Heavy Metals Induce Iron Deficiency Responses at Different Hierarchic and Regulatory Levels

Abstract

In plants, the excess of several heavy metals mimics Fe deficiency-induced chlorosis indicating a disturbance in Fe homeostasis. To examine at which level heavy metals interfere with Fe-deficiency responses, we carried out an in-depth characterization of Fe-related physiological, regulatory and morphological responses in Arabidopsis thaliana exposed to heavy metals. Enhanced Zn uptake closely mimicked Fe deficiency by leading to low chlorophyll but high ferric-chelate reductase activity and coumarin release. These responses were not caused by Zn-inhibited Fe uptake via IRT1. Instead, Zn simulated the transcriptional response of typical Fe-regulated genes, indicating that Zn affects Fe homeostasis at the level of Fe sensing. Excess supplies of Co and Ni altered root traits in a different way as Fe deficiency, induced only transient Fe-deficiency responses, which were characterized by a lacking induction of the ethylene pathway. Cadmium showed a rather inconsistent influence on Fe deficiency responses at multiple levels. By contrast, Mn evoked weak Fe deficiency responses in wild-type plants but strongly exacerbated chlorosis in irt1 plants, indicating that Mn antagonized Fe mainly at the level of transport. The present results show that the investigated heavy metals modulate Fe-deficiency responses at different hierarchic and regulatory levels and that the interaction of metals with physiological and morphological Fe deficiency responses is uncoupled. Thus, this study emphasizes not only the importance of assessing heavy metal toxicities at multiple levels but provides also a new perspective on how Fe deficiency contributes to the toxic action of individual heavy metals.

Full text

Heavy Metals Induce Iron Deficiency Responses at
Different Hierarchic and Regulatory Levels1[OPEN]
Alexandra Lešková,a,b,c RicardoF.H.Giehl,
aAnja Hartmann,aAgáta Fargašová,band Nicolaus von Wiréna,2
a
Department of Physiology and Cell Biology, Leibniz Institute for Plant Genetics and Crop Plant Research,
06466 Gatersleben, Germany
b
Department of Environmental Ecology, Faculty of Natural Sciences, Comenius University in Bratislava,
84215 Bratislava, Slovakia
c
Department of Plant Physiology, Plant Science and Biodiversity Center, Slovak Academy of Sciences,
84523 Bratislava, Slovakia
ORCID IDs: 0000-0003-4587-2550 (A.L.); 0000-0003-1006-3163 (R.F.H.G.); 0000-0002-9660-4313 (A.H.); 0000-0001-6443-1887 (A.F.);
0000-0002-4966-425X (N.v.W.).
In plants, the excess of several heavy metals mimics iron (Fe) deficiency-induced chlorosis, indicating a disturbance in Fe
homeostasis. To examine the level at which heavy metals interfere with Fe deficiency responses, we carried out an in-depth
characterization of Fe-related physiological, regulatory, and morphological responses in Arabidopsis (Arabidopsis thaliana)
exposed to heavy metals. Enhanced zinc (Zn) uptake closely mimicked Fe deficiency by leading to low chlorophyll but high
ferric-chelate reductase activity and coumarin release. These responses were not caused by Zn-inhibited Fe uptake via IRON-
REGULATED TRANSPORTER (IRT1). Instead, Zn simulated the transcriptional response of typical Fe-regulated genes,
indicating that Zn affects Fe homeostasis at the level of Fe sensing. Excess supplies of cobalt and nickel altered root traits in
a different way from Fe deficiency, inducing only transient Fe deficiency responses, which were characterized by a lack of
induction of the ethylene pathway. Cadmium showed a rather inconsistent influence on Fe deficiency responses at multiple
levels. By contrast, manganese evoked weak Fe deficiency responses in wild-type plants but strongly exacerbated chlorosis in
irt1 plants, indicating that manganese antagonized Fe mainly at the level of transport. These results show that the investigated
heavy metals modulate Fe deficiency responses at different hierarchic and regulatory levels and that the interaction of metals
with physiological and morphological Fe deficiency responses is uncoupled. Thus, this study not only emphasizes the
importance of assessing heavy metal toxicities at multiple levels but also provides a new perspective on how Fe deficiency
contributes to the toxic action of individual heavy metals.
The contamination of arable soils with heavy metals
has become a worldwide concern due to the ever-
increasing industrial demand for metals. In particular,
mining, smelting, waste disposal, and also agriculture
contribute to the emission and distribution of heavy
metals in the environment, where they can exert a
detrimental effect on plant growth (Nagajyoti et al.,
2010). A large part of their adverse effects has been
explained by the inhibition of enzyme activities, the
production of reactive oxygen species, and the compe-
tition with other nutrients in various physiological
processes (Shahid et al., 2014). Among the most affected
nutrients is iron (Fe), which shares several similarities
with other heavy metals regarding chemical structure,
behavior, and availability in soils or uptake by plant
roots. An excess of several heavy metals can induce chlo-
rosis in younger leaves (Schaaf et al., 2006; Meda et al.,
2007; Morrissey et al., 2009; Fukao et al., 2011; Wu et al.,
2012), hence resembling the most typical visual symptom
of Fe deficiency (Vert et al., 2002; Wu et al., 2012). Even
in the absence of visual symptoms, heavy metals can
negatively interfere with Fe homeostasis, as seen in the
case of manganese (Mn; Allen et al., 2007; Lanquar
et al., 2010). Induction of Fe deficiency by heavy metals
is due, at least in part, to the broad substrate specific-
ity of IRON-REGULATED TRANSPORTER 1 (IRT1),
which can transport divalent metals, such as zinc (Zn),
cobalt (Co), nickel (Ni), cadmium (Cd), and Mn, besides
Fe (Connolly et al., 2002, 2003; Henriques et al., 2002;
Vert et al., 2002; Nishida et al., 2011). As these heavy
metals may outcompete Fe during root uptake, they
promote Fe deficiency and increase the up-regulation of
IRT1, which further favors an imbalanced uptake of
1
This work was supported by Vedecká Grantová Agentúra (grant
no. VEGA 1/0098/14 to A.F. and A.L.) and by the Deutsche For-
schungsgemeinschaft (grant no. WI1728/21-1) to N.v.W.
2
Address correspondence to vonwiren@ipk-gatersleben.de.
The author responsible for distribution of materials integral to the
findings presented in this article in accordance with the policy de-
scribed in the Instructions for Authors (www.plantphysiol.org) is:
Nicolaus von Wirén (vonwiren@ipk-gatersleben.de).
A.L., R.F.H.G., A.F., and N.v.W. designed the experiments; A.L.
performed all experiments with the assistance of R.F.H.G.; A.H. per-
formed the principal component analysis; A.L., R.F.H.G., and N.v.W.
analyzed the data and wrote the article with contributions of all the
authors.
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other metals over Fe. In fact, several studies have in-
dicated that Fe deficiency is associated with deleterious
effects caused by excess Cd or Zn and that the induction
of Fe deficiency-responsive genes is required to coun-
teract metal toxicity (Meda et al., 2007; Solti et al., 2008;
Fukao et al., 2011; Pineau et al., 2012).
In order to overcome Fe limitation, plants have
evolved different mechanisms to acquire Fe from
sparingly available Fe precipitates (Giehl et al., 2009).
Nongraminaceous plants employ a reduction-based
mechanism, which involves the solubilization of ferric
Fe via protons released into the rhizosphere followed
by the subsequent reduction of Fe(III) by FERRIC
REDUCTION OXIDASE2 (FRO2; Robinson et al.,
1999; Connolly et al., 2003). As shown in Arabidopsis
(Arabidopsis thaliana), ferrous Fe is then transported
across the root plasma membrane of outer root cells by
IRT1 (Vert et al., 2002). Recently, it was found that the
Fe(II)- and 2-oxoglutarate-dependent dioxygenase
FERULOYL-COA 69-HYDROXYLASE (F69H1) assists
the reduction-based strategy by solubilizing ferric Fe
from sparingly soluble sources (Rodríguez-Celma et al.,
2013; Schmid et al., 2014; Schmidt et al., 2014). This
enzyme is involved in the synthesis of coumarins, some
of which, upon release to the rhizosphere, are able to
mobilize Fe from insoluble precipitates (Fourcroy et al.,
2014; Schmid et al., 2014). At the transcriptional level,
Fe acquisition in nongraminaceous plants is coordi-
nated by the cooperative action of the basic helix-loop-
helix (bHLH) transcription factors FER-LIKE IRON
DEFICIENCY INDUCED TRANSCRIPTION FAC-
TOR (FIT) and bHLH38 and bHLH39 (Colangelo
and Guerinot, 2004; Yuan et al., 2008; Wu et al., 2012).
FIT also can interact with the transcription factors
ETHYLENE-INSENSITIVE3 (EIN3) and ETHYLENE-
INSENSITIVE3-LIKE1 (EIL1), which, similar to
bHLH38 and bHLH39, enhance FIT-mediated Fe acqui-
sition (Lingam et al., 2011). To avoid oxidative stress by
uncontrolled Fe uptake, IRT1 DEGRADATION FAC-
TOR1 (IDF1) mediates the degradation of the plasma
membrane-bound IRT1 protein (Shin et al., 2013). Intra-
cellular availability of Fe in roots is controlled by FER-
RITIN1 (FER1), which oxidizes and stores excess Fe
in order to prevent Fe-dependent oxidative stress (Briat
et al., 2010). Iron allocation, in turn, is regulated by
bHLH100 and bHLH101 (Sivitz et al., 2012; Wang et al.,
2013) and by the transcription factors POPEYE (PYE) and
MYB DOMAIN PROTEIN10 (MYB10) and MYB72 (Long
et al., 2010; Palmer et al., 2013). Although the Fe-sensing
mechanism is not yet completely known, a class of
Haemerythrin motif-containing Really Interesting New
Gene and Zinc-finger proteins and BRUTUS (BTS) from
rice (Oryza sativa) and Arabidopsis, respectively, have
been proposed as iron sensors (Kobayashi et al., 2013;
Selote et al., 2015). The E3 ligase BTS is involved in the
Fe-dependent posttranslational regulation of PYE-like
transcription factors (Selote et al., 2015). These tran-
scription factors then interact with PYE, which, in turn,
regulates the expression of genes involved in the in-
tracellular and intercellular transport of Fe in the root
stele, such as FERRIC REDUCTION OXIDASE3 (FRO3),
NICOTIANAMINE SYNTHASE4 (NAS4), and FERRIC
REDUCTASE DEFECTIVE3 (FRD3; Durrett et al., 2007;
Long et al., 2010; Palmer et al., 2013; Selote et al., 2015).
The expression of NAS4 is coregulated by MYB10 and
MYB72 (Palmer et al., 2013). MYB72 also is involved in
the regulation of the phenylpropanoid pathway, includ-
ing the synthesis of coumarins (Zamioudis et al., 2014),
thereby linking Fe acquisition and Fe allocation processes.
Taken together, the aforementioned genes represent a
set of Fe deficiency-responsive genes that act at differ-
ent regulatory levels, some of which are sensitive to other
heavy metals (van de Mortel et al., 2006; Wu et al., 2012).
