Differential response of poplar (P. x canescens) leaves and roots ...

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Running title:

Hypoxia tolerance of poplar

Corresponding author:

Jürgen Kreuzwieser, Professur für Baumphysiologie, Albert-Ludwigs-Universität

Freiburg, Georges-Köhler-Allee Geb. 053/054, Germany

e-mail [email protected]

phone +49 761 203 8311

fax +49 761 203 8302

Research area:

Whole plant and ecophysiology

Plant Physiology Preview. Published on November 12, 2008, as DOI:10.1104/pp.108.125989

Copyright 2008 by the American Society of Plant Biologists

www.plantphysiol.orgon April 12, 2018 - Published by Downloaded from Copyright © 2008 American Society of Plant Biologists. All rights reserved.

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Differential response of poplar (P. x canescens) leaves and roots underpins

stress adaptation during hypoxia

Jürgen Kreuzwieser1,2,*, Jost Hauberg1, Katharine A. Howell2,3, Adam Carroll2, Heinz

Rennenberg1, A. Harvey Millar2, James Whelan2

1Albert-Ludwigs-Universität Freiburg; Institut für Forstbotanik und Baumphysiologie;

Professur für Baumphysiologie, Georges-Köhler-Allee Geb. 053/054, D-79110 Freiburg

i. Br., Germany. 2ARC Centre of Excellence in Plant Energy Biology, The University of

Western Australia, M316 Crawley WA 6009, Australia. 3Max-Planck-Institut für

Molekulare Pflanzenphysiologie, Am Mühlenberg 1, 14476 Potsdam-Golm, Germany.

Correspondence:

Dr. Jürgen Kreuzwieser,

Albert-Ludwigs-Universität Freiburg;

Institut für Forstbotanik und Baumphysiologie,

Professur für Baumphysiologie

Georges-Köhler-Allee Geb. 053/054

D-79110 Freiburg

tel +49 761 203 8311

fax +49 761 203 8302

E-Mail:

Email-addresses:

[email protected]; [email protected];

[email protected]; [email protected];

[email protected]; [email protected]



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Footnotes:

This study was funded by the Australian Research Council Linkage Fellowship

(LX0664516) and the German Science Foundation (DFG) under contract number

Kr2010/1.

*Corresponding author; e-mail [email protected]



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Abstract

The molecular and physiological responses of Grey poplar (Populus x canescens)

following root hypoxia were studied in roots and leaves using transcript and metabolite

profiling. The results indicate that there were changes in metabolite levels in both

organs, but changes in transcript abundance were restricted to the roots. In roots,

starch and sucrose degradation were altered under hypoxia, and concurrently, the

availability of carbohydrates was enhanced, concomitant with depletion of sucrose from

leaves and elevation of sucrose in the phloem. Consistent with the above, glycolytic

flux and ethanolic fermentation were stimulated in roots but not leaves. Various mRNAs

encoding components of biosynthetic pathways such as secondary cell wall formation,

i.e. cellulose and lignin biosynthesis, and other energy demanding processes such as

transport of nutrients, were significantly down-regulated in roots but not in leaves. The

reduction of biosynthesis was unexpected, as shoot growth was not affected by root

hypoxia suggesting that the up-regulation of glycolysis yields sufficient energy to

maintain growth. Besides carbon metabolism, nitrogen metabolism was severely

affected in roots as seen from numerous changes in the transcriptome and the

metabolome related to N uptake, N assimilation, and amino acid metabolism. The

coordinated physiological and molecular responses in leaves and roots, coupled with

transport of metabolites reveal important stress adaptations to ensure survival during

long periods of root hypoxia.



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Introduction

Higher plants are aerobic organisms and depend on the availability of O2. A lack

of O2 in the rhizosphere affects the maintenance of numerous pathways and is

therefore an important environmental stress for vascular plants (Drew, 1997). Plant

adaptations to O2 deprivation include avoidance strategies at the morphological level

and physiological tolerance mechanisms (Bailey-Serres and Voesenek, 2008). One of

the major cellular pathways dependent on O2 is mitochondrial respiration. In order to

maintain energy generation under conditions of decreased O2 availability, plants switch

from respiration to fermentative metabolism. Fermentation allows regeneration of NAD+

in the absence of respiration, thereby maintaining glycolysis and the generation of ATP

under anaerobic conditions. As an initial reaction to O2 deprivation, many plants

activate lactic acid fermentation. As generation of lactic acid causes a decrease in

cytosolic pH (Roberts et al., 1984) which reduces the activity of the responsible

enzyme, lactate dehydrogenase (LDH) (Hanson and Jacobson, 1984), lactic acid

fermentation is followed by alcoholic fermentation (Davies et al., 1974; Roberts et al.,

1984). The significantly lower energy yield of alcoholic fermentation, compared to

mitochondrial respiration, causes an energy crisis in anaerobic tissues (Bailey-Serres

and Voesenek, 2008).

A high rate of fermentation increases the demand for carbohydrates, leading to

the hypothesis that carbohydrate supply becomes critical for survival under prolonged

hypoxic conditions. This assumption is supported by the following: (1) improved

survival of flood sensitive species by exogenous supply of sugars (Waters et al. 1991,

Perata et al. 1992, Loreti et al., 2005), (2) activation of glycolytic enzymes by hypoxia

(Setter et al. 1997, Loreti et al. 2005, Liu et al. 2005) and (3) decreased flooding

tolerance when the synthesis of these enzymes is inhibited (Subbaiah et al. 1994).

Although carbon and energy metabolism have been identified to play a crucial role for

the physiological adaptation of plants to hypoxia, it has not yet been clarified what

mechanisms ensure the steady supply of carbohydrates to hypoxic tissues of tolerant

plant species. Furthermore, the changes observed in response to O2 deficit are caused

and accompanied by altered gene expression patterns such as enhanced transcription

of genes required for fermentation and morphological adaptations (Bailey-Serres and

Voesenek, 2008). The latter include genes involved in ethylene biosynthesis,

programmed cell death, ethylene signal transduction and cell wall lysis (Klok et al.,

2002). Moreover, transcript levels of enzymes required for biosynthetic processes such

as cell wall synthesis and flavonoid biosynthesis are reduced (Klok et al., 2002;



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Geigenberger, 2003; Branco-Price et al., 2008, van Dongen et al., 2008).

Although the morphology and physiology of plants grown under anaerobic

conditions have been studied in detail (including the targeted analysis of specific

metabolites), limited work has been done to elucidate adaptations at the molecular

level. While some microarray studies have been performed (Klok et al., 2002; Loreti et

al., 2005; Liu et al., 2005; Branco-Price et al., 2005; Lasanthi-Kudahettige et al., 2007;

Branco-Price et al., 2008, van Dongen et al., 2008), the regulation of anaerobically

induced genes and the integration of metabolic responses in hypoxic organs with that

of attached normoxic feeder organs has not been comprehensively studied at a

molecular level. Furthermore, there have been no previous reports of the differences

between trees and annual species, such as Arabidopsis, with respect to their response

to O2 deficit. The aim of the present study was to gain a comprehensive insight into

plant adaptation mechanisms to root hypoxia, with a focus on carbon metabolism,

using the flooding tolerant species Grey poplar (Populus x canescens). Grey poplar is a

hybrid of P. alba and P. tremula that naturally occurs in regularly flooded areas of

alluvial forests along several European rivers (Fossati et al., 2004; Lexer et al., 2005;

van Loo et al., 2008). Its high flooding tolerance has also been demonstrated in a

series of physiological studies (Kreuzwieser et al. 1999, 2002). In the present work, a

global analysis of gene expression patterns was performed using the Affymetrix poplar

genome array representing 56,055 transcripts. This approach was complemented with

metabolomic analysis and physiological measurements in order to assess whether

observed gene expression changes were likely to be responsible for the plants

adaptation to anaerobic conditions.

