JXB Advance Access published online on March 7, 2007
Journal of Experimental Botany, doi:10.1093/jxb/erl289
RESEARCH PAPER |
Relationships of root conductivity and aquaporin gene expression in Pisum sativum: diurnal patterns and the response to HgCl2 and ABA
Department of Biology, Trent University, 1600 West Bank Drive, Peterborough, Ontario K9J 7B8, Canada
* To whom correspondence should be addressed: E-mail: nemery{at}trentu.ca
Received 7 November 2006; Accepted 30 November 2006
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Abstract |
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Experiments were undertaken to test how aquaporins (AQPs) facilitate the uptake of water by roots of Pisum sativum. Changes in PsPIP2-1 gene expression and root hydraulic conductivity (Lpr) were measured in response to the time of day as well as treatment of the roots with a compound that reduced Lpr [i.e. mercuric chloride (HgCl2)] and one that was intended to increase Lpr [abscisic acid (ABA)]. There was a diurnal rhythm in PsPIP2-1 expression in lateral roots that was strongly correlated with diurnal changes in Lpr. Taproots also displayed a rhythm in PsPIP2-1 expression, but this was offset from that of Lpr. This suggested that changes in Lpr were mediated by changes in PsPIP2-1 mRNA transcript abundance. Reduction of Lpr by HgCl2 treatment was accompanied by an increase in PsPIP2-1 expression, implying that PsPIP2-1 expression may have increased to compensate for AQPs blocked by mercury. ABA usually increased Lpr, but changes in PsPIP2-1 were variable and the direction of the response was strongly dependent on the dose of ABA that was applied. Overall, the coincident rhythms in Lpr and PIP2 expression and response to AQP blockage are consistent with the hypothesis that Lpr changes are mediated, at least in part, by changes in PsPIP2-1 expression. Inconsistencies with ABA data may have been due to more complex interactions of ABA with AQP channels.
Key words: ABA, aquaporin, mercuric chloride, Pisum sativum, root hydraulic conductivity
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Introduction |
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Aquaporins (AQPs) are membrane proteins that belong to the large family of major intrinsic proteins (MIPs; Agre et al., 1998). The most abundant group of AQPs is that of the plasma membrane (plasma membrane intrinsic proteins or PIPs). They are subdivided into two categories, PIP1 and PIP2 AQPs, the latter of which has been shown to have higher water channel activity (Chaumont et al., 2000).
Root water passage involves both radial and axial movement. Due to the absence of membranes, the role of AQPs along the axial pathway is negligible. However, radial water entry involves permeation across several layers of cells. It occurs along a combination of apoplastic, symplastic, and transcellular pathways (Steudle, 2000), and thus membranes must be traversed. This is the result of the endodermal (and often exodermal) Casparian band preventing water from moving directly into the xylem via the apoplast. Therefore, AQPs might facilitate water passage past such barriers by channelling the water through membranes.
A few lines of study have indicated that AQPs are necessary to assist water passage through roots. For example, Kaldenhoff et al. (1998) used antisense RNA to block the expression of an AQP gene in Arabidopsis and found that the AQP-knockout developed a much larger root system for which water permeability was 20–30% of that in controls. It was concluded that roots developed a larger surface area to compensate for the missing AQP.
The use of mercuric chloride (HgCl2) to inhibit root conductivity (Lpr) has further implicated a role for AQPs in water uptake. Since HgCl2 blocks most AQPs, it has been frequently used to estimate their contribution to whole root water transport (Javot and Maurel, 2002). Many studies have found that roots exposed to this compound experienced a decline in Lpr (reviewed in Javot and Maurel, 2002). This evidence indicated that AQPs are critical in bulk water flow and suggested that they are responsible for most of the water permeability of the plasma membrane (reviewed in Steudle, 2000).
In biophysical studies of root water entry, Emery and Salon (2002) and Murphy (2003) detected non-linear flow at high pressures by measurements in pressure chambers. Both studies suggested that this was consistent with a role for plasma membrane AQPs. Owing to their finite capacity to allow water to pass through, it was reasoned that at high pressures the water channels would become saturated and their inability to move an increasing volume of water would limit flow. Furthermore, maximum flow rates at high pressure changed diurnally (Emery and Salon 2002), increasing at 9:00 h, peaking at 11:00 h, and declining thereafter. Changes in conductivity were hypothesized to be correlated to changes in AQP abundance.
