that this is due to the lack of growth potential in elongated cells (Kami et
al, 2012; Preuten et al, 2013; Yamamoto et al, 2014). Our results suggest that in addition to a reduced ability to grow, elongated
cells with concomitantly reduced apoplast thickness also have a reduced potential to form a lateral
auxin gradient (Fig 2C and Supplementary Figs S2 and S3)
(Derbyshire et al, 2007). During phototropic
bending of the hypocotyl, the epidermis on the shaded side elongates the most of all layers (MacLeod
et al, 1985; Orbovic & Poff, 1993) and it corresponds to the layer with the most wall material
(Derbyshire et al, 2007). Thereby, the
naturally observed topology favors both gradient formation and rapid elongation without the prior
need for new cell wall synthesis.Our model also predicts a strong impact of cell size distributions on gradient formation (Fig
2B and Supplementary Fig S2). Seedling morphology with small
cells enhances the potential to form a lateral auxin gradient. Moreover, a layer of small epidermal
cells, followed by large cortex cells and small endodermal cells, is favorable for the establishment
of a lateral auxin gradient while inverting the sizes of the cells in the different cell types
prevents gradient formation (Fig 2B). As expected for an
embryonic organ, the hypocotyl cellular arrangement is stereotypical with 33–36 epidermal, 13
outer cortex, 8 inner cortex, and 8–9 endodermis cells (Fig 1) (Gendreau et al, 1997; Crowell
et al, 2011). Intriguingly, the cell size
distribution present in Arabidopsis hypocotyls appears to be conserved among
angiosperms, suggesting the possibility of selection of morphological features that favor tropic
hypocotyl growth (Meyer, 1971; Busse et al,
2005).Our findings highlight the importance of cellular morphology that may constrain the formation of
auxin gradients. Several recent studies have provided evidence for links between mechanical/cellular
constraints and auxin-mediated growth processes (Heisler et al, 2010; Nakayama et al, 2012; Peret et al, 2012;
Lindeboom et al, 2013; Lucas et
al, 2013; Vermeer et al, 2014). Further investigating the relationship between cellular
morphology, the associated biophysical constraints and auxin-mediated growth processes are important
if we want to understand fundamental aspects of plant growth.
A role for regulated H+-ATPase activity in phototropism
We designed our starting modeling assumptions based on a paper that showed polar distribution of
PIN3 in the endodermis of the lit side during phototropism (Ding et al, 2011). Our model suggests that polarization of PIN3 in the
endodermis is not sufficient to create an auxin gradient (Fig 2 and Supplementary Fig S2). This does not mean that light-induced PIN3 relocalization is
unimportant, but suggests that additional mechanisms are required to promote auxin gradient
formation in photostimulated hypocotyls (see below). By testing a number of model parameters, we
identified modulation of apoplastic pH as a key step to form a lateral auxin gradient across the
hypocotyl of photo-stimulated seedlings. Apoplastic basification on the lit side and apoplastic
acidification on the shaded side is the optimal combination to establish a lateral auxin gradient
(Fig 2A). We propose that this leads to the concomitant
increase and decrease in growth rates on opposing sides of the stem that has been documented
previously (MacLeod et al, 1985; Orbovic
& Poff, 1993). Interestingly, pH changes have been
observed on the surface of gravi-stimulated Arabidopsis roots (Monshausen
et al, 2011) and appear to be linked to