Results and Discussion

Validation of the experimental set-up

Induction of root hypoxia caused an onset of ethanolic fermentation in roots of

poplar trees, as demonstrated by increases in transcript levels of pyruvate

decarboxylase, PDC (Prot ID 560932), and alcohol dehydrogenase, ADH (Prot ID

643524) (Fig. 1A). This finding was supported by the observed 3-fold increase in ADH

activities (Fig. 1A). Although the mean PDC transcript level was 15-times higher after 5

h of hypoxia, this transcriptional up-regulation was only associated with a 3-fold

increase in PDC activity in poplar roots. Possible explanations for this difference

include reduced translation efficiency (Branco-Price et al., 2008), decreased protein



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stability or some other form of post-transcriptional or post-translational regulation of

enzyme activity. The observed relatively high basal activities of PDC in normoxic

controls have also been discussed as a reason for such observations (Bouny and

Saglio, 1996; Tadege et al., 1998). In contrast to roots, leaves did not show altered

PDC and ADH expression. However, leaf ADH activity increased as a consequence of

hypoxic treatment of the roots. While this observation indicates that the expression of

an additional ADH isoform may be enhanced in leaves, the microarray data does not

provide evidence for this. Increased ADH activity in leaves of flooded trees may be

required to cope with the xylem-transported ethanol produced in the roots (Kreuzwieser

et al., 2001), as suggested from considerable emission of the volatile oxidation product

of ethanol, acetaldehyde. Acetaldehyde emission from leaves increased from 22±9

nmol m-2 min-1 (controls) to 423±158 nmol m-2 min-1 and 282±164 nmol m-2 min-1 after

24 and 168 h of hypoxia, respectively, consistent with previous studies (Kreuzwieser et

al., 1999; 2001). Obviously due to the transport of ethanol from roots to leaves, the

alcohol did not accumulate to any great degree in the roots with root ethanol

concentrations remaining below 4 µmol g-1 f.wt. (Figs. 2 and 3). In contrast, ethanol

concentrations in the xylem sap increased by a factor of 200 after 24 hours of flooding.

Transcript profiling

Based on these observations, microarray analysis was performed using root

samples taken after 0, 5, 24 and 168 h of flooding, and leaf samples taken 0 and 168 h

after treatment. To assess if the microarray data were comparable to the highly

sensitive qRT-PCR approach, the results for 12 genes analysed by both techniques

were examined (Supplemental Fig. S1). The high correlation (r2=0.83) of these results

validated the microarray analysis and confirmed that the normalisation method

employed provided reliable results.

Exposure to root hypoxia caused altered transcript levels of over 5,000 genes in

roots during the experiment (Fig. 1B; Supplemental Table S1). Interestingly, the

number of genes with more than 2-fold changed (q<0.05) transcript abundance

strongly differed between roots and leaves. No genes in the leaves showed different

expression levels after 1 week of root hypoxia indicating that the response of poplar to

O2 deficiency involves adaptations mainly in the stressed tissue itself. This finding is

surprising considering that root hypoxia led to reduced abundance of mRNA encoding

for some low molecular weight proteins in leaves of flooding tolerant Populus



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trichocarpa x P. deltoides (Neuman and Smit, 1993). The reason for this discrepancy

might be either the different species studied or the very stringent conditions applied in

the present study in which only genes showing a statistically significant difference of at

least 2-fold (q<0.05) were considered. It should be mentioned that unaffected transcript

abundance not necessarily means unchanged protein abundance as seen from work of

Branco-Price et al. (2008) with anoxia treated Arabidopsis. These authors clearly

demonstrated that translation efficiencies can selectively be altered independent on

transcription. Changed metabolite concentrations in poplar (Figs 2 and 3) may be a

result of this phenomenon or be caused by modified xylem or phloem transport. In root

tissue, the transcript abundance of 5,250 genes was significantly altered. After 5 h of

root hypoxia, only 195 genes showed altered expression, of which more than 85%

were up-regulated. The expression of 147 and 144 of these genes were still altered

after 24 h and 168 h of flooding, respectively. Prolonged duration of flooding caused

considerably more genes to show altered expression with 3,728 and 5,066 genes

differing in their expression compared to controls after 24 h and 168 h of root hypoxia,

respectively. In contrast to the early response to hypoxia, approximately two thirds of

these genes were found to be down-regulated. This is consistent with the gene

expression response in another flooding tolerant species, rice, where 1,364 and 1,770

probe sets showed increased and decreased expression respectively (Lasanthi-

Kudahettige et al., 2007).

Differentially expressed genes in roots were clustered into hierarchical

dendrograms resulting in the genes being classified into 15 clusters according to their

expression profiles (Fig. 4 and Supplemental Table S1). About 70% of all differentially

expressed genes were classified into the main clusters 4, 7, 13 and 14; the largest

cluster 14 alone contained 26% of all differentially expressed genes. Genes in clusters

4 and 7 were up-regulated in the roots during hypoxia. In contrast, members of clusters

13 and 14 exhibited down-regulated gene expression in roots in response to hypoxia;

genes in cluster 14 were less strongly reduced than genes in cluster 13. Comparable to

the Arabidopsis study by Liu et al. (2005), genes in the roots were either up- or down-

regulated during the whole course of the experiment and expression patterns changing

from up- to down-regulation or vice versa were scarce.

The genes with significant (q<0.05) and more than 2-fold changes in expression in

the roots were classified into functional groups using the MapMan Bin code (Thimm et

al., 2004) (Supplemental Table S1) and the software Pageman (Usadel et al., 2006)

(Supplemental Figs. S2 and S3). More than one third of these genes had unassigned



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functions. A relatively high percentage (~7%) seemed to play a direct role in

metabolism or be involved in transport processes, the latter genes were mostly

reduced in expression (Supplemental Fig. S2). The high proportion of genes involved in

regulation of transcription, signalling and hormone metabolism and the numerous

genes with changed expression encoding for protein kinases indicate the dynamic

adjustment of metabolic processes taking place in the stressed plants. Similar changes

have also been reported by other studies on the transcriptome of plants stressed by O2

deficiency (Klok et al., 2002; Liu et al., 2005; Loreti et al., 2005; Lasanthi-Kudahettige

et al., 2007; Branco-Price et al., 2008, van Dongen et al., 2008).

Effects on carbon metabolism

The switch from mitochondrial respiration to fermentation is likely to strongly affect

energy and C metabolism. Indeed, some important genes involved in glycolysis were

up-regulated in roots due to hypoxia (Fig. 5). The transcript abundance of key enzymes

of this pathway (Plaxton, 1996), phosphofructokinase (Prot. ID 695057) and pyruvate

kinase (Prot. ID 698714) were significantly increased due to hypoxia. As expected and

verified by quantitative RT-PCR data, transcript abundance of genes mediating

alcoholic fermentation increased significantly due to root hypoxia. In good agreement

with the expression profile of LDH in some herbaceous species (e.g. Arabidopsis, Klok

et al., 2002; maize, Christopher and Good, 1996), the LDH transcript in poplar (Prot. ID

704268) increased in abundance in the initial stages of root hypoxia (5 h treatment) but

thereafter dropped again. Consistent with this, the lactate concentration in flooded

roots was 6-times higher than in controls after short-term flooding but thereafter

decreased to control levels. This pattern was also seen in pyruvic acid concentrations

that initially increased by a factor of 3 (5 h flooding) but then dropped to control levels

(Fig. 2, Supplemental Table S2). Similarly increased pyruvate and lactate abundance

was recently observed in anoxia treated Arabidopsis (Branco-Price et al., 2008). These

observations support the pH-stat hypothesis (Roberts et al., 1984) and show that in

poplar, induction and inhibition of LDH can occur not only at the physiological but also

at the molecular level.