Upon exposure to excess Zn, Cd, or Ni, Arabidopsis
induces the two major Fe acquisition genes IRT1 and
FRO2, resembling a genuine Fe deficiency (Becher et al.,
2004; van de Mortel et al., 2008; Fukao et al., 2011;
Nishida et al., 2011; Shanmugam et al., 2011; Wu et al.,
2012). Nevertheless, other studies using the same plant
species found a strong repression of IRT1 and FRO2 in
response to high Cd supply (Besson-Bard et al., 2009;
Hermans et al., 2011). Moreover, investigations of Fe
deficiency-related transcriptional markers upon metal
excess have been expanded to transcription factors (van
de Mortel et al., 2006, 2008; Hermans et al., 2011).
Therein, the expression of the transcription factors
bHLH38/39/100/101,PYE, and MYB72 was found to be
up-regulated under high Cd or Zn supply, suggesting
that Cd- and Zn-induced Fe deficiency is initiated at a
higher regulatory level. In contrast, Besson-Bard et al.
(2009) found no evidence for the induction of major
transcriptional regulators under elevated supplies of
Cd. Such discrepancies among experiments with dif-
ferent or even the same metal emphasize the necessity
to investigate a series of time points and heavy metal
concentrations and to standardize the plant cultivation
platform with a direct comparison with Fe-deficient
plants. The comparability of conditions is unequivocal
in order to assess how specifically particular Fe-regulated
gene sets respond to different heavy metals.
The large plasticity observed in root system archi-
tecture (RSA) under different nutrient deficiencies, in-
cluding Fe deficiency (Gruber et al., 2013; Giehl et al.,
2014), suggests that architectural root traits also may
exhibit a large variation after exposure to different
heavy metals. In the case of copper, lateral root emer-
gence turned out to be more sensitive to excess copper
supplies than primary root elongation (Lequeux et al.,
2010). In the case of Zn, changes in root traits depended
more strongly on the applied Zn dose. Lower concen-
trations of Zn induced lateral root elongation and
caused no further changes in RSA (Jain et al., 2013),
while higher concentrations inhibited both primary and
lateral root growth (Fukao et al., 2011; Richard et al.,
2011). However, so far, root architectural responses
have always been analyzed separately under Fe defi-
ciency or metal excess (Lequeux et al., 2010; Giehl
et al., 2012; Gruber et al., 2013; Jain et al., 2013; Yuan
et al., 2013). Thus, it remains unclear to what extent
changes in root morphology upon heavy metal exposure
Plant Physiol. Vol. 174, 2017 1649
Heavy Metal-Induced Iron Deficiency
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resemble those occurring under Fe deficiency and whether
such root morphological changes can be attributed to the
induction of Fe deficiency.
In order to assess whether and the level at which
heavy metals interfere with Fe deficiency responses,
we designed an integrative approach for the in-depth
characterization of Fe-related physiological, regulatory,
and morphological responses in Arabidopsis exposed
to heavy metals. Plants were cultivated under unified
experimental conditions that caused visual Fe defi-
ciency symptoms due to either a lack of Fe supply or
an excess of Zn, Co, Ni, Cd, or Mn. We then analyzed
Fe deficiency-related root and shoot physiological re-
sponses, RSA traits, and the transcriptional response of
Fe-regulated genes, which allowed ranking metals
according to their ability to induce Fe deficiency. This
systematic analysis showed that the occurrence and the
intensity of Fe deficiency responses evoked by the
tested metals differ substantially and are manifested at
multiple levels. Excess Zn mimics typical Fe deficiency
responses almost at all levels, whereas Co, Ni, and Cd
tweak distinct Fe-related processes and Mn undergoes
the least specific interaction with Fe. This study repre-
sents not only a novel type of multilevel comparative
assessment of heavy metal toxicity effects but also
provides a new perspective on the extent to which Fe
deficiency contributes to the toxic action of these heavy
metals.
RESULTS
Induction of Fe Deficiency Symptoms in Shoots by
Heavy Metals
The main goal of this study was to investigate the
extent to which heavy metal-induced Fe deficiency re-
sponses contribute to metal toxicity in Arabidopsis.
Therefore, we grew plants in the absence or presence of
75 mMFe-EDTA and a range of Zn, Co, Ni, Cd, or Mn
supplies to identify those metal concentrations that in-
duced leaf chlorosis and/or shoot biomass decrease
similar to that in Fe-deficient plants (Fig. 1). Plants
cultivated under elevated supplies of Zn, Co, Ni, or Cd
developed chlorosis in young leaves, which resembled
the typical visual symptoms observed in Fe-deficient
plants (Fig. 1A). As expected, the appearance of leaf
chlorosis was accompanied by a significant decrease in
chlorophyll levels, which, depending on the heavy
metal supply, were comparable to those of plants
grown on 0 mMFe (Fig. 1B). Both low Fe supply and the
excess supply of all tested heavy metals, particularly at
their highest concentrations, decreased shoot biomass
significantly (Fig. 1C). Despite the suppression of shoot
biomass, high Mn supplies induced neither any visible
sign of leaf chlorosis nor a significant decrease in chlo-
rophyll concentrations (Fig. 1). In fact, even when plants
were supplied with up to 2,000 mMMn, no apparent leaf
chlorosis was induced in plants (Supplemental Fig. S1).
Instead, brown spots appeared on the leaves, which are
indicative of Mn toxicity (Fecht-Christoffers et al., 2006;
Williams and Pittman, 2010).
To assess whether the high supplies of heavy metals
caused significant changes in elemental concentrations,
a detailed elemental analysis of the shoots was carried
out. By raising the supply of individual heavy metals in
the growth medium, the levels of these elements in-
creased considerably in plant shoots (Table I). Even
though the highest supplies of Zn, Co, Ni, and Cd
provoked visible leaf chlorosis and loss of chlorophyll
to a similar extent as under no Fe supply, these heavy
metals suppressed shoot Fe levels much less than the
lack of Fe supply (Table I). In fact, in those cases in
which a particular heavy metal induced visible symp-
toms of Fe deficiency and a similar drop in chlorophyll
concentrations to that under Fe deficiency, Fe concen-
trations in the shoots did not fall below critical
deficiency levels (Fig. 1; Table I; Giehl et al., 2012;
Marschner, 2012; Gruber et al., 2013). Zn treatments
slightly decreased Mn levels in addition to those of Fe,
whereas Co reduced phosphorus (P), potassium (K),
and Zn levels. Ni treatment decreased P, K, and Mg
levels, and Cd treatment decreased those of Zn and Mn
and, at 40 mMsupply, additionally those of calcium (Ca;
Table I). Excess Mn did not affect Fe levels in the shoots
but slightly decreased the concentrations of P and even
more of Ca and especially of Mg to severely deficient
levels. Thus, excess Mn supply provoked deficiency of
Mg rather than of Fe. With the exception of Mn- and
Cd-induced decreases in Ca and Mg concentrations,
none of the other alterations in mineral element con-
centrations could be associated with symptoms typical
of Fe deficiency in young leaves.
Since shoot Fe concentrations in metal treatments
did not fall below the critical threshold, we assessed
whether the severe chlorosis phenotype observed in
these treatments was related to hampered Fe remobili-
zation from source to sink tissues. Therefore, we con-
ducted another experiment in which we measured Fe
and metal concentrations in both young and old leaves
separately. In fact, Fe concentrations in young leaves of
metal-treated plants remained significantly above those
in Fe-deficient plants (Supplemental Fig. S2A). With ap-
proximately 70 mgg
21Fe in young leaves of Zn-treated
plants, young leaves also contained sufficient Fe for
chlorosis-free growth. Furthermore, the ratio of Fe in old
versus young leaves did not change relative to that in
control or Fe-deficient plants (Supplemental Fig. S2B),
indicating that Zn had no particular impact on Fe
remobilization from old to young leaves. A different
trend appeared in Co- or Cd-treated plants, in which
these metals may have impaired Fe remobilization.
The next step was to verify whether metals alter Fe
concentrations in the roots. We measured Fe and other
heavy metal concentrations in roots after the removal of
apoplastic Fe (Cailliatte et al., 2010; Zhai et al., 2014).
While the concentrations of remaining Fe in roots may
indicate that apoplastic Fe was not removed com-
pletely, all metal treatments significantly decreased Fe
levels in the roots (Supplemental Fig. S3). Nevertheless,
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Lešková et al.
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remaining Fe levels in metal-treated plants were still
2-fold higher than under no Fe supply, rendering it
unlikely that metal treatments led directly to deficient
Fe levels in roots.
In order to verify whether the added heavy metals
may have altered Fe availability by displacing Fe
from highly soluble Fe(III)-EDTA chelates, we first
performed a theoretical metal speciation analysis by
Figure 1. Appearance of typical Fe
deficiency-related symptoms in Ara-
bidopsis Columbia-0 (Col-0) plants
exposed to various heavy metals. A,
Shoot phenotypes. B, Chlorophyll
concentrations of the shoots. C, Shoot
fresh weights. Seedlings were precul-
tured for 7 d in one-half-strength
Murashige and Skoog (MS) me-
dium and then transferred to one-half-
strength MS medium with (control) or
without Fe + 50 mMferrozine (0 Fe) or
with Fe and the supplementation of the
indicated concentrations of different
heavy metals. Plants were cultivated
on these treatments for 9 d. Bars rep-
resent means 6SD;n=3to4.Asterisks
indicate statistically significant differ-
ences from the control treatment
according to Tukey’s test (*, P,0.05;
**, P,0.01; and ***, P,0.001). FW,
Fresh weight.
Plant Physiol. Vol. 174, 2017 1651
Heavy Metal-Induced Iron Deficiency
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Table I. Elemental concentrations in shoots of Arabidopsis plants grown on various concentrations of heavy metals
Seedlings were precultured in one-half-strength MS medium for 7 d and then transferred to one-half-strength MS medium (control) or one-half-strength MS medium supplemented with the
indicated concentrations of metals for 9 d. Values represent means 6SD. Different letters indicate statistically significant differences among means for each heavy metal (P,0.05, Tukey’s test);
n.d., not detected. Boldface values are significantly lower than those measured in Fe-supplemented control plants. Values for Ca, K, Mg, P, and S are in mg g21, and those for Fe, Cd, Co, Mn, Ni,
and Zn in mgg
21.