Investigations between Lpr rhythms and AQP gene expression have been undertaken in two studies, which showed that, similarly to Lpr, AQP expression exhibits a diurnal rhythm. Henzler et al. (1999) examined diurnal conductivity in Lotus japonicus and correlated this to changes in PIP1 transcript levels. They reported that Lpr peaked about midday and declined to a minimum at 20:30 h. Expression of two PIP1 genes showed some overlap with the diurnal Lpr rhythm, whereby Lpr peaked 5–7 h after onset of the photoperiod and AQP expression peaked 6–8 h into the photoperiod. Lpr declined to a minimum at 20:30 h, while AQP expression reached a minimum at either the same time or shortly thereafter (Henzler et al., 1999). In contrast, Lopez et al. (2003) found that peak transcript abundance of two PIP2 genes preceded maximum sap flux by 2–4 h and PIP protein levels peaked at the same time as maximum sap flux (i.e. midday). The discrepancy between these studies makes it uncertain if AQPs affect Lpr or whether their rhythms are coincidental.
The purpose of this study was to determine what factors contribute to how AQPs regulate the transfer of water from rhizosphere to xylem in pea. To address this, experiments combined measurements of Lpr and AQP gene expression. Based on the hypothesis that an increase in AQP expression would cause an increase in Lpr, three predictions were made: (i) diurnal changes in Lpr would be preceded by, or coincident with, changes in AQP expression; (ii) following manipulation to decrease Lpr, AQP expression should increase to compensate for the reduction in water flow through roots; and (iii) following manipulation to increase Lpr, AQP expression would decrease since AQPs would not be as critical for maintaining water flow.
Peas were used as the model system because their Lpr physiology has previously been described (Emery and Salon, 2002). Additionally, AQP genes in peas have been previously characterized by Schuurmans et al. (2003) who identified PsPIP2-1, the AQP gene used in this study. PsPIP2-1 belongs to the PIP2 subcategory of PIPs. PIP2 AQPs are of considerable interest since all plant PIP2 proteins examined in water permeability assays so far have shown higher water channel activity than their PIP1 counterparts, which had either low or no activity in several species (Fetter et al., 2003) and, in particular, peas (Schuurmans et al., 2003).
For the first prediction, an attempt was made to resolve the discrepancy between Henzler et al. (1999) and Lopez et al. (2003) by analysing the diurnal relationship between Lpr and PsPIP2-1 expression in greater detail. This was done by taking root heterogeneity into consideration since Hukin et al. (2002) found that AQP expression differs over various regions of the root. Thus, PsPIP2-1 expression was studied separately for tap and lateral roots. Lateral roots would perform most of the water uptake, based on greater available mass, and surface area and proportion that would be at a maturity conducive to water uptake (Waisel and Eshel, 2002). Moreover, quantitative real-time polymerase chain reaction (PCR) was used for its greater sensitivity for discerning differences in PsPIP2-1 mRNA levels among sampling time points.
To assess the second prediction, Lpr was reduced with HgCl2 to observe the influence on PsPIP2-1 expression. While the physiological effects of HgCl2 have been well described, its influence on AQP gene expression is unknown. It was expected that Hg2+ would reduce Lpr by blocking AQPs and that PsPIP2-1 expression would increase to compensate for this blockage. Furthermore, as concentrations of Hg2+ increased, a corresponding increase in AQP expression was predicted until the concentration of Hg2+ reached a toxic level.
To test the third prediction, roots were treated with abscisic acid (ABA), which is known to increase Lpr in most systems (Freundl et al., 1998; Quintero et al., 1999; Hose et al., 2000; Sauter et al., 2002; Lee et al., 2005; Schraut et al., 2005), although this effect is not thought to involve changes in AQPs (Quintero et al, 1999). It was predicted that the plants, which received adequate water, would be acclimated such that they would have appropriate levels of AQPs present in the roots. Thus, as Lpr increased, PsPIP2-1 expression would either remain the same or decrease since the same number or even fewer AQPs should be required to conduct the same amount of water. In both the HgCl2 and ABA experiments, a range of concentrations was applied to roots. Given the potential for diurnal fluctuations, the timing of application and root harvest was controlled precisely. Furthermore, the region of the root harvested for AQP expression analysis was the same for each experiment.
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Materials and methods |
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Growth conditions
Peas (Pisum sativum, Cutlass cultivar) were grown in a Conviron PGR15 (Winnipeg, MN) growth chamber with a 16 h light/8 h dark cycle.
Peas were grown in Ray Leach RLC-7UV Cone-tainersTM (Stuewe & Sons, Inc. Corvallis, OR, USA). Cone-tainersTM were used because they allow peas to develop uniform root systems, and their small size (115 ml) enabled them to fit inside the pressure chamber. Peas were planted in Fafardä Agro Mix (Saint-Bonaventure, QC, Canada), a sphagnum peat moss growing medium. Seeds were inoculated with NitraginTM pea inoculant (Milwaukee, WI, USA). Peas were watered regularly with deionized water. Once the shoot appeared on the surface of the soil, peas were watered to saturation on alternate days with nutrient solution (Emery and Salon, 2000). Excess water or nutrient solution drained out through holes in the bottom of pots or Cone-tainersTM.