In this study the higher demand for carbohydrates required for glycolysis in

hypoxia treated plants was most probably compensated for by increased phloem

transport of sucrose from leaves to roots as suggested by the higher sucrose

concentrations in the phloem of hypoxically treated plants (2.14±0.44 µmol g-1 bark



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f.wt.) than in controls (1.43±0.32 µmol g-1 bark f.wt.) and simultaneously, significant

decreases in sucrose levels in leaves (Figs. 2 and 3). In the roots, altered transcript

levels clearly indicated a switch in sucrose degradation from cleavage by invertases

(Prot. ID 711782, 574265) to phosphorolytic degradation by sucrose synthases (SuSy,

Prot. ID 692288) (Fig. 5, Supplemental Table S4). Moreover, it may be that the

observed up to 10-fold decrease in pyrophosphatase transcript levels (Prot. ID 748006,

704742, 707491, 551881, 664206) caused decreased abundance and activity of this

enzyme, resulting in increased levels of pyrophosphate, the substrate for SuSy.

Progressive induction of pyrophosphate-dependent phosphofructose kinase (Prot ID

704902, 550714) provides a further link between enhanced glycolysis and

pyrophosphate during root hypoxia (Supplemental Table S1). The observed switch in

sucrose degradation which has also been observed in several other studies at the

physiological and molecular levels (Guglielminetti et al., 1995; Zeng et al. 1998; 1999;

Liu et al., 2005, Loreti et al., 2005; Branco-Price et al., 2008, van Dongen et al., 2008)

is energetically advantageous as only one pyrophosphate is used by SuSy, compared

to 2 ATP molecules needed by invertases. Starch biosynthesis and degradation was

also found to be affected by hypoxia (Fig. 5). Starch production seemed to be slowed

down as transcript levels of the starch branching enzyme (Prot. ID 589574) and starch

synthase (Prot. ID 569276) decreased. In contrast, starch degradation was most

probably altered because of an observed increase in β-amylase expression (Prot. ID

679498), and a decrease in α-amylase (Prot. ID 577743) and α-xylosidase (Prot. ID

564524) expression at the same time.

Consistent with these changes in transcript levels, some C metabolite

concentrations in leaves and roots were altered during hypoxia (Figs. 2 and 3). As

suggested from accelerated sucrose and starch catabolism, glucose, fructose and

fructose-6-phosphate concentrations increased in roots while starch concentration

showed a slight, but not significant, decrease after 1 week of hypoxia. Increased

carbohydrate levels in the roots of flooded plants have been previously observed in

trees and herbaceous species (Albrecht et al., 1993; Castonguay et al., 1993; Huang

and Johnson, 1995) and have been explained by a reduced C demand due to a decline

in root growth and N metabolism (Angelov et al., 1996). In contrast, the results of the

present study suggest that improved sugar supply to hypoxic roots occurs in order to

compensate for increased carbohydrate demand under these conditions. Interestingly,

reduced carbohydrate concentrations have been reported in roots of hypoxically

treated flood sensitive species (Vu and Yelenosky, 1991) highlighting the importance of

sugar delivery to roots in tolerating periods of O2 deficiency.



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An inhibition of respiration under conditions of reduced O2 supply has been

observed in herbaceous plants (Geigenberger, 2003). As this inhibition occurs at O2

concentrations higher than the KM of cytochrome oxidase (COX), it has been proposed

that under hypoxic conditions respiration is slowed down in order to reduce O2

consumption, thereby avoiding anoxia (Geigenberger 2003). However, in the present

study, transcript abundance of most respiratory chain components were found to be

unaffected by root hypoxia using qRT-PCR (Supplemental Fig. S4) and microarray

approaches (Supplemental Table S1), suggesting (1) that any inhibition of respiration

occurs at the protein or enzyme activity level or (2) - as also concluded from work on

Arabidopsis (Branco-Price et al., 2008) - that substrate availability for TCA cycle and

respiration is limited because of increased flux in the direction of fermentation.

The expression of most genes encoding enzymes of the TCA cycle was unaffected

or only slightly reduced by root hypoxia (Fig. 5) supporting observations of Loreti et al.

(2005) and Branco-Price et al. (2008) working with Arabidopsis. The gene showing the

most strongly reduced expression was a NADP dependent isocitrate dehydrogenase

(IDH, Prot. ID 55426) which dropped almost 15-fold after 1 week of hypoxia (Fig. 5).

This isoform showed high similarity to a cytosolic (At1g65930) and a mitochondrial

(At1g54340) IDH isoform of Arabidopsis. In contrast to IDH, the transcript abundances

of isocitrate lyase (ICL; Prot. ID 741351) and malate synthase (MS; Prot. ID 57656,

570219), increased indicating an enhanced glyoxylate cycle under hypoxia. Increases

in succinate concentrations in roots of hypoxia treated poplar which have also been

demonstrated in anoxia treated Arabidopsis (Branco-Price et al., 2008) are consistent

with this proposal (Fig. 2; Supplemental Table S2). The glyoxylate cycle exerts a

gluconeogenic function linking lipid degradation and carbohydrate production

(Eastmond et al., 2000) but may also play an anaplerotic role as seen in

microorganisms (Kornberg and Krebs, 1957). It is interesting that ICL and MS activities

are also enhanced in C starved plants (Kim and Smith, 1994), a situation that may exist

in plants experiencing O2 deficiency (Loreti et al., 2005). In this case an involvement of

the glyoxylate cycle in gluconeogenesis is more likely than an anaplerotic role (Smith,

2002). Through the glyoxylate cycle excess acetyl-CoA resulting from β-oxidation of

fatty acids would be channelled into carbohydrate biosynthesis. Stimulated degradation

of fatty acids is indeed suggested by the 5-fold up-regulation in expression of acyl-CoA

synthetase (Prot. ID 709380, 709180) (Supplemental Table S1), an enzyme involved in

this pathway in peroxisomes (Fulda et al., 2002). Consistent with this observation, the



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biosynthesis of fatty acids seemed to be repressed as the transcript levels of S-malonyl

transferase (Prot. ID 722565), Acetyl-CoA carboxylase (Prot. ID 684485, 559199,

673504), 3-ketoacyl-ACP synthase (Prot. ID 554288, 714498, 691067) and enoyl-ACP

reductase (Prot. ID 576267, 684702) dropped during hypoxia (Supplemental Table S1).