Treatment Ca K Mg P S Fe Cd Co Mn Ni Zn
mM
Fe 75 5.8 60.4 b 53.5 63.2 b 1.8 60.1 b 15.7 61.3 a 8.2 60.4 a 89.7 66.6 a n.d. n.d. 213 614.4 b n.d. 162 615.0 b
0a9.9 61.6 a 60.7 68.3 a 2.7 60.5 a 15.9 62.2 a 21.3 63.6 b 19.3 610.7 b n.d. n.d. 456 652.3 a n.d. 1,006 6234.3 a
Zn 18 5.1 60.7 b 54.1 63.8 b 1.4 60.1 ab 14.3 61.1 a 8.6 60.6 b 89.7 66.6 a n.d. n.d. 199 611.2 b n.d. 157 69.3 d
75 6.1 60.4 a 63.1 64.4 a 1.5 60.1 a 14.8 61.9 a 13.5 61.7 ab 65.9 611.3 b n.d. n.d. 220 616.8 a n.d. 641 6160.7 c
150 6.0 60.8 a 56.2 65.1 b 1.5 60.1 ab 13.8 61.3 a 17.1 61.4 a 54.3 622.3 b n.d. n.d. 184 620.0 b n.d. 1,060 690.7 b
225 5.1 60.4 b 52.7 65.4 b 1.3 60.1 b 12.8 61.7 a 16.6 61.3 a 63.4 617.7 b n.d. n.d. 158 614.9 c n.d. 1,325 681.9 a
Co 0.05 4.0 66.3 b 51.9 64.2 a 1.6 60.1 b 13.3 61.3 a 10.0 60.6 c 89.7 66.6 a n.d. n.d. d 191 614.9 a n.d. 161 633.7 a
50 4.9 65.5 a 49.3 63.5 ab 1.8 60.1 a 12.9 61.3 ab 15.2 60.7 a 82.2 65.4 a n.d. 197 618.9 c 210 617.0 a n.d. 116 626.8 b
90 4.6 62.0 a,b 45.9 62.2 b 1.6 601. a,b 11.5 61.2 b,c 14.6 60.9 a,b 56.8 614.8 b n.d. 328 623.8 b 208 610.1 a n.d. 111 62.1 b
110 3.9 64.9 b 45.4 61.4 b 1.5 60.1 b 10.9 61.0 c 13.7 60.6 b 58.0 69.7 b n.d. 406.9 630.9 a 201 612.3 a n.d. 113 65.6 a,b
Ni 0 2.7 60.3 b 49.9 63.8 b 1.3 60.1 a 12.0 61.2 a 8.0 60.5 b 89.7 66.6 a n.d. n.d. 166 615.3 b n.d. d 169 624.2 c
60 3.4 60.5 a 58.3 67.8 a,b 1.1 60.1 a,b,c 13.5 61.6 a 11.2 61.8 a 75.6 68.6 ab n.d. n.d. 225 634.0 a 80 613.7 c 330 650.4 a
100 2.4 60.3 b 55.0 62.5 a 1.1 60.1 b 9.4 60.9 b 9.7 60.7 a 71.2 66.8 b,c n.d. n.d. 146 612.1 b 140 616.9 b 245 616.9 b
150 3.1 60.4 a 39.6 63.3 c 1.0 60.1 c 7.4 60.8 b 8.7 61.4 a 49.9 612.2 c n.d. n.d. 118 611.8 b 296 636.2 a 192 637.4 b
Cd 0 5.0 60.3 b 50.0 61.8 b 1.6 60.1 c 14.2 60.9 c 8.4 60.5 c 89.7 66.6 a n.d. c n.d. 211 615.0 b n.d. 169 623.2 a
57.860.6 a 68.8 64.9 a 2.2 60.1 a 20.4 62.0 a 18.3 62.2 b 61.0 68.9 b 200 635.7 b n.d. 235 613.8 a n.d. 165 616.4 a
20 4.3 60.4 b 58.4 65.0 ab 1.8 60.2 b 16.8 61.1 b 24.2 62.4 a 65.2 612.5 b 238 630.0 a,b n.d. 139 613.7 c n.d. 149 638.4 ab
40 3.3 60.3 c 52.3 62.4 b 1.6 60.1 b,c 16.2 61.1 b 21.3 61.5 a,b 66.3 618.4b 280 615.7 a n.d. 118 613.5 c n.d. 118 610.5 b
Mn 40 3.2 60.1 b 46.1 62.2 a 1.2 60.05 a 8.7 60.3 a 6.4 60.3 c 89.7 66.6 a n.d. n.d. 143 68.7 c n.d. 128 623.4 b
1,000 2.1 60.3 b 48.4 66.0 a 0.6 60.05 b 8.8 61.3 a 10.1 60.9 a 83.8 612.7 a n.d. n.d. 2,261 6286.4 b n.d. 228 618.4 a
1,250 2.7 60.8 b 51.7 66.7 a 0.6 60.2 b,c 6.1 60.6 b 7.8 60.4 b 74.7 615.7 a n.d. n.d. 2,785 6386.0 a,b n.d. 207 619.1 a
1,500 1.3 60.4 c 47.4 62.5 a 0.5 60.1 c 7.5 60.7 b 10.3 60.5 a 75.4 613.1 a n.d. n.d. 2,650 6135.5 a n.d. 235 620.3 a
Critical valuesb5 - 3 50 - 20 3.5 - 1.5 5 - 3 5 - 1 150 - 50 – – 20 - 10 10 - 0.01 20 - 15
a
0Fe+50mMferrozine. bAccording to Marschner (2012) and Gruber et al. (2013).
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simulating the elemental composition of the different
agar media used in our experiments. According to a
simulation carried out with Visual MINTEQ 3.1 software
(Gustaffson, 2012), the presence of metals provoked no or
only little displacement of Fe from Fe(III)-EDTA com-
plexes (3% or less) except for Ni, which lowered Fe
availability by 10% (Supplemental Table S1). Therefore,
we directly compared plant responses to heavy metals
when Fe was supplied as Fe(III)-EDTA or Fe(III)-
EDDHA. Fe(III)-EDDHA is more stable than Fe(III)-
EDTA (pK of 35.1 versus 25.1, respectively; Smith and
Martell, 1989) and more resistant to photodegradation
(Yunta et al., 2003). According to Fe and chlorophyll
concentrations, Zn and Ni induced leaf chlorosis to a
highly similar extent when supplemented with Fe(III)-
EDTA or Fe(III)-EDDHA (Supplemental Fig. S4). There-
fore, a reduced Fe availability prior to uptake was unlikely
to contribute to the heavy metal-induced Fe deficiency
responses.
Effects of Excess Heavy Metals on Physiological Root
Responses to Fe Deficiency
In the next step, we assessed whether heavy metal-
induced stress is associated with typical Fe deficiency-
related physiological responses in roots and focused on
ferric chelate reduction. Plants were subjected to metal
concentrations shown to induce Fe deficiency symp-
toms after 9 d (Fig. 1; Table I). Already after 3 d of metal
exposure, the expression of FRO2, which is responsible
for most of the Fe deficiency-induced ferric-chelate re-
ductase (FCR) activity in Arabidopsis roots (Robinson
et al., 1999), was induced by high Zn and Co almost to
the same degree as by Fe deficiency (Fig. 2A). Tran-
script levels of this gene also were up-regulated by all
other heavy metals, although to a lesser extent. During
the time course of metal exposure, FRO2 transcript
levels dropped markedly, but they remained higher in
roots of plants grown on low Fe or excess Zn (Fig. 2A).
As expected, the high levels of FRO2 expression in
Fe-deficient roots were accompanied by higher FCR
activities (Fig. 2B). In agreement with the induction of
FRO2 expression, also high Zn and Co provoked sig-
nificant increases in FCR activities. In the case of Co,
however, such an induction was limited to the first time
point (Fig. 2B). Ni also induced FCR activity, although
to a lower extent than low Fe or high Zn and Co. Roots
treated with high Mn experienced only a slight increase
in FRO2 transcript levels and FCR activity (Fig. 2). The
weak but significant up-regulation of FRO2 expression
by Cd excess was not translated into increased FCR
activities at any time point.
Recently, it was shown that Fe deficiency induces the
synthesis and release of coumarins in roots of Arabi-
dopsis (Rodríguez-Celma et al., 2013; Fourcroy et al.,
2014; Schmid et al., 2014). However, it is not yet known
whether excess heavy metals also can induce such a
response. Therefore, we first assessed the responsive-
ness of F69H1 to excess heavy metals (Fig. 3A). As
expected, Fe deficiency up-regulated transcript levels of
F69H1 during the whole course of the experiment. Zn
and Co caused similarly high transcript levels of this
gene at the earliest time point. However, F69H1
up-regulation by high Co was not sustained after pro-
longed exposure to this heavy metal. High Ni and high
Figure 2. FRO2 expression and root Fe(III)-chelate reductase activity in
response to heavy metal supplies. Time-course analysis is shown for
FRO2 transcript levels (A) and root Fe(III)-chelate reductase activities (B)
of plants exposed to different treatments. Seven-day-old seedlings
grown on one-half-strength MS medium were transferred to one-half-
strength MS medium with (control) or without Fe + 50 mMferrozine
(0 Fe) or with Fe and supplemented with 225 mMZn (++Zn), 110 mMCo
(++Co), 100 mMNi (++Ni), 5 mMCd (++Cd), or 1,500 mMMn (++Mn).
Bars represent means 6SE;n= 5 to 6. Asterisks indicate statistically
significant differences from controls at each time point according to
Tukey’s test (*, P,0.05; **, P,0.01; and ***, P,0.001). FW, Fresh
weight.
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Cd supplies caused only an initial slight up-regulation
of F69H1, whereas Mn caused either no induction or
even a down-regulation, as evident over the long term
(Fig. 3A). Many coumarins synthesized in response to
low Fe availability exhibit fluorescence when exposed
to UV light (365 nm), which allowed us to monitor
the appearance of coumarin-dependent fluorescence in
roots and in the agar (Fig. 3B). Compared with control
conditions, the cultivation of plants without Fe sup-
plementation resulted in a strong accumulation of flu-
orescence in roots and in the agar (Fig. 3, B and C).
Although more pronounced at the first time point (i.e.
3 d after starting the treatments), the increased levels of
fluorescence detected in the agar persisted over 9 d.
None of the heavy metals provoked such a response at
the earliest time point (Fig. 3B). However, excessive
Figure 3. Effects of heavy metals on F69H1 gene expression and the accumulation of fluorescent coumarins in roots and root
exudates. A, Time course of F69H1 transcript levels. B, UV fluorescence visualized at 365-nm wavelength. C and D, Relative
fluorescence measured in roots and agar of plants grown on no supplementation of Fe + 50 mMferrozine (0 Fe) for 3, 6, and 9 d (C)
or excess heavy metal supplies for 6 d (D). Relative quantification was based on average pixel intensities of equally defined lengths
of roots and agar portions around the roots. Seven-day-old seedlings grown on one-half-strength MS medium were transferred to
one-half-strength MS medium with (control) or without Fe + 50 mMferrozine (0 Fe) or with Fe and supplemented with 225 mMZn
(++Zn), 110 mMCo (++Co), 100 mMNi (++Ni), 5 mMCd (++Cd), or 1,500 mMMn (++Mn). Bars represent means 6SE;n= 25 to 30.
Asterisks indicate statistically significant differences from controls at each time point according to Tukey’s test (*, P,0.05;
**, P,0.01; and ***, P,0.001).
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supply of Zn provoked a significantly higher fluores-
cence in both roots and agar after a period of 6 d (Fig. 3,
B and D). Co, Cd, and Ni supplies, in this order, caused
less but still significant increases in agar fluorescence (Fig.
3, B and D). Thus, these heavy metals stimulated a mod-
erate synthesis and secretion of fluorescent coumarins.
Altogether, these results indicated that Zn induced
all root physiological responses typically associated
with Fe deficiency, while Co and Ni moderately af-
fected FCR activity and coumarin synthesis or release.
In contrast, high Cd and Mn did not provoke prominent
changes in Fe-related physiological root responses.
Effects of Excessive Heavy Metal Supplies on RSA
RSA is highly responsive to nutritional conditions
and can be employed as a read-out for the plant nutri-
tional status (Malamy, 2005; Giehl et al., 2014). Thus, we
compared the RSA of plants grown under a range of Fe
or heavy metal concentrations and assessed which RSA
traits responded most sensitively to metals. Mild Fe
deficiency, which was obtained by growing plants with
the supply of 5 or 2.5 mMFe-EDTA, caused a small but
significant increase in primary root length and a slight
increase in average lateral root length (Fig. 4A; Table II).
Only when Fe concentrations in the growth medium
dropped below 1 mMdid the length of the lateral roots
decrease significantly. Noteworthy, the addition of
ferrozine, a potent Fe(II) chelator, to Fe-deficient me-
dium resulted in an additional repression of primary
root length. In contrast, lateral root density decreased
consistently with decreasing Fe supplies, suggesting
that this root trait is the most sensitive to Fe limitation
(Fig. 4A; Table II).