intracellular pH modulation (Fasano et al, 2001; Boonsirichai et al, 2003;
Monshausen et al, 2011). Cytoplasmic
basification (that correlates with extracellular acidification) occurs within 2 min of
gravi-stimulation and precedes asymmetric distribution of PIN efflux carriers (Fasano et
al, 2001; Boonsirichai et al, 2003; Monshausen et al, 2011).We provide experimental evidence supporting this important modeling prediction; to modulate
apoplastic pH, we interfered with the plasma membrane H+-ATPase activity and
showed that this disrupts formation of a lateral auxin gradient preceding phototropism (Fig 4B and Supplementary Fig S6). The fact that both
H+-ATPase activation and inhibition negatively influenced phototropic bending
suggests that not only the proton pump activity but also an appropriate regulation of its activity
is required for an optimal growth response during phototropic stimulation (Fig 3 and Supplementary Fig S6). We therefore propose that differential apoplastic pH
regulation is achieved by a differential regulation of the H+-ATPase activity on
opposing hypocotyl sides, that is, activation on the shaded side and inhibition on the lit side.Phototropins are the primary photoreceptors triggering phototropism, but how their activation
leads to auxin gradient formation remains elusive (Sakai & Haga, 2012; Christie & Murphy, 2013; Hohm
et al, 2013). Phototropin (phot1) interacts
with and regulates the phosphorylation status of several proteins involved in phototropism (Pedmale
& Liscum, 2007; Christie et al, 2011; Demarsy et al, 2012; Takemiya et al, 2013). Here, we demonstrated that phosphorylation of the plasma membrane
H+-ATPases in the hypocotyl is regulated by the phototropins (Fig 5B). We propose that the phototropin-mediated control of
H+-ATPase phosphorylation is important to establish asymmetric hypocotyl growth
during phototropism. Asymmetric activation of the phototropins has been observed during unilateral
seedling irradiation (Salomon et al, 1997);
this may lead to differential phosphorylation/regulation of H+-ATPases across a
hypocotyl section.We showed that in the context of hypocotyl phototropism, phototropin activation inhibits
H+-ATPase phosphorylation. Phototropin-mediated regulation of
H+-ATPase phosphorylation has been observed for other physiological responses. For
example, during light-induced kidney bean movements, phototropin activation also leads to a
dephosphorylation of H+-ATPases in pulvini cells (Inoue et al,
2005). In contrast, in stomata, phototropin activation leads
to enhanced phosphorylation of H+-ATPases (Kinoshita & Shimazaki, 1999). In both cases, activation of phot1 leads to changes in the
phosphorylation status of the penultimate threonine of AHA proteins, which regulates their activity.
However, the steps leading from phototropin activation to the regulation of
H+-ATPases phosphorylation are not fully understood and depend on the context
(Takemiya et al, 2013).
Working model for lateral auxin gradient formation during phototropism
Our data highlight the importance of regulated H+-ATPase activity in the
establishment of an auxin gradient preceding phototropism (Figs 2, 3 and 4).
As auxin promotes H+-ATPase activity (Chen et al, 2010; Takahashi et al, 2012), we propose a model that includes feedback and feed-forward loops between
auxin transport and H+-ATPase regulation, thereby promoting auxin gradient
formation. On the lit side, reduced proton pump activity leads to apoplast basification decreasing
auxin uptake, and in turn, the decrease in intracellular auxin further reduces proton pump activity.