Harvest
To study diurnal PsPIP2-1 expression, plants were harvested at 12:00, 3:00, 6:00, 9:00, 11:00, 13:00, 16:00, 19:00, and 22:00 h once they had reached the 6–8 node developmental stage. Peas used for conductivity experiments were harvested at the 6–8 node stage at 15:00 h and 17:00 h in addition to the times used for gene expression analysis. Three replicate plants were harvested at each time point for gene expression and conductivity experiments.
Root systems were removed from pots, and growth medium was washed off with water. Lateral roots were separated from taproots and each was cut 1–4 cm below the cotyledonary node and blotted dry with a paper towel. From each type of root, 30–100 mg of tissue was collected and stored inside a microfuge tube in RNAlater stabilization solution (Qiagen, Valencia, CA, USA). Samples were stored in a –80 °C freezer until they were used for RNA extraction.
Root conductivity (Lpr) analysis
Pressure-flow curves and Lpr calculations were generated using a pressure chamber as described in Emery and Salon (2002). Plants used for conductivity experiments were cut just below the first node. The cut surface of the shoot was thoroughly rinsed with distilled water. Each root system (still within its Cone-tainerTM) was sealed inside the pressure chamber and a piece of supple rubber tubing was fitted snugly around the root stump. The tube came out through the top of the chamber and delivered xylem exudate into pre-weighed microfuge tubes. Pressures of 0.05, 0.10, 0.20, 0.30, 0.40, 0.50, and 0.60 MPa were applied to the chamber using an air compressor (Mastercraft Model No. 820218, Toronto, ON, Canada). Stepwise pressure increments were made every 10 min. Microfuge tubes were re-weighed at the end of the experiment to determine the volume of xylem exudate that flowed at each pressure. Plants were removed from the pressure chamber and their roots washed to remove soil. Roots were weighed after drying them in an oven for 48 h at 50 °C. Once a plant had been subjected to pressure-flow manipulations, it was not used in other experiments.
Mercuric chloride treatment
For gene expression analysis, 50 ml of 1, 10, or 100 µM HgCl2 (Fisher, Fair Lawn, NJ, USA) was poured onto the soil 1 h and 3 h prior to harvesting the roots at 9:00, 11:00, and 16:00 h. Controls received 50 ml of water. All treatments were performed in triplicate.
The same HgCl2 concentrations used in gene expression analysis were used for root conductivity measurements (i.e. 1, 10, and 100 µM). At 1 h prior to harvesting, 30 ml of HgCl2 solution was delivered directly to the soil. The 3 h exposure was not used for conductivity experiments. Controls received 30 ml of water. Plants were harvested at 16:00 h. All treatments were performed in triplicate.
Abscisic acid treatment
For gene expression analysis, roots were treated with 50 ml of 0.01, 1, 10, and 100 µM (±)-2-cis-4-trans ABA (Lancaster, Pelham, NH, USA) at 24 h prior to harvest, while controls received 50 ml of water. Plants were harvested at 9:00, 11:00, and 16:00 h. All treatments were done in triplicate. ABA was diluted to its final concentration using ultra pure water.
The same ABA concentrations used in gene expression analysis were used for conductivity measurements (i.e. 0.01, 1, 10, and 100 µM). Twenty-four hours prior to harvesting, 30 ml of each ABA solution was applied to the soil, while controls received 30 ml of water. Plants were harvested at 16:00 h. All treatments were done in triplicate.
RNA extraction and quantification
RNA was extracted from roots using the RNeasy Plant Mini Kit (Qiagen, Valencia, CA, USA) and stored at –80 °C. The RNA concentration was measured on a Nanodrop® ND-1000 UV-visible spectrophotometer (Wilmington, DE, USA).
Real-time PCR
Diethylpyrocarbonate (DEPC)-treated water was used to dilute RNA to 0.5 ng ml–1 prior to its use in real-time PCR. Gene expression analysis was performed on the ABI 7900HT (Applied Biosystems, Foster City, CA, USA).
Reactions were set up in a 96-well plate using the QuantitectTM SYBR® Green RT-PCR Kit (Qiagen, Valencia, CA, USA). A 2 µl aliquot (1 ng) of RNA was added to each well in the plate. A master mix containing reaction buffer, dNTPs, PIP2 or GAPDH primers (to a final concentration of 0.4 µM), ROX (passive reference dye), MgCl2, RNase-free water, HotStarTaqTM polymerase, and Omniscript and Sensiscript reverse transcriptases were added to bring the total reaction volume in each well to 20 µl. Plates were sealed using an optical cover and placed inside the ABI 7900HT. Primers used to amplify PIP2-1 and glyceraldehyde phosphate dehydrogenase (GAPDH) are given in Table 1.