Increasing supplies of all tested heavy metals re-
duced root growth and altered the plants’RSA, to some
degree, in a metal-dependent manner (Fig. 4, B–F; Table
II). With regard to lateral root density, the Co and Ni
treatments were most clearly set apart from the Fe de-
ficiency response, because lateral root densities in-
creased with increasing Co or Ni supplies (Fig. 4, C and
D; Table II). In the case of Ni, the most sensitive RSA
component was primary root length, as a significant
decrease in primary root length was recorded before
any change in lateral root density or average lateral root
length was detected (Fig. 4D; Table II). In general, de-
creasing primary root and lateral root lengths were
observed with all metal treatments without any initial
increase at lower metal doses, as observed under mild
Fe deficiency. Increasing the supply of Zn and Cd led to
prominent decreases in primary root length and lateral
root density, which appeared to progress more inten-
sively than under Fe deficiency (Fig. 4, B and E; Table
II). Also, average lateral root length responded more
sensitively to elevated doses of Zn and Cd than to a
shortage in Fe supply. Unlike Zn and Cd, excess Mn
induced more similar root architectural changes to
those seen under progressing Fe deficiency, since the
repression of lateral root density and average lateral
root length set in before Mn caused any effect on pri-
mary root length (Fig. 4F; Table II).
In order to capture the major trends in the variation of
RSA traits under the metal treatments tested in this
study, we conducted a principal component analysis
(PCA) of the measured root traits. According to PCA,
principal component 1 (PC1) and principal component
2 (PC2) explained 58% and 35% of the variation of the
measured traits among the treatments, respectively
(Fig. 5A). In order to determine how much each prin-
cipal component is loaded by individual root traits, we
conducted Pearson’s correlation analysis between root
traits and principal components. PC1 was highly cor-
related with primary and lateral root lengths, while
PC2 was strongly determined by variations in lateral
root density (Fig. 5B). Most clearly, high Ni and Co
treatments separated from Fe deficiency and other
metal treatments along PC2. This was reflected by the
prominent increase in lateral root density under high Ni
and Co. In fact, on the PCA plot, the gradual decrease in
root trait variability under decreasing Fe supply mostly
overlapped with those observed at increasing levels of
Mn (Fig. 5A). Only at higher doses of Mn (1,500 mMor
greater) did root traits separate more along PC2. Ini-
tially, RSA trait changes under Zn and Cd excess also
followed a similar pattern to that in Fe treatments;
however, variations in RSA traits observed already at
greater than 150 mMZn or greater than 20 mMCd
were distributed farther along PC1 than those obtained
under decreasing Fe supplies. This indicated that a
growing excess of heavy metals led to more severe
changes in root phenotypes than were achieved upon
limiting Fe supplies. Considering the direction and
distance by which PCA clusters moved under increas-
ing metal supplies, this analysis indicated that the
pattern of RSA trait changes, especially under Mn and,
to a lesser extent, under Zn and Cd excess, mostly re-
sembled those induced by Fe deficiency, whereas Co-
and Ni-induced changes were most distinguishable.
Impact of Foliar Fe Supply and IRT1-Mediated Fe Uptake
on Heavy Metal-Induced Physiological and
Morphological Responses
To assess whether plant responses to heavy metals
were indicative of a systemic Fe deficiency status, we
supplied Col-0 plants grown under excess Zn, Ni, or
Mn with foliar Fe. By alleviating chlorosis, preventing
FCR activation, and inhibiting primary and lateral root
elongation (Fig. 6, A–D), foliar Fe supply reversed al-
most all Fe deficiency-related responses provoked by
high-Zn treatment, even though Zn still overaccumulated
heavily in shoots (Supplemental Fig. S5). This may be
indicative of a direct interaction of Zn with systemic Fe
signaling. Only suppressed lateral root density evoked by
high Zn supply was not reversed by foliar Fe treatment
(Fig. 6E), which was related to the fact that the lateral root
density of control plants even decreased by foliar Fe
supply and showed an opposite response to other root
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traits. In contrast, foliar supply of Fe to high-Mn-treated
plants did not affect any of the measured traits (Fig. 6). In
addition, foliar Fe supply to Ni-treated plants had no
impact on morphological root traits (Fig. 6, C–E), al-
though Fe application fully recovered shoots from
chlorosis and prevented the activation of FCR (Fig. 6,
Figure 4. RSA of Arabidopsis in response to elevated heavy metal supplies and low Fe. Seedlings were exposed to different
concentrations of Fe (A), Zn (B), Co (C), Ni (D), Cd (E), or Mn (F). Representative plants for each treatment are shown; n= 30 to 40.
Seedlings were precultured for 7 d in one-half-strength MS medium and then transferred to one-half-strength MS medium
(control) or one-half-strength MS medium containing the indicated concentration of each metal for a further 10 d.
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A, B, and F). Therefore, root architectural changes evoked
by Ni (Fig. 4) clearly were not related to systemic Fe de-
ficiency but rather caused by a local toxic effect of Ni.
Since IRT1 mediates the uptake of all heavy metals
investigated here, we asked whether the differential
effect of metals on Fe deficiency-related responses
simply reflects an inhibition of IRT1-mediated Fe up-
take by metals. Thus, we examined physiological and
morphological responses to high Zn, Ni, and Mn in irt1
mutant plants. Compared with wild-type plants, irt1
mutants were not only affected by high Zn but more
sensitive to high Ni and even to high Mn in terms of
chlorophyll levels (Fig. 6, A and B). Notably, high Mn
induced Fe deficiency at the physiological level specif-
ically in irt1 plants, as observed by a prominent increase
in root FCR activity (Fig. 6F). The absence of func-
tional IRT1 decreased the shoot levels of Fe and, to a
lesser extent, those of Zn (Supplemental Fig. S5), in-
dicating that, especially in the presence of excess
metals, IRT1 contributed to Zn but not to Ni or Mn
accumulation.
Finally, we tested whether those metal-induced
physiological and morphological responses, which
were independent of IRT1-mediated uptake, could be
reversed by foliar Fe supply. In fact, Fe supply to irt1
shoots brought back chlorophyll to wild-type levels
and effectively repressed root FCR activity under ex-
cess Zn, Ni, or Mn (Fig. 6, A, B, and F), while shoot
accumulation of these metals was not suppressed by
leaf Fe supply (Supplemental Fig. S5). This substantial
recovery suggested that the interference of metals with
physiological responses was not caused at the level of
IRT1 but rather regulated by metal-Fe interactions in
the shoot. With regard to morphological root traits,
foliar Fe did not prevent the occurrence of any of the
metal-induced symptoms in irt1 (Fig. 6, C–E), indicating
that metal-induced root morphological changes in irt1
were not affected by the plants’Fe nutritional status.
Table II. Primary root length, lateral root density, and average lateral root length of plants grown on
various concentrations of heavy metals
Values represent means 6SD. Different letters indicate statistically significant differences among means
for each heavy metal (P,0.05, Tukey’s test).
Treatment Primary Root Length Lateral Root Density Average Lateral Root Length
mMcm root21no. cm21primary root cm root21
Fe 75 (control) 8.5 60.8 b 2.9 60.5 a 0.8 60.2 a,b
5 9.2 60.9 a 2.4 60.5 b 1.0 60.2 a
2.5 8.9 60.8 a 2.3 60.4 b,c 0.9 60.2a
1 8.6 60.9 a,b 1.8 60.5 d 0.7 60.2 b,c
0 8.0 61.0 b,c 1.6 60.3 d 0.7 60.2 c
0 + ferrozine 6.5 60.8 c 1.8 60.5 c,d 0.6 60.2 c
Zn 18 (control) 7.4 60.6 a 2.7 60.4 a 0.7 60.2 a
75 6.4 60.6 b 2.7 60.5 a 0.6 60.1 b
150 5.5 60.7 c 2.0 60.4 b 0.4 60.1 c
225 4.8 60.5 d 1.6 60.4 b 0.3 60.1 d
300 4.0 60.7 e 1.5 60.5 b 0.2 60.1 d,e
450 2.8 60.4 f 1.7 60.7 b 0.1 60.1 e
Co 0.05 (control) 7.6 60.4 a 2.9 60.5 c 1.1 60.2 a
50 6.9 60.8 b 3.0 60.6 b,c 0.7 60.2 b
70 6.3 61.0 b,c 3.5 60.8 a,b 0.6 60.2 b,c
90 6.3 61.0 c,d 3.5 60.8 a 0.6 60.2 c,d
110 4.7 61.1 d,e 3.7 60.9 a 0.5 60.2 d,e
130 4.2 61.1 e 4.1 60.9 a 0.4 60.1 e
Ni 0 (control) 7.0 60.7 a 2.9 60.5 b 0.9 60.2 a
40 7.3 62.1 a 2.7 61.5 b 0.9 60.3 a
60 6.9 60.7 a 2.7 60.4 b 0.8 60.1 a
80 6.1 60.7 b 2.9 60.5 b 0.8 60.1 a
100 2.8 60.6 c 4.7 61.4 a 0.8 60.2 a
150 2.2 60.6 c 4.9 61.6 a 0.3 60.2 b
Cd 0 (control) 6.8 61.1 a 2.7 60.4 a 0.8 60.2 a
5 8.1 61.0 a 2.3 60.5 a 0.8 60.2 a
20 5.3 60.5 b 1.2 60.3 d 0.5 60.2 b
40 4.0 60.5 b,c 1.6 60.5 c 0.4 60.1 c
60 3.5 60.3 c,d 1.9 60.5 b,c 0.3 60.1 c,d
80 3.0 60.3 d 2.3 60.6 a,b 0.2 60.1 d
Mn 40 (control) 7.5 60.6 a 2.9 60.3 a 0.8 60.3 a
500 7.9 60.7 a 2.6 60.3 a,b 0.8 60.2 a,b
100 7.4 60.8 a 2.2 60.4 b,c 0.6 60.2 b,c
1,250 8.1 61.3 a 2.0 60.6 c,d 0.5 60.2 c
1,500 6.3 61.3 b 2.0 60.5 c,d 0.5 60.3 c
2,000 4.4 60.9 c 1.2 60.6 d 0.2 60.1 d
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Figure 5. PCA of the variation in RSA traits in response to Fe deficiency and heavy metal supplies. PCAwas based on primary root
length (PRL), lateral root density (LRD), and average lateral root length (AVG LRL) measured under the indicated treatments. A,
PC1, explaining 58% of the variation, was plotted against PC2, explaining 35% of the variation. B, Correlation analysis of root
traits and principal components. r2values define coefficients of determination. Asterisks indicate statistical significance of the
correlation between root traits and principal components: ***, P,0.001.
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The Effect of Heavy Metals on the Expression of Fe
Deficiency-Responsive Genes
In order to investigate whether individual heavy
metals provoke Fe deficiency responses at the regula-
tory level, we assessed transcriptional changes in roots
of 18 Fe deficiency-regulated genes in response to metal
supplies (Fig. 7; Supplemental Table S2). Since it is
difficult to establish comparable concentrations for the
tested heavy metals, the expression analysis was car-
ried out in a time course using two doses per heavy
metal. By this procedure, we assessed how sensitively a
Figure 6. Effects of foliar Fe supply on the occurrence of heavy metal-induced physiological and morphological responses in
Col-0 and irt1. Seven-day-old seedlings grown on one-half-strength MS medium were transferred to one-half-strength MS me-
dium containing elevated concentrations of the indicated heavy metals. Leaves were supplied or not with 250 mMFe(III) citrate. A,
Appearance of plants. B, Chlorophyll concentration. C, Primary root length. D, Average lateral root (LR) length. E, Lateral root
density. F, FCR activity. Bars represent means 6SD. Different letters indicate statistically significant differences among means for
each heavy metal (P,0.05, Tukey’s test). FW, Fresh weight.