In contrast, on the shaded side, auxin uptake increases with H+-ATPase activity
leading to apoplast acidification. In turn, auxin accumulation in the cell further enhances proton
pump activity. Thus, a network of interlaced regulatory loops controls auxin gradient formation
during the phototropic response. Consistent with this idea, we show that interference with auxin
transport (NPA) and with H+ ATPase activity (FC) disrupts lateral auxin gradient
formation (Fig 4 and Supplementary Fig S6). This reciprocal
regulation of auxin concentration and H+-ATPase activity is reminiscent of the
complex relation between auxin concentration regulation and auxin transport as auxin regulates the
expression and localization of its own transporters (Krecek et al, 2009).Our mathematical model identified a novel mechanism required for auxin gradient formation that
was validated experimentally (Figs 2, 3 and 4). The strongest auxin gradients
predicted by our model (12% by considering vacuolated cells) were lower than what was
measured in maize coleoptiles and pea epicotyls, but nevertheless comparable to the 20%
gradient determined in hypocotyls of Brassica which are closely related to
Arabidopsis (Iino, 1992; Esmon et
al, 2006; Haga & Iino, 2006). The relatively shallow gradient predicted by our simulation contrasts with
the large difference in DII-Venus signal between the shaded and lit sides of the hypocotyl observed
here (Fig 4). However, we do not know how the in
vivo auxin concentration relates to the DII-Venus signal. Hence, it cannot be concluded
that a threefold change in DII-Venus signal corresponds to a threefold change in auxin
concentration. In our model, gradient strength is sensitive to auxin efflux carrier density, pumping
capacity, and coupling of the modeled cross section to cross sections above and below not explicitly
represented in the model (see Supplementary Materials and Methods). Thereby, the steepness of the
gradient depends on these parameters. And while these parameters can have a strong effect on
gradient strength, they do not impact the qualitative behavior of the model. We unfortunately lack
precise measurements for these parameters; however, the sensitivity of our model to efflux carrier
density and pumping capacity is in accordance with the experimental evidence showing that mutants
lacking several PINs show delayed and reduced phototropic responses (Friml et al,
2002; Ding et al, 2011; Haga & Sakai, 2012; Willige
et al, 2013). Additional factors that likely
favor gradient formation are the newly identified plasmodesmatal gating mechanism (Han et
al, 2014) and the activity of AUX1/LAX carriers
(Band et al, 2014). Indeed, since AUX1/LAX
carriers are proton symporters, one can hypothesize that they contribute to reinforcing the auxin
gradient formation: Apoplastic acidification and increase in H+ concentration on
the shaded side potentially increase AUX1/LAX-mediated active auxin uptake on the shaded side (Lomax
et al, 1995; Carrier et al,
2008; Steinacher et al, 2012). This could explain the delay in phototropism observed in the
quadruple auxlax1lax2lax3 mutant (Supplementary Fig S1). Importantly, a recent
study has shown that within the root tip, members of the AUX1/LAX family are essential to determine
which cells have high auxin levels (Band et al, 2014). Taken together with our results, we conclude that further studying of mechanisms
controlling entry of auxin into cells is very important to understand the distribution of this
hormone within plants. To extend our model and to refine our hypotheses, it would be interesting to
include the contribution of the AUX1/LAX family and the feedbacks between auxin transport and pH
regulation (Carrier et al, 2008; Krecek
et al, 2009; Lomax et al;
Steinacher et al, 2012). Finally, once the
link between phototropin activation and H+ ATPase activity is better understood,
it could be included directly into the model [similarly to the implementation of
auxin-induced apoplastic acidification described by Steinacher and colleagues (Steinacher et
al, 2012)] instead of treating pH change as
an exogenous variable.
Materials and Methods
Model
Description of the model, parameters and equations are provided as Supplementary Materials and
Methods and our modeling software coded in Matlab is available as Supplementary Code.
Plant material and growth conditions
The Columbia (Col-O) ecotype of A. thaliana was used as the WT. All the
following transgenic line and mutant alleles were in the Col-O background: aha1-6,
aha2-4 (Haruta et al, 2010), phot1-5phot2-1 (de Carbonnel et al, 2010), and DII-Venus (Brunoud et al, 2012). Seeds were surface-sterilized, sown on agar plates (½
strength MS pH 5.7 buffered with MES, 0.8% agar), and treated as described (Lariguet &
Fankhauser, 2004). For pharmacological treatments, seeds were
sown on nylon mesh (160 μm, Micropore) placed on the surface of the plate. Seedlings were
grown for 3 days in darkness at 22°C before indicated treatment. Light intensities were
determined with an International Light IL1400A photometer (Newburyport, MA) equipped with an SEL033
probe with appropriate light filters.