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The ABI 7900HT was programmed as follows: 30 min at 50 °C for reverse transcription; 15 min at 95 °C to inactivate the reverse transcriptase enzymes and activate HotStarTaqTM DNA polymerase; 40 cycles of 15 s at 94 °C, 30 s at 60 °C, and 30 s at 72 °C. Data collection was carried out during the 72 °C extension step. A dissociation curve was constructed following completion of 40 amplification cycles. No-template controls and no-reverse transcriptase controls were included to ensure that reagents and samples were free of contamination. Standard curves were generated for PsPIP2-1 and GAPDH in each experiment. All samples (standards, controls, and unknowns) were run in triplicate to account for variations in pipetting.
Analysis of real-time PCR data
Conversion of cycle threshold (CT) values into relative RNA quantities was followed according to the instructions outlined in the ABI Prism 7700 Sequence Detection System User Bulletin #2 (Applied Biosystems, 2001). Expression of PsPIP2-1 was normalized by dividing its mean relative value by the mean relative GAPDH value. The smallest normalized PsPIP2-1 value was designated as the calibrator and all other normalized values were divided by the calibrator's normalized value.
Transpiration measurements
Transpiration was measured using a LI-1600 Steady-State Porometer (LI-COR, Lincoln, NE, USA). Measurements were taken from one leaf on each plant at 6:00, 9:00, 11:00, 16:00, and 19:00 h. The same leaf was measured at each time point and the leaf chosen for measurement was always located at one of the top two nodes on the pea. This ensured that variation in transpiration between young and old leaves was not a factor.
In the HgCl2 experiments, transpiration was measured at 9:00, 11:00, or 16:00 h the day before HgCl2 was applied to roots. The next day roots were exposed to HgCl2 for 1 h or 3 h. Prior to harvesting plants at 9:00, 11:00, or 16:00 h for gene expression analysis, transpiration was again measured. This enabled data to be expressed as a percentage of transpiration prior to HgCl2 treatment. Transpiration was only measured in roots exposed to HgCl2 for 3 h. As in the diurnal and ABA experiments, the same leaf from each plant was used on both days to ensure that variations between individual leaves on the same plant would not be a factor.
In ABA experiments, transpiration was measured at 9:00, 11:00, and 16:00 h. Since roots were exposed to ABA for 24 h, these data were collected just before treating roots with the hormone. The next day, transpiration was measured again at 9:00, 11:00, and 16:00 h. Following this, roots were harvested for gene expression analysis.
Statistical analysis
Statistical analyses were completed using KaleidaGraph 4.0 software (Synergy Software, Reading, PA, USA). Within each experiment, detection of differences among means was performed using one-way analysis of variance (ANOVA) followed by the Fisher's least significant difference (LSD) post hoc test (P <0.05).
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Results |
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Diurnal experiment
Hydraulic conductivity was calculated from the slope of pressure-flow curves to measure changes in Lpr throughout a 24 h period to determine any correlation with changes in PsPIP2-1 expression.
During a 24 h period, Lpr displayed two peaks. The first occurred at 9:00 h and the second between 15:00 h and 17:00 h (Fig. 1). Increases in Lpr relative to those at midnight were 
220% and 250%, respectively. One-way ANOVA and subsequent LSD analysis revealed that the Lpr peaks at 9:00 h and 15:00–17:00 h were significantly different from Lpr at 11:00 h (P <0.05).
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Real-time PCR was used to examine expression of the PsPIP2-1 gene in lateral roots and taproots of pea during a 24 h period. Expression of PsPIP2-1 differed in lateral roots and taproots (Fig. 1). In both tissues, PsPIP2-1 transcript levels were at a minimum at midnight. In lateral roots, expression of PsPIP2-1 increased at 6:00 h and reached a maximum at 9:00 h (Fig. 1A). At 9:00 h, PsPIP2-1 expression was >4-fold greater than at midnight. This declined throughout the remainder of the morning and during the early afternoon. At 16:00 h, transcript abundance increased to almost 3-fold the value at midnight. Following this, expression declined for the next 6 h and at 22:00 h it approached a value similar to the value observed at midnight. ANOVA and LSD post hoc analysis demonstrated that PsPIP2-1 expression at 9:00 h was significantly different from PsPIP2-1 levels at all other times of the day (P <0.05).
Taproots followed a different expression rhythm from that of lateral roots. PsPIP2-1 increased 3-fold from midnight to 6:00 h. After this, expression decreased slightly at 9:00 h but increased again at 11:00 h (Fig. 1B). Transcript levels were almost 4-fold greater at 11:00 h than at midnight. For the remainder of the day, PsPIP2-1 expression steadily declined and at 22:00 h approached values similar to those at midnight. Increases in taproot PsPIP2-1 transcript abundance were not significantly different (P >0.05).