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particular gene responded to increasing concentrations
of and/or exposure time to a particular heavy metal.
Relative to control conditions (one-half-strength MS
medium supplied with 75 mMFe), metal concentrations
used in this experiment caused significant (P,0.05)
reductions in shoot fresh weight (Fig. 1C), chlorophyll
concentrations (Fig. 1B), and shoot Fe concentrations
(Table I). In the case of Mn, only the shoot fresh weight
criterion was employed. For the normalization of
transcript levels, we selected UBIQUITIN2 (UBQ2)asa
reference gene, since it showed the highest expression
stability in response to the treatments used in this study
(Supplemental Fig. S6).
In accordance with previous studies, 15 genes were
either mildly or very strongly up-regulated as soon as
3 d after transferring plants to Fe-deficient conditions
(Fig. 7). As expected, only transcript levels of FER1,
which is induced by excess Fe and, hence, correlates
positively with the Fe status of plants (Briat et al., 2010;
Reyt et al., 2015), was consistently down-regulated
in roots of Fe-deficient plants (Fig. 7). As the expo-
sure time to Fe-deficient growth conditions progressed,
the transcript levels of IRT1 and FRO2 and of the
Fe-responsive bHLH-type transcription factors tended
to decrease, whereas those of EIL1,EIN3,andIDF1 rose
more significantly at later time points.
Both tested Zn supplies produced transcrip-
tional changes that resembled those triggered by Fe
deficiency (Fig. 7). In particular, mRNA levels of all Fe
deficiency-induced transcription factors experienced a
strong up-regulation by high Zn even after prolonged
exposure to this heavy metal. In the short term, high Co
supply also was able to significantly induce the ex-
pression of most Fe-regulated genes, except for NAS4,
which was significantly up-regulated only in the long
term (Fig. 7). However, the effect of Co on the expres-
sion of these genes was less persistent, as most of them,
including FIT,IRT1,FRO2,FRO3, and F69H1, were no
longer up-regulated after 9 d. Additionally, the ex-
pression of ethylene signaling genes remained unaf-
fected by Co as well as by Ni during the whole time
course of the experiment.
Despite reducing shoot growth and inducing leaf
chlorosis (Fig. 1), an excess of Cd and even more of Ni
caused relatively mild changes in the expression pat-
terns of most Fe deficiency-regulated genes (Fig. 7).
Nonetheless, both heavy metals were able to enhance
transcript levels of MYB72 as well as of bHLH100,
bHLH101,bHLH38, and bHLH39,confirming that these
genes also are sensitive to Ni and Cd. PYE,BTS,EIN3,
EIL1, and FIT were up-regulated by Cd but not by Ni,
even though this response was limited to a single time
point (Fig. 7). Interestingly, in spite of the lack of an
unequivocal increase in mRNA levels of FIT, those of
IRT1 and FRO2 were induced after 3 d on Ni excess. On
the other hand, Ni highly induced the up-regulation of
IDF1, even though IRT1 transcript levels of Ni-supplied
plants were significantly lower than those measured
under Fe deficiency. In the short run, the effect of high
Mn doses was restricted to a mild up-regulation of
Figure 7. Expression of Fe deficiency-related genes in roots under ex-
cess heavy metal supplies. The color code of the heat map indicates a
statistically significant (P,0.05) up-regulation (red) or down-regulation
(blue) of transcript levels under no supplementation of Fe + 50 mMfer-
rozine (0 Fe) or under the indicated supplies of heavy metals (mM). Gene
expression levels are expressed as fold change from control one-half-
strength MS medium treatment supplemented with 75 mm Fe-EDTA. n.s.,
No statistically significant difference from the control treatment. Plants
were precultured for 7 d in one-half-strength MS medium and then
transferred to one-half-strength MS medium with (control) or without
Fe + 50 mMferrozine (0 Fe) or with Fe and containing the indicated
concentrations of heavy metals (mM) for 3, 6, and 9 d.
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IRT1,FRO2,FRO3, and most Fe-regulated transcription
factors, except for FIT (Fig. 7). However, after 6 and 9 d
of exposure to Mn excess, the expression of most
Fe-responsive genes remained at a basal level or was
even significantly down-regulated, as was the case for
bHLH100,FRD3, and F69H1 after 9 d.
In order to extract major trends of metal-dependent
transcriptional responses over time, all transcriptional
data obtained in this study were subjected to cluster
analysis. As compared with the other heavy metals
tested herein, excess Mn produced the most dissimilar
transcriptional responses to Fe deficiency (Fig. 8). By
contrast, the transcriptional changes induced by Zn
excess largely resembled those induced by Fe deficiency.
Changes in transcript patterns evoked by elevated Co
supplies clustered with low Fe particularly in the short
run. Transcriptional changes recorded under Cd and Ni
excess resembled to some extent those observed under
Fe deficiency only at the intermediate time point (Fig. 8).
Taken together, metal-induced transcriptional responses
resembled those observed under Fe deficiency in the
order Zn .Co .Cd .Ni .Mn.
DISCUSSION
Heavy metal treatments have been frequently repor-
ted to mimic Fe deficiency symptoms and to induce Fe
deficiency responses in plants (Schaaf et al., 2006; Meda
et al., 2007; Fukao et al., 2011; Wu et al., 2012). However,
due to a lack of comparability of traits and growth
conditions among studies, it remained mostly unclear to
what extent individual heavy metals interfere with Fe
homeostasis. To address this question, this study took a
novel integrative approach by determining shoot and
root morphological and physiological traits as well as
transcriptional markers from Arabidopsis plants sub-
jected to five heavy metals reported previously to in-
terfere with Fe uptake. Thereby, heavy metal doses were
adjusted in a way that leaf chlorosis was induced to a
similar extent to that under Fe deficiency. This procedure
allowed us to determine which Fe deficiency-related
traits are sensitive to heavy metals and to rank metals
according to their ability to induce Fe deficiency re-
sponses. Our analysis clearly shows that Zn, Co, Cd, and
Ni, but not Mn, induce typical Fe deficiency symptoms
even before decreasing shoot or root Fe below critical
deficiency levels. Notably, these metals strongly differ
in the extent, type, and combination of induced Fe
deficiency-related responses, indicating that they inter-
fere with Fe homeostasis at distinct levels.
Zn Strongly Induces Fe Deficiency Signaling and Related
Physiological Responses
Among all tested metals, elevated Zn supply provoked
the strongest induction of Fe deficiency-responsive genes
(Figs. 7 and 8) and of typical Fe deficiency-related phys-
iological responses in roots (Figs. 2 and 3). These changes
coincided with the growth reduction of roots and shoots
as well as with chlorosis in young leaves (Figs. 1 and 4B;
Marschner, 2012), although Fe concentrations in
shoots and roots were still above 60 mgg
21(Table I;
Supplemental Figs. S2 and S3), which are not yet below
Figure 8. Hierarchical cluster analysis of transcript levels in heavy
metal and low-Fe treatments. The dendrogram was obtained by clus-
tering 0 Fe (no Fe + 50 mMferrozine) and heavy metal treatments based
on log2-transformed values of fold change for each time point sepa-
rately. The colors of the lines indicate cluster membership. dat, Days
after treatment.
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the critical deficiency range (Giehl et al., 2012; Marschner,
2012; Gruber et al., 2013). A similar observation was made
by Fukao et al. (2011) when excessive Zn reduced chlo-
rophyll levels and induced Fe deficiency stress-responsive
proteins, although shoot Fe concentrations remained even
above 100 mgg
21. At the root physiological level, the
up-regulation of FRO2 and F69H1 expression by excess
Zn was translated into a strong stimulation of root FCR
activity (Fig. 2B) and an increased synthesis and exuda-
tion of coumarins (Fig. 3, B and D). These findings are in
accordance with previous studies, which have reported
elevated FRO2 protein levels (Fukao et al., 2011) and in-
creased transcript levels of genes coding for enzymes that
produce precursors of coumarins under high Zn supply
(van de Mortel et al., 2006). Notably, among all heavy
metals assessed in this study, Zn induced the strongest
root accumulation and release of fluorescent coumarins,
although at lower levels than those recorded in
Fe-deficient plants (Fig. 3). F69H1-dependent coumarin
synthesis in plants is regulated by FIT and potentially
by MYB72 (Schmid et al., 2014; Zamioudis et al., 2014).
FIT positively affects the transcript levels of MYB72,
which regulates the synthesis of several metabolites on
the phenylpropanoid pathway, including that of feruloyl-
CoA, the precursor of coumarins (Rodríguez-Celma et al.,
2013). Since FIT and MYB72 remained up-regulated more
consistently by excess Zn than by any other metal (Fig. 7),
high Zn mimicked most closely the Fe deficiency response
at the molecular and physiological levels.
In terms of RSA, plants from high-Zn treatments re-
sembled those grown under limiting Fe supplies only at
lower Zn doses. Not only the phenotypic comparison
but, in particular, the multivariate analysis showed that
the root architectural traits changed in the same direc-
tion in plants treated with either inadequate Fe or ele-
vated Zn concentration (Figs. 4, A and B, and 5; Table
II). Furthermore, we showed that foliar Fe supply was
able to revert most of the changes in root morphology
induced by Zn in wild-type plants (Fig. 6, C and D).
Assessing the natural variation in Zn tolerance by a
quantitative trait locus mapping approach has revealed
that root architectural traits of Arabidopsis plants
grown on high Zn are subject to cross talk between
mechanisms regulating Fe and Zn homeostasis (Pineau
et al., 2012). FRD3 gene expression and the corre-
sponding citrate-loading activity into the xylem corre-
lated positively with the shoot Fe status and primary
root growth when Arabidopsis accessions were grown
under high Zn supply. In our experiments, FRD3 ex-
pression was not altered significantly under high Zn
(Supplemental Table S2), which may be due to the fact
that elevated Zn triggers a complex posttranscriptional
regulation of FRD3 (Charlier et al., 2015). Nevertheless,
some effects of Zn surpassed those caused by Fe defi-
ciency, as especially the length of lateral roots was more
susceptible to increasing Zn supplies (Figs. 4, A and B,
and 5A). Such effects might involve an IRT1-independent
uptake pathway, since the lateral root elongation of irt1
plants by Zn could not be recovered by foliar Fe supply, as
opposed to the situation in wild-type plants.
Zn competes with Fe already at the level of uptake
via IRT1 (Korshunova et al., 1999) and decreases Fe
levels in the roots (Supplemental Fig. S3; Fukao et al.,
2011), which, in principle, would be sufficient to ex-
plain the subsequent induction of Fe deficiency-related
processes. As reported previously (Fukao et al., 2011;
Shanmugam et al., 2011, 2012), foliar Fe supply strongly
suppressed the development of chlorosis upon excess
Zn (Fig. 6, A and B) and reduced shoot Zn accumulation
to a certain extent (Supplemental Fig. S5). However,
assessing the irt1 mutant under the same conditions
showed that the suppression of Fe deficiency responses
under foliar Fe supply was not caused by lower shoot
accumulation of Zn (Supplemental Fig. S5). This find-
ing showed that IRT1-mediated Zn uptake was not
relevant for the expression of Fe deficiency-related re-
sponses but suggested a shoot-derived interaction, in
which foliarly supplied Fe outcompeted or displaced
Zn from binding sites relevant for shoot-to-root Fe
signaling. In agreement with this assumption, we ob-
served in roots that high Zn caused a pronounced and
consistent up-regulation of BTS, a gene encoding a
putative Fe sensor in Arabidopsis (Fig. 7), which might
be responsible for the perception of phloem-derived
Fe signals in roots (Kobayashi and Nishizawa, 2014).