Inhibition of energy consuming processes

Numerous energy demanding processes were repressed in hypoxically treated

poplar (Supplemental Figs. S2 and S3). For example, the transcript abundance of

many transporters strongly decreased (Supplemental Table S1). Moreover, the

increased concentrations of the hemicellulose components arabinose and galactose

(Fig. 2; Supplemental Table S2) in flooded poplar roots indicated that changes in cell

wall formation and/or degradation occurred. Consistently, changes in transcript levels

suggested that the biosynthesis of cellulose, hemicellulose and cell wall proteins was

inhibited (Supplemental Fig. S2). Eight genes with homology to Arabidopsis cellulose

synthases were found in poplar. In the roots, the expression of cellulose synthases

required for secondary cell wall formation was dramatically (up to 44-fold; Prot. ID

555650) reduced. In contrast, the expression of only one cellulose synthase gene

(Prot. ID 714760) involved in primary cell wall biosynthesis declined and the extent of

decrease (up to 4.4-fold) was much less pronounced. These results may indicate the

importance of the primary cell wall for cellular integrity whereas formation of the

secondary cell wall seems to be of minor importance and may be initiated after survival

of the stress period. However, cellulose degradation was also affected as the

expression of most root specific cellulase isozymes was strongly reduced due to

hypoxia (e.g. Prot. ID 651956: 17-fold) (Supplemental Table S4).

Supplemental Table S5 summarizes the expression data of the relevant genes of

lignin biosynthesis together with other genes of the phenylpropanoid metabolism which

were present on the microarray. In the roots, all steps of this pathway, starting from the

conversion of chorismate into prephenate (catalysed by chorismate mutase), the

production of phenylalanine from arogenate (by arogenate dehydratase), its conversion

into cinnamate (by phenylalanine-ammonia-lyase, PAL) seemed to be down-regulated.

For example, the transcript levels of root specific PAL isozymes decreased by 7.6-fold

(Prot. ID 696959) and 11.5-fold (Prot. ID 82117). In addition, the expression of the root

specific chalcone synthase, a key enzyme of phenylpropanoid metabolism, was

reduced by 8-fold (Prot. ID 572875). Moreover, the subsequent modifications of



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cinnamate leading finally to the formation of lignin and flavonoids were repressed.

Effects on N metabolism

Nitrogen metabolism was studied in the present work by analysing amino acid

concentrations in leaves and roots after 168 h of hypoxia (Figs. 2 and 3), the

progression of metabolic changes in roots up to 168h of hypoxia (Supplemental Table

S2) and transcript levels of enzymes involved in N metabolism (Supplemental Table

S6). As expected, NO3- uptake was most probably impaired by root hypoxia as the

transcript levels of some NO3- transporters (Prot. ID 551887, 591881) decreased up to

17-fold. This is in good agreement with previous observations of reduced N uptake in

poplar (Kreuzwieser et al., 2002) and other species (Drew, 1991). The situation for

NH4+ uptake was different as two transporters were up-regulated. Considering slightly

reduced NH4+ uptake by flooded poplar (Kreuzwieser et al., 2002), up-regulated

transporters could be involved in root internal transport such as NH4+ loading into the

xylem. Consistent with the assumption of reduced N uptake into poplar roots, the gene

expression of enzymes involved in N assimilation seemed to be down-regulated. In

roots, NH4+ assimilation was transcriptionally affected as glutamine synthetase (GS)

isozymes were strongly down-regulated, a finding consistent with considerably reduced

concentrations of glutamine (Fig. 2; Supplemental Table S2). The subsequent NH4+

assimilation proceeds via glutamate synthase (GOGAT) (Lea et al., 1990). In plants an

NADH- and a ferredoxin (Fd)-dependent GOGAT isoform exist (Suzuki and Gadal,

1984). In accordance with results of anaerobically germinating rice (Mattana et al.,

1996), Fd-GOGAT expression (Prot. ID 695596) was increased whereas expression of

NADH-GOGAT (Prot. ID 569758) was reduced (Supplemental Table S4). Notably, the

opposite was the case in Arabidopsis (Liu et al., 2005). Fd-GOGAT seems to be

essential for re-assimilation of NH4+ arising from catabolism of N-containing

compounds such as proteins (Aurisano et al., 1995; Mattana et al., 1996) which is

supported by decreased protein levels in flooded poplar roots (Kreuzwieser et al.,

2002). Another interesting effect was the 6-fold increase in glutamate decarboxylase

transcripts after 5 h of hypoxia (Supplemental Table S6) which was observed together

with reduced levels of glutamate but increased levels of GABA, succinate and alanine

(Fig. 2; Supplemental Table S2) indicating onset of the GABA shunt (Streeter and

Thomson, 1972) (Fig. 2).

Metabolite profiling revealed that flooding induced rapid changes in the levels of



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a wide variety of amino acids in the roots. As seen also in Arabidopsis (Branco-Price et

al., 2008), most of the more strongly accumulating amino acids were closely derived

from either pyruvate (e.g. alanine, valine, leucine) or intermediates of glycolysis

(glycine, serine, tyrosine) while all the decreasing amino acids (glutamate, glutamine,

aspartate, asparagine) were derived from TCA cycle intermediates. This observation

strongly supports the hypothesis that the block in aerobic respiration caused by

hypoxia led to a decrease in flux into the TCA cycle (due to an accumulation of NADH

and depletion of NAD+ in the mitochondrial matrix) resulting in a redirection of glycolytic

carbon into glycolytic intermediate-derived amino acids and a decrease of flux out of

the mitochondria into TCA cycle intermediate-derived amino acids.

Interestingly, changes in amino acids were frequently associated with dynamic

changes in the levels of transcripts encoding enzymes involved in their metabolism. In

most cases, transcriptional responses appeared to act as a mechanism of

counteracting flooding-induced changes in amino acid levels. For example, rapid

increases in glycine, tyrosine, and serine were followed by transcriptional up-regulation

of enzymes involved in their biosynthesis and down-regulation of enzymes involved in

their degradation (Supplemental Tables S2 and S6). Conversely, a significant decrease

in glutamate at 24 h was accompanied by transcriptional up-regulation of enzymes

involved in its biosynthesis and down-regulation of enzymes involved in its degradation.

Interestingly, in the case of lysine, which was significantly increased after 24 h of

flooding, this pattern of negative feedback was replaced with an apparent positive

feedback mechanism with the transcript encoding dihydrodipicolinate synthase 2 (Prot.

ID 730895), the enzyme responsible for the first committed step in lysine biosynthesis,

being significantly up-regulated >4-fold after 5 hours of flooding, before lysine levels

had significantly increased. Moreover, the accumulation of lysine was followed by a

down-regulation of two enzymes involved in its degradation. Some metabolite-

transcript interactions appeared to be more complex. For example, a 7-fold up-

regulation of the transcript encoding a reversible mitochondrial aspartate

aminotransferase (Prot. ID 362675) at the 5 h time-point was followed by a 6-fold

decrease in aspartate at the 24 h time-point. Interestingly, by the time the decrease in

aspartate was at its most severe (24 h), transcript levels for the mitochondrial aspartate

aminotransferase had already decreased to the point that they were no longer

statistically significant. At this time the transcript encoding another aspartate

aminotransferase (Prot. ID 71675) had become significantly down-regulated and

transcripts encoding two enzymes of aspartate biosynthesis - namely aspartate-



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semialdehyde dehydrogenase (Prot. ID 564677) and aspartate kinase/homoserine

dehydrogenase (Prot. ID 92760) - had already become significantly up-regulated by

~4-fold. Consistent with the notion that these transcriptional responses act to maintain

homeostatic levels of aspartate by reducing its catabolism and enhancing its

biosynthesis, aspartate levels were no longer significantly decreased by the 168 h time-

point. Although it is not clear exactly how these transcriptional responses were

mediated, the observations above are consistent with the notion that transcriptional

responses of genes involved in amino acid metabolism were largely driven by changes

in amino-acid levels.