The diurnal experiment demonstrated that changes in Lpr coincided with changes in lateral root PsPIP2-1 expression. Specifically, when Lpr increased, so did PsPIP2-1 expression in the lateral roots. In contrast, the peaks in PsPIP2-1 expression in taproots preceded the peaks in Lpr by 3–6 h.
Mercuric chloride treatment
Roots were treated with HgCl2 for 1 h to manipulate their hydraulic conductivity. The purpose of this was to decrease Lpr and then determine if this had an effect on PsPIP2-1 expression.
Since the diurnal experiment revealed that Lpr was greatest during the afternoon, 16:00 h was chosen as the time to measure Lpr changes in roots treated with HgCl2 and ABA. Because gene expression was not quantified at 15:00 h and 17:00 h, these times were not used for Lpr manipulations. Therefore, the Lpr changes in HgCl2- and ABA-treated roots were all measured at 16:00 h.
Peas were treated with HgCl2 to reduce their Lpr. In all plants treated with 1, 10, or 100 µM HgCl2, Lpr was less than in controls that received only water (Fig. 2). Specifically, Lpr in controls was significantly different from Lpr in roots treated with 1 µM HgCl2 (P <0.05). On the whole, HgCl2 reduced Lpr to 50% of control values.
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Gene expression was measured at 9:00, 11:00, and 16:00 h. In addition, PsPIP2-1 expression was evaluated in roots exposed to HgCl2 for 3 h. In six of nine treatments, roots exposed to HgCl2 for 1 h experienced an increase in PsPIP2-1 expression, relative to controls (Fig. 2). Exceptions to this were in 1 µM- and 10 µM-treated roots harvested at 9:00 h and 1 µM-treated roots harvested at 16:00 h. At each time point examined, 100 µM HgCl2 increased PsPIP2-1 expression more than the lower HgCl2 concentrations. At 9:00 h PsPIP2-1 expression was significantly different in roots treated with 10 µM versus 100 µM HgCl2 (P <0.05). The next most effective concentration for increasing AQP expression was 10 µM HgCl2 at 11:00 h and 16:00 h.
In contrast to roots treated with HgCl2 for 1 h, 3 h of exposure caused a decline in PsPIP2-1 expression relative to controls at all times and all concentrations (data not shown). The only exception was in roots exposed to 10 µM HgCl2 and harvested at 11:00 h. In this case, expression was 20% greater than in the control. In general, the pattern was that PsPIP2-1 expression increased in roots treated with HgCl2 for 1 h and decreased in roots treated with HgCl2 for 3 h.
ABA treatment
ABA was added in an effort to increase Lpr and determine if this had any effect on PsPIP2-1 expression. Gene expression was measured using real-time PCR in roots exposed to 0.01, 1, 10, or 100 µM ABA for 24 h (Fig. 3).
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Plants treated with 0.01, 1, and 10 µM ABA for 24 h experienced an increase in Lpr relative to controls (Fig. 3). This was most pronounced in 0.01 µM and 10 µM treatments that displayed Lpr values
2.5 times greater than controls. Lpr readings in roots treated with 0.01 µM or 10 µM ABA were significantly different from those of controls, 1 µM and 100 µM ABA-exposed roots (P <0.05). In roots treated with 100 µM ABA, Lpr was reduced to almost 50% of that of controls.
At 9:00 h, 1 µM and 10 µM ABA increased PsPIP2-1 30% and 50% relative to controls. At 11:00 h, these same concentrations increased PsPIP2-1 expression (40%), and by 16:00 h very little difference existed between these treatments and controls (Fig. 3). However, at 9:00 h and 11:00 h, the data for 1 µM and 10 µM ABA treatments were quite variable.
In contrast, 0.01 µM and 100 µM ABA generally reduced PsPIP2-1 transcript abundance. This was most pronounced at 9:00 h and 16:00 h when expression decreased relative to controls. At 9:00 h and 11:00 h, PsPIP2-1 expression levels in 100 µM-exposed roots were significantly different from controls and 1 µM and 10 µM treatments (P <0.05).
For all real-time PCR experiments, no-template (NTC) and no-reverse transcriptase (no-RT) control reactions were included. Negative NTC controls meant reagents were free of contamination; negative no-RT controls indicated that genomic DNA was not amplified.