Moreover, we observed that PYE, which is tightly con-
trolled by BTS-mediated Fe deficiency sensing (Selote
et al., 2015) and induced by Fe deficiency (Long et al.,
2010), also was strongly induced at the transcriptional
level by high Zn supply (Fig. 7; Supplemental Table S2).
This further supports the view that transcriptional
changes observed under excess Zn (Figs. 7 and 8) were
caused by an antagonistic interaction between Zn and
Fe at the level of Fe sensing and early Fe deficiency
signaling, which were then translated into a typical Fe
deficiency response.
Co, Cd, and Ni Affect Fe Homeostasis at Distinct Steps
Although Cd, Co, and Ni induced several Fe
deficiency-related responses, the effect of each of these
heavy metals was less systematic and typically restricted
to individual traits. It has been suggested previously that
Cd influences Fe-dependent gene regulation at a high
hierarchic level (van de Mortel et al., 2008; Hermans
et al., 2011). Indeed, high Cd supply resulted in a sig-
nificant although more transient induction of genes
with regulatory functions in Fe homeostasis (Figs. 7
and 8). Among those, FIT waslessconsistentlyinduced
than bHLH38/39 and bHLH100/101. In particular, over-
expression of bHLH39 alone, or also of bHLH38 or
bHLH39 together with FIT,haveprovenefficient in in-
creasing Cd tolerance (Wu et al., 2012), suggesting that
Cd modulates the regulation of Fe acquisition genes via
bHLH39 rather than via FIT. Despite a moderate in-
duction of FRO2, together with IRT1, at earlier time
points (Figs. 2A and 7), FCR activity in Cd-treated roots
remained indistinguishable from that in control roots
during the whole course of the experiment (Fig. 2B).
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Based on previous studies, there is no consensus about
the impact of elevated Cd on FRO2 regulation, as un-
changed (Chang et al., 2003), elevated (Chang et al., 2003;
Gao et al., 2011), or even repressed (López-Millán et al.,
2009; Gao et al., 2011; Hermans et al., 2011) FRO2 tran-
scription and/or FCR activities have been reported,
depending on the Cd concentrations, plant species, or
cultivation times used in these studies. However, our
study supports the notion that FRO2 and FCR are not
preferential targets of Cd interactions with Fe homeo-
stasis. Instead, Cd showed a prominent induction of PYE
and its target NAS4 as well as of bHLH100/101 (Fig. 7;
Supplemental Table S2), indicating that Cd predomi-
nantly influences the transcriptional control of genes
involved in the long-distance allocation of Fe in plants
(Long et al., 2010; Sivitz et al., 2012).
At the root architectural level, elevated Cd supplies
induced changes that greatly resembled those of plants
suffering from severe Fe deficiency (Figs. 4, A and E,
and 5A). However, in particular, primary root length
was more inhibited by high Cd than by Fe deficiency
(Figs. 4, A and E, and 5A). This may be due to the
concomitant decline of Ca concentrations below critical
deficiency levels (Table I), which strongly suppresses
primary root elongation (Gruber et al., 2013) and may
have added to the inhibitory action of Cd itself. This
side effect made RSA traits difficult to interpret purely
in the light of Cd-Fe interactions.
In the case of Co and Ni, the transcriptional responses
evoked by these metals were similar to Fe deficiency at
a rather early time point but weaker over the long term
(Figs. 7 and 8). High Co and Ni also resulted in a rapid
induction of FRO2 and F69H1 expression as well as FCR
activity (Figs. 2 and 3A). However, in contrast to Fe
deficiency, the expression of EIN3 and EIL1 was not
altered by excess Co or Ni at any time (Fig. 7). During Fe
deficiency, ethylene signaling via EIN3/EIL1 intensifies
the response of FIT, FIT-interacting transcription fac-
tors, and their downstream elements, as shown by
the down-regulation of FIT,IRT1,FRO2, and bHLH39 in
the ein3eil1 double mutant (Lingam et al., 2011). The
ethylene-dependent regulation of these genes also was
confirmed by Lucena et al. (2006) and García et al.
(2010) by inhibiting ethylene synthesis in Fe-deficient
plants with silver thiosulfate or Co supply at levels
comparable to those used in our study. Therefore, due
to the ability of Co to act as a negative feedback regu-
lator of ethylene synthesis, it is likely that Co sup-
pressed the sustained up-regulation of FIT and its target
genes in the long run (Figs. 2A, 3A, and 7). By contrast,
PYE and its target NAS4 remained induced even
after prolonged cultivation under high Co, indicating
that the expression of these genes depends less on an
ethylene boost (Fig. 7). This scenario may explain the
differential regulatory action of Co on FIT- and PYE-
dependent gene regulation and support the view of Co
affecting Fe acquisition primarily in the short run.
Unlike Zn and Cd treatments, the effect of Ni on the
up-regulation of regulatory components was restricted
to bHLHL38,bHLHL39,MYB72,bHLH100,andbHLH101
(Fig. 7; Supplemental Table S2). However, it is intriguing
that the expression of IRT1 and FRO2 (Figs. 2A and 7;
Supplemental Table S2) as well as FCR activity (Fig. 2B)
were significantly induced by Ni, even in the absence of
a clear induction of their closest upstream regulator FIT.
This observation suggests that the activation of the Fe
acquisition machinery by high Ni relies on the activation
of other transcription factors, such as bHLH38 and
bHLH39. Interestingly, IDF1 expression was induced in
Ni-treated plants to levels comparable to those detected
in Fe-deficient plants (Fig. 7). However, idf1 plants were
indistinguishable from wild-type plants when grown
under the excess of the heavy metals tested herein (data
not shown), suggesting that the degradation of IRT1
through IDF1 neither prevents nor promotes the heavy
metal susceptibility of plants. A minor involvement of
IRT1 in the induction of Fe deficiency by Ni is reinforced
by the finding that not only wild-type plants showed Fe
deficiency symptoms but even irt1 plants developed
stronger Fe deficiency-like physiological responses
when treated with high Ni (Fig. 6, A, B, and F).
In terms of RSA, Co and especially Ni produced the
most distinct changes in relation to the other heavy
metals and to Fe deficiency (Figs. 4 and 5). The excess of
Co and Ni significantly increased lateral root density,
which was opposite to the effect of Fe deficiency or el-
evated supply of other metals (Fig. 4; Table II). In ad-
dition, primary root length was severely inhibited by
Ni, while lateral root growth remained unaffected up
to higher doses of Ni (Fig. 4D; Table II), indicating that
the growth effects on roots of different orders were
uncoupled by high Ni supply. Foliar supplementa-
tion of Ni-treated plants with Fe was not efficient in
reverting the RSA changes, despite the full recovery of
chlorosis (Fig. 6, A–E). Thus, distinctive RSA changes
induced by Co and especially by Ni were unrelated to
Fe deficiency but likely caused by localized toxic effects
of these metals.
Excess Mn Provokes Fe Deficiency in the Absence of IRT1
In wild-type plants, excess Mn evoked changes in
RSA that strongly resembled Fe deficiency (Figs. 4, A
and F, and 5A). However, respecting the weak inter-
action of Fe and Mn at the regulatory and physiological
levels (Figs. 1–3, 7, and 8), it is less likely that the
morphological root phenotype was a consequence of
Mn-induced Fe deficiency in roots. This assumption
was additionally reinforced by the fact that extra Fe
supply did not alter Mn-dependent root architectural
traits (Fig. 6, C–E). The root phenotype provoked by
excess Mn also can hardly be explained by the recorded
Ca and Mg deficiency (Table I), as either of the related
root phenotypes showed a different coupling of af-
fected root traits (Gruber et al., 2013). In this regard, it
has been shown that primary root elongation is more
sensitive to Mn deficiency than lateral root branching
or elongation (Gruber et al., 2013). Together with
the observation that primary root elongation was less
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Heavy Metal-Induced Iron Deficiency
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sensitive to excess Mn than lateral root branching and
elongation (Fig. 4F; Table II), this may suggest a higher
Mn requirement for primary root elongation than for
lateral root development. Thus, it is more likely that
excess Mn shaped RSA in a similar way to Fe defi-
ciency did by directly affecting the root developmental
program.
Mn serves as a substrate for IRT1, and thus, Mn and
Fe competition can already take place at the level of root
uptake (Vert et al., 2002). Unlike the other metals
assessed herein, the effect of Mn on Fe deficiency re-
sponses was very limited and restricted mainly to re-
sponses at the root level. In shoots, exposure of plants to
Mn neither induced chlorosis in young leaves (Fig. 1, A
and B) nor substantially reduced Fe levels (Table I).
Even when considerably higher Mn concentrations
were supplied to plants, which resulted in severely
stunted shoot and root growth and the appearance of
brown spots on leaves, no signs of chlorosis were ob-
served in wild-type plants (Supplemental Fig. S1). In
fact, the formation of brown spots on leaves upon high
Mn supply results from Mn deposition in the leaf apo-
plast, which might prevent intracellular interference
of this heavy metal with Fe homeostasis (Fecht-
Christoffers et al., 2006). Intriguingly, decreased chloro-
phyll concentrations or the appearance of pale/yellowish
color in leaves have been reported as long-term symp-
toms of excess Mn supply in cowpea (Vigna unguiculata;
Horst, 1983), wheat (Triticum aestivum;Moronietal.,
1991), or even Arabidopsis (Dixit and Dhankher, 2011).
However, in these studies, Mn-induced chlorosis was not
restricted to young leaves, as is most typical for Fe defi-
ciency (Vert et al., 2002; Schmid et al., 2014). Notably, in
our experiments, excess Mn decreased the concentrations
of Ca and especially of Mg (Table I) below critical defi-
ciency levels for Arabidopsis plants (Gruber et al., 2013).
Therefore, excess Mn interferes more significantly with
Mg or even Ca nutrition than with Fe. In fact, we found
that, upon prolonged Mn exposure, almost none of the Fe
deficiency-induced genes were induced anymore, and
several genes related to Fe acquisition, such as F69H1,or
Fe allocation, such as bHLH100 and FRD3,wereeven
down-regulated (Fig. 7). Nevertheless, high Mn supply
decreased Fe levels in the roots (Supplemental Fig. S3),
down-regulated the expression of FER1,andcauseda
slight, short-term up-regulation of genes with regulatory
functions in Fe acquisition or distribution (Figs. 2A and 7;
Supplemental Table S2). Excess Mn led only initially to
a slight induction of FRO2 gene expression and root
FCR activity (Fig. 2), indicating that other Fe-related root
physiological responses were sufficient to cope with
an enhanced Mn over Fe uptake. In this context, a criti-
cal component preventing cytosolic Mn overload in
Fe-deficient Arabidopsis plants turned out to be MTP8
(Eroglu et al., 2016). MTP8 gene expression is under the
control of FIT, and the corresponding protein is respon-
sible for Mn loading into root vacuoles. Hence, mtp8
mutants suffer from Fe deficiency in the presence of Mn
(Eroglu et al., 2016). Likewise, irt1 mutant plants devel-
oped severe symptoms of Fe deficiency upon high Mn
supply, as revealed by the appearance of chlorosis and the
strong increase of FCR activity (Fig. 6, A, B, and F). A
similar scenario can be observed when wild-type plants
are cultivated under low-Fe and high-Mn conditions
(Eroglu et al., 2016). This suggests that, once Fe deficiency
responses are induced, the presence of additional Mn can
even strengthen the severity of the symptoms. Our study
also revealed that the promotion of Fe deficiency re-
sponses by Mn does not rely on IRT1-mediated uptake.