Surprisingly, the most dramatic increase in abundance of a metabolite (57-fold)

was observed for uric acid in hypoxically treated poplar roots (Fig. 2; Supplemental

Table S2). This N containing compound is a well known transport form of symbiotically

fixed N2 in the xylem sap of legumes (Reinbothe and Mothes, 1962) but is also a

product of purine degradation (Woo et al., 1980). The latter is most likely the source of

uric acid in the present study as stresses other than hypoxia that affect the nutrient

balance of plants such as sulphur deficiency (Nikiforova et al., 2006) also cause a

higher abundance of this N-rich compound. The elevation of AMP (Fig. 2;

Supplemental Table S2) may suggest the availability of purines for degradation in

hypoxic roots. It has to be tested in further studies if N is relocated from roots to the

shoot (as uric acid or other N containing compounds) as suggested by decreasing

protein concentrations in roots but increasing concentrations in the leaves of flooded

poplar (Kreuzwieser et al., 2002).

Growth and physiology of the trees

Repressed nutrient uptake/transport and the inhibition of biosynthetic processes

are in accordance with the assumption that plants restrict O2 consumption in order to

avoid the occurrence of complete anoxia (Geigenberger, 2003). Although (i) the roots

of the hypoxia treated trees switched from mitochondrial respiration to alcoholic

fermentation with an assumed impaired energy metabolism (Fig. 1) and (ii)

biosyntheses were inhibited (Supplemental Tables S4 and S5), the shoot growth of

poplar trees did not show any significant limitation, at least during two weeks of hypoxic

treatment (Fig. 6A). Given the metabolic analysis performed in the present study, which

indicates that the availability of both sugars and amino acids was not considerably

reduced (Fig. 2, Supplemental Table S2), a reduction in both root and shoot growth



16

would not necessarily be expected. Moreover, CO2 assimilation rates which drop in

anoxia sensitive species as a response to this stress (Pezeshki et al., 1996; Nunez-

Elisea et al., 1999) were nearly unchanged in poplar (Fig. 6B) and a steady supply of

carbohydrates was therefore ensured. In addition, the leaves of poplar were supplied

with reduced C in the form of ethanol via the transpiration stream as suggested from

high ethanol concentrations in the xylem sap and ongoing transpiration even after 1

week of root hypoxia (Fig. 6B). However, as growth of below-ground plant parts was

not determined, it cannot be excluded that root growth was limited by reduced energy

supply.

Possible flooding adaptations

One aim of the present work was to identify mechanisms mediating flooding

tolerance by comparing the highly flooding tolerant poplar with flooding sensitive

Arabidopsis. As expected, the present study revealed numerous pathways connected

to C and N metabolism which are altered by hypoxia. These pathways were affected in

a similar way in Arabidopsis although experimental conditions differed from the present

poplar study (Klok et al., 2003: root cultures exposed to 5% O2 for up to 20 h; Liu et al.,

2005: whole seedlings exposed to 3% O2 for up to 24 h and use of whole plants for

array analysis; Loreti et al., 2005: whole seedlings anoxically exposed for up to 72 h

and use of whole plants for array analysis; Branco-Price et al., 2008: whole seedlings

exposed to argon environment free of O2 and CO2 for up to 9 hours, use of whole

seedlings; van Dongen et al., 2008: whole seedlings exposed to varying O2

concentrations for up to 48 hours, whole seedlings used for microarrays). Adaptations

seen in all experiments included increased glycolytic flux, modified sucrose

degradation and a reduction in energy consuming processes such as transport

processes and biosyntheses.

However, analysis of the hypoxic response in poplar provided insights not apparent

in studies performed using Arabidopsis which cannot be explained by the different

experimental conditions alone. A large difference between Arabidopsis and poplar (and

also rice, Lasanthi-Kudahettige et al., 2007) is the number of genes differentially

expressed during hypoxia. In stress exposed poplar tissue, over 5,000 genes showed

significantly altered expression whereas under similar conditions the transcript

abundance of only c. 150 genes was changed in Arabidopsis (Klok et al., 2002; Liu et

al., 2005). Differences in gene expression in Arabidopsis studies can partially be



17

explained by the different O2 concentrations applied (van Dongen et al., 2008). At lower

O2 abundance, more genes were differentially expressed. This explains that in the

study by Branco-Price et al. (2008) c. 1500 genes were differentially expressed in

Arabidopsis. However this was still less than a third of the changes observed in

hypoxia treated poplar. A high percentage of altered genes in both species were

transcription factors (TFs) (456 genes in poplar), protein kinases (>200 genes), or were

involved in signalling (115 genes) and hormone metabolism (137 genes). In poplar,

over 2,500 TFs have been identified and classified into 64 families (Zhu et al., 2007) of

which 456 showed altered transcript abundances in the present study (Supplemental

Table S1). Although Arabidopsis possesses nearly the same number of TFs (estimated

1,922), only c. 50 of them were differentially expressed in response to hypoxia (Liu et

al., 2005). Transcription factors with modified expression levels spanned all major TF

families such as AP2-domain (17 genes), basic helix-loop-helix (28 genes), zinc finger

(43 genes), myb (50 genes), Leu-zipper (21 genes) and WRKY (20 genes) family

proteins. However, in contrast to Arabidopsis, members of the NAC domain- (26

genes) and bZIP- (15 genes) families also showed changes in expression in poplar.

Among the most dramatically up-regulated TFs were members of the myb-, AP2/EREB

and Leu-zipper families. Similarly, strongest down-regulation was observed in TFs

belonging to the myb-, Leu-zipper and WRKY family (Supplemental Table S1). Some

members of these families have been suggested to be involved in transcriptional

regulation of wood formation (Demura and Fukuda, 2007) suggesting that the observed

down-regulation of genes involved in this pathway is a result of a complex regulatory

network involving regulation of TFs at the level of transcription. The observed changes

in transcript abundance of genes involved in cytokinin signalling may also indicate

down-regulated wood formation (Demura and Fukuda, 2007). The observed differential

expression of numerous TFs and components of plant hormone signalling in poplar

suggests a very complex transcriptional regulatory network leading to stress adaptation

of poplar in response to hypoxia.

Another difference between Arabidopsis and poplar was the different temporal

pattern of transcriptome changes. In the Arabidopsis study by (Liu et al., 2005),

changes in transcript abundance peaked in number and magnitude 6 hours after

hypoxic treatment, in the study by van Dongen et al. (2008) a steady state was reached

around 2 hours after starting the stress whereas in poplar differential gene expression

increased steadily until 7 days of treatment. Such a pattern was evident for a broad

range of genes ranging from TFs and other regulatory elements to genes of major



18

metabolic pathways. ADH transcript abundance in Arabidopsis for example peaked 2 to

4 hours after hypoxia (Liu et al., 2005) whereas in poplar it was consistently up-

regulated during the whole flooding period. Similar patterns were observed for genes

involved in glycolysis. It is suggested that many of the changes in gene expression

observed in flooded poplar are related to an improvement of carbohydrate status and to

the maintenance of high carbohydrate concentrations to allow for the formation of

energy equivalents. Furthermore changes in transcript abundance in poplar occurred in

an organ specific manner, revealing that the majority of changes at a transcript level

were restricted to the site of hypoxia, and thus no general systemic signal appears to

be generated to trigger gene expression changes throughout the plant. However,

analysis of various metabolites in both leaves and roots (Figs. 2 and 3) reveal that the

aerial parts of the plant facilitate specific alterations in primary metabolism that

provides hypoxic root with sources of energy, resulting in flooding tolerance.