Transpiration
To determine if Lpr or PsPIP2-1 expression was driven by water demand, transpiration was evaluated in 15 replicate plants at 6:00, 9:00, 11:00, 16:00, and 19:00 h. The purpose of this was to establish if there was a diurnal transpiration pattern. Such a rhythm would suggest that water usage changed during the day and could be compared with Lpr and PsPIP2-1 expression data to see if there was a correlation. This experiment revealed that transpiration increased steadily after 6:00 h, peaked at 9:00 h, and declined for the remainder of the day (Table 2). Mean transpiration values varied significantly throughout the day (P <0.05). Most notably, the 9:00 h peak was different from that at 6:00, 16:00, and 19:00 h, while that at 11:00 h was significantly different from those at 16:00 h and 19:00 h. The increase in transpiration at 9:00 h coincided with the first peak in Lpr as well as the rise in lateral root PsPIP2-1 expression at 9:00 h. However, when lateral root PsPIP2-1 expression increased again at 16:00 h, transpiration was declining. This indicated that diurnal changes in transpiration were not correlated to changes in Lpr or PsPIP2-1 expression.
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Roots were treated with HgCl2 for 3 h and transpiration measurements were made at 9:00, 11:00, and 16:00 h. Data in roots treated with 1, 10, or 100 µM HgCl2 (Table 2) were not significantly different from those in controls at 9:00 h and 16:00 h (P >0.05). At 11:00 h, all concentrations of HgCl2 caused a slight decline in transpiration relative to controls, and all of these changes were statistically significant.
With the exception of a single treatment (0.01 µM at 16:00 h), all plants treated with ABA (0.01, 1, 10, or 100 µM) for 24 h experienced a decline in transpiration relative to controls (Table 2). Most of the reductions in transpiration following ABA treatment were statistically significant (P <0.05). The magnitude of the reduction increased as the ABA concentration increased.
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Discussion |
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TopAbstractIntroductionMaterials and methodsResultsDiscussionReferences |
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This study investigated how AQPs are involved in root water uptake from rhizosphere to xylem. To address this question, root conductivity, Lpr, and expression of an AQP gene, PsPIP2-1, were quantified in roots of P. sativum over a 24 h period as well as in response to treatment with a compound that decreases Lpr (HgCl2) and one that was intended to increase Lpr (ABA).
The majority of the data supported the hypothesis that changes in PsPIP2-1 expression were related to dynamics of pea root Lpr. Firstly, diurnal changes in lateral root PsPIP2-1 expression coincided exactly with the diurnal Lpr rhythm. Secondly, in roots treated with HgCl2, a reduction in Lpr coincided with increased PsPIP2-1 expression. As root conductivity decreased due to HgCl2 exposure, PsPIP2-1 expression increased, perhaps to compensate for those AQPs blocked by Hg2+. However, roots exposed to increasing concentrations of ABA did not display predictable changes in PsPIP2-1 transcript abundance. Although changes in PsPIP2-1 mRNA abundance were not correlated to the application of ABA, this could be the result of an interaction between the protein and hormone that is not yet well understood.
Diurnal Lpr and PsPIP2-1 rhythm
To test the hypothesis that AQPs increase Lpr in pea roots, Lpr and PsPIP2-1 expression were measured during a 24 h period. It was predicted that changes in PsPIP2-1 transcript abundance would either just precede, or directly coincide with, changes in Lpr. In lateral roots, this prediction was supported since there was a strong correlation between PsPIP2-1 expression in lateral roots and Lpr. Specifically, PsPIP2-1 expression displayed two distinct peaks at 9:00 h and 16:00 h. At all other times, PsPIP2-1 expression was very close to its baseline expression level at midnight. Similarly, Lpr reached maxima at 9:00 h and 16:00 h. The distinct overlap in their peaks demonstrated that changes in Lpr were correlated to changes in PsPIP2-1 transcript abundance. Therefore, conductivity increases may have been mediated by increases in PsPIP2-1 abundance. This is supported by Schuurmans et al. (2003) who found that PsPIP2-1 proteins exhibited the greatest water permeability of all the known AQP proteins in pea.
Increases in taproot PsPIP2-1 preceded increases in Lpr by 3–6 h. While PsPIP2-1 displayed two peaks in taproots at 6:00 h and 11:00 h, Lpr peaked at 9:00 h, and between 15:00 h and 17:00 h. The lack of a relationship between PsPIP2-1 expression and Lpr in taproots suggests that AQPs in taproots may have a less significant role in water uptake than AQPs in lateral roots. The taproot comprises a very small proportion of the total root system area, compared with the lateral roots, which take up the majority of water used by the plant. However, these results emphasize the importance of studying these two types of roots separately since analysis of a mixture of tap and lateral roots may not have revealed any consistent diurnal rhythm of PsPIP2-1 expression.