Instead, uptake by IRT1 circumvents the interactions be-
tween Mn and Fe. It is possible that other unspecificmetal
transporters, highly expressed under low external Fe
concentrations and derepressed in the absence of IRT1,
are responsible for Mn-induced Fe deficiency. The most
likely candidate appears to be NRAMP1, which facilitates
the uptake not only of Mn but also of Fe (Cailliatte et al.,
2010; Castaings et al., 2016).
CONCLUSION
Even though elevated supplies of Zn, Co, Ni, and Cd
caused typical symptoms of Fe deficiency-induced
chlorosis and reduced shoot or root Fe levels to a sim-
ilar extent that remained above critical deficiency
levels, each metal elicited a different set of Fe
deficiency-related responses. Among all tested metals,
Figure 9. Fe deficiency response scheme highlighting the relative im-
pact of individual heavy metals on Fe deficiency-induced processes in
Arabidopsis. The ranking of metals along the geometrical forms repre-
sents their degree of interference with Fe deficiency responses at the
shoot or root physiological, morphological, or transcriptional level.
Details are described in the text.
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excess Zn supply mimicked Fe deficiency the most, as
expressed by a strong induction of the Fe-dependent
regulatory gene network and its related downstream
physiological as well as early morphological responses
in roots (Fig. 9). Thus, an impaired balance between Fe
and Zn appears to be perceived as Fe deficiency at the
regulatory level, where the sensing of systemic Fe de-
ficiency takes place. Co, Ni, or Cd evoke selective or
transient responses resembling those of Fe deficiency.
Although high Ni up-regulates the expression of a
limited number of Fe-related transcription factors, this
induction is sufficient for a pronounced physiological
response in roots (Fig. 9). The effect of Co and, to a lesser
extent, Ni is characterized by an early and transient
stimulation of root physiological processes, likely due
to a lack of induction of the ethylene-dependent re-
sponse pathway. Both Ni and Co increase lateral root
density and, thus, affect root morphology in a dissimilar
way to Fe deficiency. This differential effect strongly
argues in favor of an uncoupled interference of these
metals on Fe deficiency responses at the physiological
and morphological levels. Although Cd-induced leaf
symptoms resemble Fe deficiency, Cd induces rather
inconsistent changes in Fe-related physiological, mor-
phological, or molecular responses in roots, which may
be due to negative Cd-Fe interactions at a lower hierar-
chic level (e.g. during transport or metabolism). Among
all tested metals, Mn is the weakest inducer of regulatory
and physiological responses typical for Fe deficiency in
wild-type plants (Fig. 9). However, Mn intensifies Fe
deficiency responses if specific transporters are lacking,
such as IRT1 or MTP8. Thus, we conclude that the in-
duction of Fe deficiency responses by the investigated
heavy metals takes place at different regulatory and
mechanistic levels and that metal-induced physiological
and morphological processes mimicking Fe deficiency
are uncoupled.
MATERIALS AND METHODS
Plant Material and Growth Conditions
The accession line Col-0 of Arabidopsis (Arabidopsis thaliana) was used in this
study unless indicated otherwise. The irt1 mutant (Col-0 background) has been
characterized by Varotto et al. (2002). Seeds were surface sterilized with 70%
(v/v) ethanol and 0.05% (v/v) Triton X-100. The seeds were sown on preculture
medium consisting of one-half-strength MS medium (Murashige and Skoog,
1962) with 75 mMFe-EDTA, 0.5% (w/v) Suc, and 1% Difco agar (Becton Dick-
inson). The pH of the medium was kept at 5.5 by adding 2.5 mMMES buffer
adjusted to pH 5.5. The agar plates containing the seeds were kept for 48 h in
4°C. Afterward, the plates were placed vertically inside growth cabinets and
precultured under a regime of 10 h of light (120 mmol m22s21, 22°C ) and 14 h of
dark (19°C) for 7 d. Seedlings were then transferred to fresh agar plates of
different composition depending on the experiment. Control plants were cul-
tivated under one-half-strength MS conditions with 75 mMFe(III)-EDTA, unless
stated otherwise, whereas Fe deficiency was obtained as indicated. In some
cases, Fe deficiency was induced by supplying no Fe plus 50 mMferrozine [3-(2-
pyridyl)-5,6-diphenyl-1,2,4-triazine sulfonate; Serva]. Heavy metals were
added to one-half-strength MS medium as ZnSO4O$7H2O, CoCl2O$6H2O,
NiSO4
$6H2O, CdCl2
$H2O, or MnSO4
$H2O salts to obtain the concentrations
indicated in the figure legends. For experiments with foliar Fe supply, Fe was
provided as ammonium ferric citrate. In these experiments, the agar was sep-
arated horizontally into two segments and shoots were placed on the top
segment to avoid diffusion of the foliar supplied Fe solution into the bottom,
root-containing segment.
RSA and PCA
After 10 d of cultivation on treatments, plants were scanned with an Epson
Expression 10000XL scanner (Seiko Epson) at a resolution of 300 dots per inch
using settings described by Gruber et al. (2013). Primary root lengths, total
lateral root lengths, and lateral root numbers from 30 to 40 plants per treatment
were analyzed using WinRhizo Pro version 2009c (Reagent Instrument). Av-
erage lateral root length was calculated by dividing the total length of lateral
roots by the numberof lateral roots. The density of the lateralroots was calculated
by dividing the number of lateral roots by the length of the primary root.
PCA was performed on independent root traits, namely primary root
length, average lateral root length, and lateral root density, from all treatments.
Prior to analysis, root trait data were normalized using a modified z-score
normalization algorithm (Gruber et al., 2013):
~
X¼X-m1=2MS control treatment
s1=2MS control treatment=sallcontrols þmallcontrols
where m1/2MS control treatment and s1/2MS control treatment are the observed mean and SD
of the control one-half-strength MS treatment in any given experiment and
sall controls and ma ll contro ls are the global mean and SD calculated from the
control one-half-strength MS treatments across all experiments.
The normalized root trait values were used as input data for PCA performed
with the R package ADE-4 (Thioulouse et al., 1997). For better visibility, the
distribution of control treatments is magnified in Supplemental Figure S7. The
first two components, which explained 93% of the total variability in RSA, were
correlated with the normalized root trait data, and coefficients of determination
were calculated.
The statistical significance among treatments was tested with Student’sttest
or Tukey’s test for two-group and ANOVA-based multiple group comparisons,
respectively. The statistical tests were undertaken with SigmaPlot version 11.0
(Systat Software).
Chlorophyll and Element Analyses
Depending on the experiment, whole shoots were harvested or old and young
leaves were collected separately before weighing. Chlorophyll was extracted by
incubating whole shoots in N,N9-dimethylformamide (Merck) for 48 h at 4°C.
The absorbance of the extract was measured at 647 and 664 nm, and total
chlorophyll concentrations were calculated using the formula described by
Moran (1982).
The removal of metals from the root apoplast was achieved by washing roots
as described previously (Cailliatte et al., 2010; Zhai et al., 2014). Briefly, roots
were washed in 2 mMCaSO4and 10 mMEDTA for 10 min followed by washing
in a solution containing 0.3 mMbathophenanthroline disulfonate and 5.7 mM
sodium dithionite for 3 min. Roots were then rinsed three times with deionized
water.
Root and shoot samples were dried at 65°C and digested with HNO3in
polytetrafluoroethylene tubes and in a pressurized system (UltraCLAVE IV;
MLS). Elemental analysis of whole shoots was performed by inductively cou-
pled plasma-optical emission spectrometry (iCAP 6500 Dual OES Spectrometer;
Thermo Fisher Scientific), whereas young leaves, old leaves, and roots were ana-
lyzed by sector field high-resolution inductively coupled plasma-mass spectrom-
etry (ELEMENT 2; Thermo Fisher Scie ntific).In both cases, element standards we re
prepared from certified reference materials from CPI International.
Ferric-Chelate Reductase Activity and Detection of
Fluorescent Compounds in Roots
Root ferric-chelate reductase activity was determined by placing the roots of
plants previously cultivated for 3, 6, or 9 d on treatments into a mixture of 0.1 mM
Fe(III)-EDTA, 0.2 mMCaSO4,5mMMES, pH 5.5, and 0.2 mMferrozine (Waters
et al., 2006). The formation of pink coloration, indicative for Fe(II)-ferrozine
complexes, was monitored over time. The reaction was stopped after 90 to
120 min, plants were removed from the solution, and roots were cut and
weighed. An aliquot of the stained solution was removed, and the absorbance
was measured at 562 nm. The concentration of Fe(II)-ferrozine complexes was
calculated using 28.6 mmol dm23cm21as molar extinction coefficient (Yi and
Guerinot, 1996).
Plant Physiol. Vol. 174, 2017 1665
Heavy Metal-Induced Iron Deficiency
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Prior to fluorescence visualization, plants were exposed to UV radiation at
365 nm using a 20-ms exposure time. The emitted root and agar fluorescence was
captured by the fluorescence imaging system Quantum ST4 (Vilber Lourmat)
equipped with a 440-nm filter (F-440M58). Root fluorescence measurements
were taken from equal lengths of the subapical parts of the roots, where most of
the fluorescence accumulated. Agar fluorescence measurements were recorded
from equal areas and distances from the roots, and average pixel intensities were
used as relative quantification units of fluorescence. For background correction,
average pixel intensities of the empty bottom parts of the agar were used. Image
analysis was undertaken by ImageJ software.
Gene Expression and Cluster Analyses
Total RNA of the roots was extracted using the Trizol method (Invitrogen)
according to the manufacturer’s instructions. Samples were treated with DNase
to remove all potential DNA contamination. cDNA was synthesized by reverse
transcription of the RNA using the RevertAid First Strand cDNA Synthesis Kit
of Fermentas and oligo(dT) primer. Mastercycler epgradient S realplex2(Eppendorf)
was used to carry out quantitative real-time PCR on cDNA templates and iQ
SYBR Green Supermix (Bio-Rad Laboratories) mixture. Three reference genes,
namely UBQ2,SAND family protein,andF-Box protein, previously used in Fe
deficiency- or heavy metal-related studies, were tested for gene expression
stability (Remans et al., 2008; Schmid et al., 2014). Gene expression stability was
inspec ted with RefFinder (http://150.216.56.64/refe rencegene.php), a Web-based
tool that integrates the currently available major computational programs
(geNorm, Normfinder, BestKeeper, and the comparative ΔCtmethod) to com-
pare and rank the tested reference genes (Llanos et al., 2015). UBQ2 showed the
highest stability; therefore, this reference gene was used in all expression
analyses to normalize gene expression levels of the target genes (Supplemental
Fig. S6). Gene expression levels were expressed as fold changes from control
one-half-strength MS treatment using the following equation (Pfaffl, 2004):
Fold change ¼EDCttarget geneðcontrol-sampleÞ
target gene
EDCtreference geneðcontrol-sampleÞ
reference gene
where Eis gene amplification efficiency derived from the standard curve and Ct
is cycle threshold. All primers used in the quantitative real-time PCR are listed
in Supplemental Table S3.