Pharmacological treatments
Nylon meshes with 3-day-old etiolated seedlings were transferred 1 h before indicated light
treatment onto freshly prepared plates supplemented by 0, 5, or 10 μM fusicoccin (FC, Sigma)
and 0.01% DMSO, or 0, 10, or 50 μM dicyclohexylcarbodiimide (DCCD, Sigma) and
0.01% ethanol, or 10 μM 1-N-naphthylphthalamic acid (NPA, Duchéfa).
Phototropism
Three-day-old etiolated seedlings (6- to 9-mm-long hypocotyls) grown on vertical agar plates were
irradiated with 10 μmol m−2 s−1 unilateral blue light for
24 h. Pictures were taken with an infrared camera at different time points. Angles formed by the
hypocotyl relative to vertical were measured with the NIH image software. Means, standard errors,
and Student's t-test were performed on 50 seedlings minimum.
DII-Venus signal visualization and quantification
Seedlings were grown as described for phototropism except that an additional 24-h treatment with
white light (25 μmol m−2 s−1) was applied to induce
de-etiolation. This treatment was necessary to allow detection of DII-Venus signal in the hypocotyl,
and the seedlings were still responding to phototropic stimulation and sensitive to FC treatment
(Supplementary Fig S6B and C).Imaging was performed on an LSM-510 laser-scanning confocal microscope (Zeiss). Serial optical
sections were acquired and quantification was performed as described in Supplementary Fig S6A.
Quantification of H+-ATPase phosphorylation level at Thr947
Three-day-old etiolated seedlings (6- to 9-mm-long hypocotyls) grown on vertical agar plates were
irradiated with 10 μmol m−2 s−1 unilateral blue light or
10 μmol m−2 s−1 blue light from above for indicated time
(0–30 min). Seedlings were fixed in EtOH-acetic acid solution (3:1) for 15 min and
transferred into 75% EtOH for 1–3 h. Proteins were extracted from 25 hypocotyls
sections grounded with a plastic pestles in 20 μl 1× phosphate-buffered saline (PBS)
containing 6 M urea and overnight incubation at room temperature. After addition of 30 μl
2× Laemmli buffer, proteins (10 μl per lane) were separated on 9%
SDS–polyacrylamide gels and transferred onto nitrocellulose with Tris-glycine buffer. The
blots were probed with antibodies raised against the catalytic domain of AHA2, or antibodies that
recognize peptide containing the phosphorylated Thr947 in AHA2 (Hayashi et al,
2010). These antibodies recognize not only AHA2 but also
other H+-ATPase isoforms in Arabidopsis (Hayashi et
al, 2010). Membranes were blocked in PBS,
0.1% Tween-20, and 5% nonfat milk (PBS-T-M) for 1 h at room temperature, incubated in
presence of the primary antibodies overnight at 4°C, washed three times in PBS-T-M, incubated
with a goat anti-rabbit IgG conjugated to horseradish peroxidase for 1 h at room temperature, and
washed three times in PBS-T-M. Chemiluminescence signals were generated using Immobilon Western HRP
Substrate (Millipore). Signals were captured with a Fujifilm ImageQuant LAS 4000 mini CCD camera
system, and quantifications were performed with ImageQuant TL software (GE Healthcare)
(Supplementary Fig S7).
Authors: Kanokporn Boonsirichai; John C Sedbrook; Rujin Chen; Simon Gilroy; Patrick H Masson Journal: Plant Cell Date: 2003-09-24 Impact factor: 11.277
Authors: Victor Aguilar-Hernández; Do-Young Kim; Robert J Stankey; Mark Scalf; Lloyd M Smith; Richard D Vierstra Journal: Mol Plant Date: 2017-04-28 Impact factor: 13.164
Authors: Mohamad Abbas; Jorge Hernández-García; Stephan Pollmann; Sophia L Samodelov; Martina Kolb; Jiří Friml; Ulrich Z Hammes; Matias D Zurbriggen; Miguel A Blázquez; David Alabadí Journal: Proc Natl Acad Sci U S A Date: 2018-06-13 Impact factor: 11.205