A rhythm in AQP gene expression has been identified in other studies that have monitored it over the course of a day (Henzler et al., 1999; Lopez et al., 2003). The present findings are more consistent with the results of Henzler et al. (1999) who found an overlap in PIP1 gene expression and Lpr. Similar to Henzler et al. (1999) who found that AQP expression followed a circadian rhythm, the present data also indicated that PsPIP2-1 expression exhibits circadian behaviour. In their study though, the increase in Lpr slightly preceded the increase in PIP1 expression. In contrast, Lopez et al. (2003) found that peaks in AQP expression were late and out of phase with water movement. Inconsistencies between L. japonicus (Henzler et al., 1999), maize (Lopez et al., 2003), and the present study could be attributed to a number of factors. The most obvious is, firstly, that a different species was used in each study. Secondly, neither Henzler et al. (1999) nor Lopez et al. (2003) specified whether lateral roots or the taproots were used for gene expression analysis. The present study revealed that the type of tissue sampled is critical since PsPIP2-1 was differentially expressed in lateral roots and taproots. Moreover, Hukin et al. (2002) found that variation in AQP abundance exists at even small intervals along the root-growing zone of maize as the expression of two AQP genes increased in the more mature region of the root. Previous studies also did not specify which region of the root was used to harvest tissue. In the present study, lateral root and taproot tissue were always harvested 1–4 cm below the cotyledonary node. As a more developed part of the root, this region would offer some degree of apoplastic blockage (Schreiber et al., 1999).
Thirdly, the physiological determination of apparent root conductivity by Lopez et al. (2003) was measured using spontaneous root system sap exudation upon shoot removal and not Lpr. In field studies of pea, it was found that there is no correspondence between Lpr generated from pressure chamber manipulations and spontaneous sap exudation from cut root stumps (Emery and Salon, 2002; Emery et al., 2002). Thus, caution should be used in comparing the results of those two techniques.
HgCl2—effects on PsPIP2-1 and Lpr
To test the prediction that a reduction in Lpr would increase PsPIP2-1 expression, HgCl2 was applied to block AQPs physically. With the exception of 9:00 h, this prediction was not supported by statistical analysis. Many of the roots treated with HgCl2 for 1 h and harvested at 9:00, 11:00, or 16:00 h displayed an increase in PsPIP2-1 expression but the only significant difference in expression was between roots treated with 10 µM and 100 µM HgCl2 at 9:00 h. The treatments that did not increase PsPIP2-1 expression over controls mostly occurred in plants exposed to low doses of HgCl2, (mainly 1 µM). Following exposures to higher concentrations, the increased PsPIP2-1 expression coincided with a significant decrease in Lpr. The decline in Lpr occurred regardless of the concentration of HgCl2. These latter data are in agreement with the many studies that have shown that treating roots with HgCl2 causes a reduction in their ability to conduct water, presumably through AQPs (reviewed in Javot and Maurel, 2002). Therefore, the inverse relationship between 10 µM and 100 µM HgCl2 and PsPIP2-1 expression supports the idea that blockage by HgCl2 would up-regulate PsPIP2-1 expression to compensate for restricted water movement.
Although it could be argued that the response to the high HgCl2 concentrations in the present study was due to Hg2+ toxicity, other studies have reported the use of even greater concentrations without damaging plant cells. Maggio and Joly (1995) exposed tomato roots to 500 µM HgCl2 for >2 h and measured Lpr using a pressure chamber. They found that not only did Lpr decrease by 57%, but there was no significant change in osmotic potential, or K+ concentration of xylem exudates, and no divergence in pressure flow linear responses. A linear pressure-flow response was also observed in the present study at all concentrations of HgCl2. However, the duration of the exposure of pea roots to HgCl2 influenced PsPIP2-1 expression. While expression generally increased in roots treated with HgCl2 for 1 h, the opposite effect was seen after 3 h. With the exception of roots exposed to 10 µM HgCl2 for 3 h and harvested at 11:00 h, all other 3 h treatments caused a decline in PsPIP2-1 expression (data not shown). Therefore, it is thought that a 3 h exposure was toxic to the roots.
ABA—effects on PsPIP2-1 and Lpr
To test the prediction that increasing Lpr would decrease the expression of PsPIP2-1, ABA was applied as a root drench. Roots were treated with a range of ABA concentrations. The greatest concentration (100 µM) was tested since it has been commonly used in other studies; however, it is so large that it is not likely to be physiologically relevant. The rationale was that AQP expression would decline because ABA is known to increase Lpr in most systems (Freundl et al., 1998; Quintero et al., 1999; Hose et al., 2000; Sauter et al., 2002; Lee et al., 2005; Schraut et al., 2005). It was assumed the plant would be acclimated with pre-existing AQPs so that as Lpr increased, the same number of or even fewer AQPs would be required to conduct the same amount of water. With a few exceptions, this prediction was not supported.