Interestingly, the expression of two AOX isoforms (Prot. ID 727508, 365930) was

considerably increased in poplar roots during hypoxia. In contrast, in Arabidopsis

exposed to hypoxia, AOX expression is reduced (Liu et al., 2005) or only transiently

enhanced (Klok et al., 2002). AOX induction in poplar may simply be due to a

restriction of electron transport via the cytochrome electron transport chain

(Vanlerberghe and Mclntosh, 1994; Wagner and Moore, 1997). As the KM of AOX for

O2 is even higher than that of COX (Millar et al., 1994; Ribas-Carlo et al., 1994), it is

unlikely that it plays any role during hypoxia, but may act as a pre-oxidant defence

mechanism on return to aerobic conditions (Purvis and Shewfelt, 1993, Purvis et al.,

1995; Millar et al., 2001; Sweetlove and Foyer, 2004). Although ROS have often been

implicated in the induction of AOX, signal transduction pathways inducing AOX

independent of ROS have been described in other plants (Amirsadeghi et al., 2007;

Clifton et al., 2006) and it is possible that ROS are produced under hypoxia (Rhoads et

al., 2006).

In poplar the GABA shunt was stimulated which was in contrast to Arabidopsis

where it was either observed to be only transiently up-regulated (Klok et al., 2002; Liu

et al., 2005) or not up-regulated at all (Loreti et al., 2005). The GABA shunt is

considered a metabolic adaptation to O2 limitation as it is a proton consuming process

stabilizing cytoplasmic pH (Crawford et al., 1994). It further represents an anaplerotic

sequence for the TCA cycle, by-passing the IDH reaction. As GABA stimulates

ethylene production in sunflower, it might play a role in signalling (Kathiresan et al.,

1997). Thus, changes in GABA concentrations in roots of hypoxically treated poplar



19

may be a first step in inducing morphological adaptations such as the formation of

hypertrophied lenticels and aerenchyma. In poplar, such adaptations usually occur 2 to

3 weeks after flooding treatment and were therefore not observed in the present study.

Conclusion

Comparison of the response of the relatively flood-sensitive plant, Arabidopsis, with

that of the highly flood-tolerant tree, poplar, revealed important differences. The

metabolite and transcript patterns reveal the poplars’ capability to maintain C and

energy metabolism during periods of O2 deficiency may be an important adaptation that

allows tolerance to anoxia (Drew et al., 1997). In poplar, this is mediated by stimulation

of glycolysis and a steady supply of sugars for this pathway on the one hand, and the

repression of energy-demanding processes on the other hand. From the large changes

in transcript abundance observed, we conclude that not one single pathway, but the

sum of numerous well orchestrated processes in carbon and nitrogen metabolism and

morphological adaptation is responsible for the high flood-tolerance of poplar.



20

Experimental procedures

Plant material

Experiments were performed with 3-month-old hybrid poplar plants (Populus x

canescens). The plants were micro-propagated and cultivated as described by Leplé et

al. (1992). Four week old stem explants were transferred from sterile agar cultures into

plastic pots (12 x 10 x10 cm) containing a mixture of perlite, sand and potting soil (2 / 1

/ 1). Each tree was supplied with 200 mL of a solution containing 3 g l-1 of a complete

fertiliser (Hakaphos blau; Bayer, Leverkusen, Germany) every two weeks and was

watered daily with tap water. Trees were grown under long day conditions (16 h light)

at day and night temperatures of 22±4°C and relative humidity of 72±10 %.

Experimental set-up

At the beginning of the experiment, the shoots of the trees had a size of 20 to 25 cm.

To induce root hypoxia 52 trees were transferred into large plastic containers. The

containers were filled with tap water until the water level exceeded the soil surface by

2-3 cm. Oxygen concentration in the soil of flooded trees were analysed

representatively in 4 individuals using O2 micro-sensors (micro-optodes; Microx TX2,

PreSens GmbH, Regensburg, Germany). Under normoxic conditions O2 concentrations

amounted to about 7.5 ppm (equal to c. 80% air saturation), whereas under flooding

conditions, values decreased to 0.1 ppm (1.3 % air saturation) within 2 hours; they

further dropped to 0.05 ppm (0.6 % air saturation) within another hour and then

remained constant at this level for the rest of the flooding period. Besides flooded trees,

52 trees were used as non flooded, normoxic, controls. After 1h, 3h, 5h, 7h, 24h and

168 h of treatment, 4 trees of each treatment (flooded and controls) were harvested;

tissues were immediately frozen in liquid nitrogen and stored at -80°C until further

analysis. Enzyme activities were determined immediately using fresh material.

RNA isolation and cDNA synthesis

For total RNA extraction the Plant RNeasy kit (Qiagen, Hilden, Germany) was used

according to the manufacturer’s instructions with some minor modifications. Aliquots of



21

90 mg of frozen plant powder were added to 900 µl RLT buffer supplemented with 1%

ß-mercaptoethanol, 1% PVPP and 2% (w/v) polyethylenglycol (PEG 10,000), and then

incubated for 10 min at 58°C. The samples were further processed according to the

manufacturer’s protocol. For microarray and qRT-PCR analysis, total RNA was treated

with DNase during (RNase free DNase kit, Qiagen, Hilden, Germany) and after (DNA-

free TM kit, Ambion) the extraction procedure. For cDNA synthesis 1 µg of total RNA

was reverse transcribed using oligo (dT) primers and Superscript II reverse

transcriptase™ (Invitrogen) in a total volume of 20 µl.

Quantitative RT-PCR

For measurements of transcript levels of the genes of interest, specific oligonucleotide

primer sets were designed and tested for cross-hybridisation and efficiency

(Supplemental Table S7). Quantitative PCR was performed using the iQ5 instrument

with iQ™ SYBR® Green Supermix (Bio-Rad, Regents Park, Australia), using 25 µl

reaction volumes with 0.5 to 0.9 µM of each primer (Supplemental Table S5) and 2.5 µl

of template, under conditions optimized to minimize primer-dimer formation and

maximize amplification efficiency (“hot start”: 30 s, 95°C; 40 cycles: 15 s at 95°C; 30 s

at 55°C). Melting curve analysis was performed after PCR amplification to ensure

products were specific. For internal normalisation, transcript levels of poplar β-tubulin

(PcTUB; EMBL AY353093) were determined.

Microarray analysis

Microarray analysis of changes in transcript abundance in poplar leaves and roots was

performed using a set of 30 Affymetrix GeneChip® Poplar Genome Arrays (Affymetrix,

Santa Clara, CA). Twenty-one and nine arrays were used to analyse root and leaf

samples, respectively. The root samples from flooded trees taken 5h, 24h and 168h

after starting the flooding treatment (9 arrays) and the root control samples collected

before and 5h, 24h and 168h after starting the flooding treatment (12 arrays) were

analysed by the microarray technique. For leaves, the controls collected before

flooding and 168h after starting the treatment (6 arrays) and the leaves of the flooded

poplar at this time (3 arrays) were used for analysis. The quality of the isolated total

RNA was tested using an Agilent Bioanalyzer (Agilent Technologies, Palo Alto, CA)

and spectrophotometric analysis (NanoDrop® ND-1000, NanoDrop Technologies,



22

Wilmington, DE) to determine the A260 to A280 ratio. Preparation of labelled cRNA from

3.5 µg of root total RNA and 5 µg of leaf total RNA, target hybridization as well as

washing, staining, and scanning were performed exactly as described in the Affymetrix

GeneChip Expression Analysis Technical Manual, using an Affymetrix GeneChip

Hybridization Oven 640, an Affymetrix Fluidics Station 450 and a GeneChip Scanner

3500 7G at the appropriate steps. Data quality was assessed using GCOS1,4

(Affymetrix) by checking raw array images for artefacts, background levels and

percentages of absent and present calls for all arrays within an experiment as well as

3’/5’ ratios of control genes. Normalisation was performed using the raw data (CEL

files) by applying the RMA (Robust Multi-Array Average) algorithm using RMAExpress

(Version 0.4.1 Release, Bolstad et al., 2003). Transcripts called as “absent” and genes

with an average raw signal value below 50 in the untreated sample were filtered out.