Changes in PsPIP2-1 expression and Lpr were not correlated in the ABA-treated samples, and the response of these two variables was highly ABA dose dependent. At 16:00 h, the lowest and highest concentrations of ABA (0.01 µM and 100 µM, respectively) lowered PsPIP2-1 expression, and intermediate concentrations had no effect relative to controls. The effect on Lpr at 16:00 h was also dependent on the ABA concentration. ABA elicited a typical hormone response curve whereby low to medium concentrations promoted Lpr but high concentrations led to a decline in Lpr. Curiously, 1 µM ABA caused very little change in PsPIP2-1 expression or Lpr relative to controls. At 9:00 h and 11:00 h, the trend in PsPIP2-1 expression was almost identical to the pattern at 16:00 h. Normally, ABA has been applied in the range of 0.005–4 µM (Freundl et al., 1998; Quintero et al., 1999; Hose et al., 2000; Sauter et al., 2002; Schraut et al., 2005). Therefore, 100 µM ABA was too high a concentration to be physiologically relevant and the Lpr decline at this dose may have been caused by hormone toxicity. Although other physiological studies reported that Lpr increased at lower ABA concentrations (this study found the same when 0.01, 1, and 10 µM ABA were applied), none examined AQP gene expression at the same time to determine if the two factors were related. Several studies have examined AQP gene expression (although without corresponding Lpr data) in various plant tissues treated with ABA. All show that the AQP response is complex (Weig et al., 1997; Mariaux et al., 1998; Jang et al., 2004).
The ABA component of this study does not support the hypothesis that PIP2 AQPs are functionally involved in regulating Lpr changes. However, unlike HgCl2, the effect of ABA on AQPs is largely unknown. Whether or not ABA increases Lpr in roots through a direct or indirect interaction with AQPs remains unclear. It has been suggested that ABA stabilizes AQPs by binding to and maintaining these channels in an open conformation (Wan et al., 2004; Lee et al., 2005), although this hypothesis remains speculative.
It has been proposed that ABA increases Lpr during periods of water stress so the plant can capture all available water remaining in the soil (Javot and Maurel, 2002). However, without understanding how ABA increases Lpr, one can only speculate that it might occur through an interaction with AQPs. The process could be more complex and involve a cascade of events that include other signalling processes within the cell or an interaction with other hormones. This hypothesis is supported by the complex transcriptional response in a number of AQP genes in ABA-treated roots of Arabidopsis and Craterostigma plantagineum (Weig et al., 1997; Mariaux et al., 1998; Jang et al., 2004). These studies demonstrated that PIP2s respond differentially to ABA treatment and that such a response may involve both ABA-dependent and independent signalling pathways (Mariaux et al., 1998; Jang et al., 2004).
Water demand
When HgCl2 was applied to roots, there was often no difference in transpiration between Hg2+-treated roots and controls (Table 2). In contrast, ABA caused a marked decrease in transpiration, an effect that has been known for some time (Dodd and Davies, 2004). However, because diurnal changes in transpiration were not correlated to changes in Lpr or PsPIP2-1 gene expression, there is little evidence to suggest that Lpr or PsPIP2-1 expression were driven by water demand. Furthermore, although the simultaneous increase of Lpr and transpiration rate has been shown previously (Mees and Weatherley, 1957; Passioura and Tanner, 1985), there do not appear to be any studies that have correlated AQP expression with changes in transpiration. Henzler et al. (1999) also examined both factors, but found no relationship between PIP1 transcript abundance and transpiration rate.
Future steps towards understanding the role of pea PIP2 AQPs in root water uptake will be to determine if changes in PsPIP2-1 protein levels are correlated to the PsPIP2-1 gene expression and Lpr changes that have been demonstrated. This could be studied using an antibody to monitor changes in PsPIP2-1 protein levels, or by using RNA interference (RNAi) to knock out the expression of the gene. Additionally, a histological approach could be used to determine where along the radial pathway PsPIP2-1 is most prevalent. By establishing its location along the root cylinder, it will be possible to resolve which layer of cells is utilized to facilitate xylem water entry. A further study could involve examining AQP expression in a species in which the path of water movement is largely apoplastic. For example, modelling and the inhibition of AQP activity with HgCl2 has determined that radial water flow in lupins is predominantly apoplastic, whereas that of wheat uses a combination of cell–cell and apoplast pathways (Bramley, 2006). Thus, in the case of a species such as lupin, Lpr should not be as limiting, and it would be predicted that AQP expression would be unaffected by treatment with HgCl2. All of these approaches would offer further insight into the functional role AQPs play in root water uptake.
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Acknowledgements |
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This research was supported by Natural Science and Engineering Research Council (NSERC) Discovery Grants to RJNE and JY.
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Abbreviations |
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ABA, abscisic acid; ANOVA, analysis of variance; AQP, aquaporin; GAPDH, glyceraldehyde phosphate dehydrogenase; Lpr, root hydraulic conductivity; LSD, least significant difference..
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