Correct normalisation was checked and differentially expressed genes were

determined by applying a two-tailed Student's t-tests (p<0.05). In this procedure, each

hypoxically treated set of root samples was tested against all 4 control sets (each

collected in triplicate before and 5h, 24h and 168h after starting the flooding treatment).

The same was applied for leaf samples where leaves from flooded trees were tested

against the controls taken before treatment and after 168h of flooding treatment. FDR

analysis was then performed using the QVALUE software (Storey and Tibshirani,

2003). For estimating q-values, π0 (an estimate of the total proportion of true null

hypotheses) was determined based on the distribution of 61,413 p-values using the

smoothing method. A stringent approach was used to select genes differentially

expressed in poplar roots and leaves. Only genes were considered to be differentially

expressed when (i) the transcript abundance in hypoxia treated plants was significantly

different against all 4 controls as determined by Student's t test, (ii) the calculated q-

value against the direct control was < 0.05, and (iii) the change in expression was at

least 2-fold compared to the control. TIGR Multiexperiment viewer v4.0.1 was used to

produce hierarchical dendrograms of differentially expressed genes revealing natural

groupings in microarray data. Dendrograms displaying the ‘natural’ groupings within the

data are displayed with different colour intensities based on sorted fold-change data,

and distances (4.00) between tree branches determined using a Euclidean function

(Eisen et al., 1998; Saeed et al., 2003). The Software Pageman (Usadel et al., 2006)

was used for the generation of overview graphs displaying differentially expressed

genes in functional classes using Wilcoxon statistical testing. Data from this study are

available from GEO (http://www.ncbi.nlm.nih.gov/geo) and are listed under the



23

following accession numbers: GPL4359 (for the array platform) and GSE13109 (for the

experimental series) where a link to the expression data is given.

Metabolite determination

Concentrations of soluble carbohydrates were determined by HPLC-PAD (Heizmann et

al., 2001). Ethanol concentrations were determined enzymatically as described

previously (Kreuzwieser et al., 2001). Starch was analyzed colorimetrically using a

commercial test kit (Boehringer, Ingelheim, Germany). For extraction, 50 mg of

powdered (under liquid N2) plant material was added to 1 ml of DMSO/25 % (w/v) HCl

(80:20, v/v). After 30 min of incubation at 60°C, samples were centrifuged (5 min;

12,000 x g) and 200 µl of the supernatant was added to 1.2 ml of ice-cold 0.2 M citrate

buffer (pH 10.6). The resulting solution was then used for analyses. Amino acid

concentrations were determined using the HPLC method described by Kreuzwieser et

al. (2002).

In parallel to these techniques, concentrations of polar low molecular weight

metabolites present in poplar roots were analysed by GC-MS. Metabolites were

extracted and derivatised using a method modified from that of Roessner-Tunali et al.

(2003). Derivatised samples were analyzed on an Agilent GC/MSD system (Agilent

Technologies, Palo Alto, CA, USA). Raw GC-MS data files in the proprietary

ChemStation (.D) format were exported to generic NetCDF / AIA (.CDF) format with

ChemStation GC/MSD Data Analysis Software. The NetCDF files produced were then

processed using in-house MetabolomeExpress (Ver 0.9) software to carry out all peak

detection, quantification, library matching, normalization, statistical analysis and data

visualization. Detailed methodology are presented in Supplemental Information 1.

Enzyme activities

ADH and PDC activities were determined according to the protocol of Owen et al.

(2004). Aliquots of 100 mg fresh leaf or root material were homogenised in 1.5 ml ice-

cold extraction buffer (0.1 M MES buffer, pH 6.5, 15% (v/v) glycerol, 0.2% (v/v) Tween

20, 2 mM DTT, 1 mM PMSF, 10% PVPP). For determination of PDC activity, 30 µl

protein extract were added to 250 µl assay buffer (0.1 M MES-buffer, pH 6.5, 80 µM

NADH, 10 µM TPP, 5 mM MgCl2, 14 u ml-1 ADH, 5 mM pyruvate) and NADH



24

consumption was analysed.

Gas exchange

Net CO2 assimilation, transpiration, stomatal conductance and acetaldehyde exchange

between leaves and the atmosphere were determined using the portable gas exchange

measuring system GFS-3000 (Walz, Effeltrich, Germany) similarly as described in

Kreuzwieser et al. (1999). Standard conditions (1,000 µmol PPFD m-2 s-1; 25°C leaf

temperature) were applied. From each plant, 8 fully mature leaves were analysed.

Statistical analysis

Data obtained were subjected either to Student’s t-test (Microsoft-Excel 2002) or to

analyses of variance and multiple range tests (Tukey) by ANOVA (SPSS® 14.0 for

Windows®, SPSS Inc., Chicago, USA).



25

Supplemental material

Supplemental Figure S1. Real-time PCR validation of array data.

Supplemental Figure S2. Overview of pathways with significantly changed transcript

abundance in hypoxia treated poplar roots.

Supplemental Figure S3. Detailed view on pathways involved in cell wall biosynthesis.

Graphical representation was extracted from Figure S2.

Supplemental Figure S4. Transcript levels of genes involved in the TCA cycle and

mitochondrial respiration.

Supplemental Table S1. Genes differentially expressed in roots and leaves of

hypoxically treated poplar.

Supplemental Table S2. Changes in metabolite concentrations.

Supplemental Table S3. Differentially expressed genes involved in primary energy

metabolism in poplar roots

Supplemental Table S4. Genes involved in cellulose biosynthesis or degradation

Supplemental Table S5. Genes involved in phenylpropanoid metabolism.

Supplemental Table S6. Differentially expressed genes involved in N metabolism.

Supplemental Table S7. Oligonucleotide primer sets used for quantitative RT-PCR.

Supplemental Information 1. Materials and Methods for GC-MS analysis

Supplemental Information 2. The MIAME checklist



26

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33

Figure Legends

Figure 1. Effects of hypoxia on expression and activity of fermentative enzymes

(A) and general transcript abundance (B) in poplar roots and leaves. (A)

Transcript levels and activities of PDC (left panel) and ADH (right panel) in leaves

(upper row) and roots (lower row) of Grey poplar. Transcript levels of normoxic controls

(-■-) and flooded plants (-□-) are normalised to β-tubulin mRNA levels. Means (±s.e.) of

the enzyme activities (bars) of 4-6 independent experiments are shown. Statistically

significant differences at p<0.05 were calculated by Student’s t-test and are indicated

by asterisks. (B) Number of differentially expressed genes (>2-fold changes, q<0.05)

following root hypoxia as determined by microarray analysis. Data represent averages

of three biological replicates for each timepoint/tissue. Applying the criteria given in

methods in leaves no differentially expressed genes were observed.

Figure 2. Effect of hypoxia on metabolite abundance in leaves and roots of

poplar. Normoxic controls and hypoxically treated trees were harvested and metabolite

concentrations were determined by GC-MS (roots) at times 5 h, 24 h and 168 h and by

HPLC (leaves) at time 168 h. Ethanol concentrations were determined enzymatically.

Metabolites given in red showed significantly lower concentrations in treated trees than

in controls. Blue and green colours indicate higher and unchanged concentrations,

respectively. Diagrams behind metabolite names indicate fold-changes (log2 converted)

of results obtained by GC-MS.

Figure 3. Carbohydrate (A) and ethanol (B) and amino acid (C) concentrations in

leaves and roots of poplar affected by root hypoxia. Normoxic and hypoxic grown

trees were harvested and metabolite concentrations were determined. Results shown

are means (±s.e.) of at least 4 trees per time point and treatment. Statistically

significant differences between treatments per carbohydrate species at p<0.05 were

calculated with Tukey-test under ANOVA (A) or Student's t-test (B, C) and are indicated

by different letters/asterisks over bars. Asp, aspartate, 3-m-his, 3-methyl histidine, ala,

alanine, arg, arginine, asn, asparagines, asp, aspartate, cit, citrulline, cys, cysteine,

gaba, γ-amino butyric acid, glu, glutamate, gln, glutamine, gly, glycine, his, histidine,

ile, isoleucine, leu, leucine, lys, lysine, met, methionine, orn, ornithine, phe,

phenylalanine, pro, proline, ser, serine, thr, threonine, trp, tryptophan, tyr, tyrosine, val,



34

valine.

Figure 4. Hierarchical clustering of changes in transcript abundances following

flooding. Following microarray analysis, fold-changes were determined from three

biological replicates for each timepoint/tissue type. (A) Hierarchical clustering was

performed using the TMeV software package from log2 signal ratio data. To distinguish

between clusters, violet triangles are drawn to the left of clusters and cluster numbers

are given. (B) Colour scale indicating signal log2 ratios. The criteria given in materials

were applied and only genes with >2-fold changed expression (q<0.05) are displayed.

Figure 5. Expression changes of genes involved in primary C metabolism. After 5

h (left squares), 24 h (middle squares) and 168 h (right squares) of hypoxia, roots were

harvested and transcript levels determined by microarray analysis. The log2 values of

fold-changes of genes involved in C metabolism are displayed using the colour code

indicated. ProteinIDs are indicated. The figure was generated using MapMan (Thimm

et al., 2004). Green arrows, gluconeogenesis; orange arrows, glyoxylate cycle. Details

on gene expression are given in Supplemental Table S2.

Figure 6. Effect of root hypoxia on shoot growth (A) and gas exchange (B) of

Grey poplar. (A) Two weeks prior to and after starting the hypoxic treatment, shoot

lengths were determined. Means (±s.e.) of 5 to 10 trees per treatment are given. (B)

Fully mature leaves were chosen and rates of net CO2 assimilation (A), transpiration

(E) and stomatal conductance for water vapour (g(H2O)) were determined. Means

(+s.e.) of 8 leaves per plant and 4 plants per treatment are given. Statistically

significant differences between treatments and controls at p<0.05 are indicated by

asterisks over bars. White symbols and bars: normoxic controls; grey symbols and

bars: hypoxic treated plants.



0 10 20 30 1600 10 20 30 1600

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Jürgen

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Figure 1

Jürgen

Textfeld

Figure 1. Effects of hypoxia on expression and activity of fermentative enzymes (A) and general transcript abundance (B) in poplar roots and leaves. (A) Transcript levels and activities of PDC (left panel) and ADH (right panel) in leaves (upper row) and roots (lower row) of Grey poplar. Transcript levels of normoxic controls (-■-) and flooded plants (-□-) are normalised to β-tubulin mRNA levels. Means (±s.e.) of enzyme activities (bars) of 4-6 independent experiments are shown. Statistically significant differences at p<0.05 were calculated by Student's t-test and are indicated by asterisks. (B) Number of differentially expressed genes (>2-fold changes, q<0.05) following root hypoxia as determined by microarray analysis. Data represent averages of three biological replicatesfor each time point/tissue. Applying the criteria given in methods in leaves no differentially expressed genes were observed.

kreuzwie


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Figure 2

Jürgen

Textfeld

Figure 2. Effect of hypoxia on metabolite abundance in leaves and roots of poplar. Normoxic controls and hypoxically treated trees were harvested and metabolite concentrations were determined by GC-MS (roots) at times 5 h, 24 h and 168 h or by HPLC (leaves) at time 168 h. Ethanol concentrations were determined enzymatically. Metabolites given in red showed significantly lower concentrations in treated trees than in controls. Blue and green colours indicate higher and unchanged concentrations, respectively. Diagrams behind metabolites indicate fold-changes (log2 converted) of results obtained by GC-MS.


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Figure 3. Carbohydrate (A), ethanol (B) and amino acid (C) concentrations in leaves and roots of poplar affected by root hypoxia. Normoxic and hypoxic grown trees were harvested and metabolite concentrations were determined. Results shown are means (±s.e.) of at least 4 trees per time point and treatment. Statistically significant differences between treatments at p<0.05 were calculated with Tukey-test under ANOVA (A) or Student's t-test (B, C) and are indicated by different letters/asterisks over bars. Asp, aspartate, 3-m-his, 3-methyl histidine, ala, alanine, arg, arginine, asn, asparagine, cit, citrulline, cys, cysteine, gaba, gamma-amino butyric acid, glu, glutamate, gln, glutamine, gly, glycine, his, histidine, ile, isoleucine, leu, leucine, lys, lysine, met, methionine, orn, ornithine, phe, phenylalanine, pro, proline, ser, serine, thr, threonine, trp, tryptophan, tyr, tyrosine, val, valine.

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Figure 3

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Figure 4

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Figure 4. Hierarchical clustering of changes in transcript abundances. Following micro-array analysis, fold-changes were determined. (A) Hierarchical clustering was performed using the TMeV software package from log2 signal ratio data. To distinguish between clusters, violet triangles are drawn to the left of clusters and cluster numbers are given. (B) Colour scale indicating signal log2 ratios. The criteria given in materials were applied and only genes with <2-fold changed expression (q<0.05) are displayed.

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Figure 5

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Figure 5. Expression changes of genes involved in primary C metabolism. After 5 h (left squares), 24 h (middle squares) and 168 h (right squares) of hypoxia, roots were harvested and transcript levels determined by microarray analysis. The log2 values of fold-changes of genes involved in C metabolism are displayed using the colour code indicated. Protein IDs are indicated. The figure was generated using MapMap (Thimm et al., 2004). Green arrows, gluconeogenesis; orange arrows, glyoxylate cycle.


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Figure 6

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Figure 6. Effect of root hypoxia on shoot growth (A) and gas exchange (B) of Grey poplar. (A) Two weeks prior to and after starting the hypoxic treatment, shoot lengths were determined. Means (±s.e.) of 5 to 10 trees per treatment are given. (B) Rates of net CO2 assimilation (A), transpiration (E) and stomatal conductance for water vapour (g(H2O)) were determined. Means (+s.e.) of 8 leaves per plant and 4 plants per treatment are given. Statistically significant differences between treatments and controls at p<0.05 are indicated by asterisks over bars. White symbols and bars: normoxic controls; grey: hypoxic treated plants.


Differential response of poplar (P. x canescens) leaves and roots ...

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