Fold change values were log2transformed in order to correct for hetero-
scedasticity in the data set (van den Berg et al., 2006). These transformed values
then served as input data for hierarchical cluster analysis of treatments con-
ducted for each time point separately. Cluster analysis was performed with R
software using Ward’s method and Euclidean distance.
Supplemental Data
The following supplemental materials are available.
Supplemental Figure S1. Effects of strongly elevated Mn supply on leaf
symptoms and shoot fresh weight.
Supplemental Figure S2. Metal concentrations in young and old leaves of
Arabidopsis (Col-0).
Supplemental Figure S3. Metal concentrations in roots of Arabidopsis
(Col-0) plants.
Supplemental Figure S4. Impact of the Fe source on the development of
heavy metal-induced Fe deficiency responses.
Supplemental Figure S5. Effects of foliar Fe supply on shoot metal con-
centrations in Col-0 and irt1 plants.
Supplemental Figure S6. Distribution of Ctvalues of reference genes
tested for expression stability.
Supplemental Figure S7. PCA of the variation in RSA traits in control
treatments for all heavy metal treatments.
Supplemental Table S1. Relative proportions of individual Fe species in
metal-supplemented cultivation medium.
Supplemental Table S2. Effects of low Fe and high heavy metal supply on
transcript levels of genes involved in Fe deficiency-related responses.
Supplemental Table S3. List of primers used in the study.
ACKNOWLEDGMENTS
We thank Susanne Reiner and Yudelsy A. Tandron Moya for excellent
technical assistance with elemental analysis.
Received December 19, 2016; accepted May 4, 2017; published May 12, 2017.
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***
0
2
4
6
8
10
12
Control 2000 µM Mn
Shoot FW (mg.plant
-1
)
Control 2000
µM Mn
Supplemental Figure S1. The effect of highly elevated Mn supply on leaf appearance
a
nd shoot fresh weight. Seedlings were pre-cultured for 7 days in ½ MS medium an
d
t
hen transferred to ½ MS medium (control) or ½ MS supplemented with 2000 µM o
f
M
n for another 9 days. Bars represent means ± SD. Asterisks indicate statis
s
ignificant differences from control treatment according to Student’s t-tes p
<
0
.001).
tically
t (***

0
0.5
1.0
1.5
2.0
2.5
control -Fe ++Zn ++Co ++Ni ++Cd ++Mn
Fe ratio between
old and young leaves
A
C
AB
BB
AB
A
a
e
bc
d
cd d
ab
0
30
60
90
120
150
180
control -Fe ++Zn ++Co ++Ni ++Cd ++Mn
Shoot Fe concentration
(µg g-1 DW)
old young
C
B
A
CCCC
c
b
a
cccc
0
500
1000
1500
2000
2500
control -Fe ++Zn ++Co ++Ni ++Cd ++Mn
Shoot Zn concentration
(µg g-1 DW)
n.d. n.d. n .d n.d. n.d. n.d.
0
100
200
300
400
control -Fe ++Zn ++Co ++Ni ++Cd ++Mn
Shoot Cd concentration
(µg g-1 DW)
n.d. n.d. n.d. n.d. n.d. n.d.
0
100
200
300
400
500
control -Fe ++Zn ++Co ++Ni ++Cd ++Mn
Shoot Co concentration
(µg g-1 DW)
n.d. n.d. n.d. n.d. n.d. n.d.
0
50
100
150
200
250
300
control -Fe ++Zn ++Co ++Ni ++Cd ++Mn
Shoot Ni concentration
(µg g-1 DW)
BBBBBB
A
cbcccc
a
0
1000
2000
3000
4000
5000
control -Fe ++Zn ++Co ++Ni ++Cd ++Mn
Shoot Mn concentration
(µg g-1 DW)
AB
CD
EF
G
n.s.
Supplemental Figure S2. Metal concentrations in young and old leaves of A. thaliana
(
Col-0) plants grown on various concentrations of heavy metals. Seven day-ol
d
s
eedlings grown on ½ MS were transferred to ½ MS medium with Fe (control) o
r
w
ithout Fe + 50 μM ferrozine (-Fe) or with Fe and supplemented with 225 μM Z
n
(
++Zn), 90 μM Co (++Co), 100 μM Ni (++Ni), 20 μM Cd (++Cd) or 1500 μM Mn (++Mn)
.
A
fter 9 days, the four oldest rosette leaves were collected separately from th
e
r
emaining leaves (young leaves) and analyzed by ICP-MS. Bars represent means
±
S
EM (n = 5-6). Different uppercase or lowercase letters indicate statistically significan
t
d
ifferences according to Tukey‘s test (p < 0.05) among means in old or young leaves
,
r
espectively. n.s., not significant according to one-way ANOVA (p = 0.794); n.d., no
t
d
etected.

a
e
c
b
d
bc
c
0
200
400
600
800
1000
control -Fe ++Zn ++Co ++Ni ++Cd ++Mn
Root Fe concentration
(µg g-1 DW)
c
b
a
dcd d
b
0
100
200
300
400
500
control -Fe ++Zn ++Co ++Ni ++Cd ++Mn
Root Zn concentration
(µg g-1 DW)
c
b
cccc
a
0
30
60
90
120
150
180
control -Fe ++Zn ++Co ++Ni ++Cd ++Mn
Root Mn concentration
(µg g-1 DW)
n.d. n.d. n.d. n.d. n.d. n.d.
0
30
60
90
120
150
control -Fe ++Zn ++Co ++Ni ++Cd ++Mn
Root Cd concentration
(µg g-1 DW)
n.d. n.d. n.d. n.d. n.d. n.d.
0
20
40
60
80
100
120
140
control -Fe ++Zn ++Co ++Ni ++Cd ++Mn
Root Co concentration
(µg g-1 DW)
n.d. n.d. n.d. n.d. n.d. n.d.
0
20
40
60
80
100
120
control -Fe ++Zn ++Co ++Ni ++Cd ++Mn
Root Ni concentration
µg g-1
DW)
AB
CD
EF
Supplemental Figure S3. Metal concentrations in roots of A. thaliana (Col-0) plants
g
rown on various concentrations of heavy metals. Seven day-old seedlings grown o
n
½
MS were transferred to ½ MS medium with Fe (control) or without Fe + 50 μ
M
f
errozine (-Fe) or with Fe and supplemented with 225 μM Zn (++Zn), 90 μM Co (++Co)
,
1
00 μM Ni (++Ni), 20 μM Cd (++Cd) or 1500 μM Mn (++Mn). After 9 days, apoplasti
c
F
e was removed from roots, and roots were subjected to mineral analysis. Bar
s
r
epresent means ± SEM (n = 5-6). Different letters indicate statistically significan
t
d
ifferences according to Tukey’s test (p < 0.05), n.d., not detected.

0
0.10
0.20
0.30
0.40
0.50
0.60
0.70
Chlorophyll concentration
(μg mg-1 FW)
Fe-EDTA
Fe-EDDHA
½ MS
150 Zn
100 Ni
+Fe-EDDHA+Fe-EDTA
0
0.10
0.20
0.30
0.40
0.50
0.60
0.70
Chlorophyll concentrations
(μg mg
-1
FW)
A
C
½ MS 150 Zn 100 Ni
0
20
40
60
80
100
120
140
Shoot Fe concentrations
(µg g-1 DW)
Fe-EDTA
Fe-EDDHA
½ MS 150 Zn 100 Ni
B
n.s.
n.s.
n.s.
*
n.s.
n.s.
Supplemental Figure S4. Impact of the Fe source on the development of heavy metal-
i
nduced Fe deficiency responses. (A) Shoot phenotype, (B) chlorophyll and (C) F
e
c
oncentrations of the shoots. Seedlings were pre-cultured for 7 days in ½ MS mediu
m
a
nd then transferred to ½ MS containing either 75 μM Fe-EDTA or 75 μM Fe-EDDH
A
a
nd supplied or not with 150 μM Zn or 100 μM Ni.

n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
0
50
100
150
200
250
300
control ++Zn ++Ni ++Mn
Shoot Ni concentration
(µg g -1 DW)
0
50
100
150
200
250
300
control ++Zn ++Ni ++Mn
Shoot Fe concentration
(µg g -1 DW)
Col-0 mock
irt1 mock
0
200
400
600
800
1000
1200
1400
1600
control ++Zn ++Ni ++Mn
Shoot Zn concentration
(µg g -1 DW)
Col-0 mock
Col-0 shoot Fe
irt1 mock
irt1 shoot Fe
0
1000
2000
3000
4000
5000
6000
control ++Zn ++Ni ++Mn
Shoot Mn concentration
(µg g -1 DW)
AB
CD
Supplemental Figure S5. Effect of foliar Fe supply on shoot metal concentrations in
C
ol-0 and irt1 plants. Seven day-old seedlings grown on ½ MS were transferred to
½
M
S containing elevated concentrations of the indicated heavy metals. Leaves wer
e
s
upplied or not with Fe citrate (250 μM). Shoot concentrations of (A) Fe, (B) Zn, (C
)
N
i, and (D) Mn of plants cultivated for 8 days under the indicated conditions. ++Zn
,
2
25 μM Zn; ++Ni, 100 μM Ni; ++Mn, 1500 μM Mn; mock, water. Bars represent mean
s
±
SD. Since plants with foliar Fe supply received Fe directly onto their leaves, shoo
t
F
e levels were extremely high in these plants and are not presented in (A). n.d. = no
t
d
etectable.

UBQ2 F-BOX protein SAND family protein
18
20
22
24
26
28
30
32
***
*
**
Ctvalues
Supplemental Figure S6. Distribution of C
t
values of reference genes tested for
e
xpression stability. The C
t
values are gathered from control and various heavy meta
l
t
reatments from different time points. The lower and upper boundaries of the box mar
k
t
he 25
th
and 75
th
percentile, respectively. The line within the box indicates the media
n
o
f the dataset’s distribution, while the whiskers below and above the box correspon
d
t
o the 10
th
and 90
th
percentile, respectively, and the outliers are represented by th
e
c
ircles outside the whiskers. Asterisks denote gene expression stability according t
o
R
efFinder’s recommended comprehensive ranking (* average, ** good, *** better).

S
upplemental Figure S7. PCA of the variation in root system architectural traits i
n
c
ontrol treatments for all heavy metal treatments.

Supplemental Table S1. Relative proportion of individual Fe species in
metal-supplemented cultivation media. Percent values were calculated
using Visual MINTEQ simulation (Gustaffson, 2012). Bold fonts indicate
Fe(III)-EDTA complexes.
Treatment
Fe species
% of total concentration
½ MS
Fe(OH)
2+
0.262
FeHPO
4+
0.118
FeEDTA
-
98.842
FeOHEDTA
-2
0.761
150 µM Zn
FeOH
+2
0.023
Fe(OH)
2+
0.856
FeHPO
4+
0.385
FeEDTA
-
97.969
FeOHEDTA
-2
0.758
110 µM Co
FeOH
+2
0.021
Fe(OH)
2+
0.771
FeHPO
4+
0.348
FeEDTA
-
98.094
FeOHEDTA
-2
0.757
100 µM Ni
FeOH
+2
0.199
Fe(OH)
2+
7.296
FeHPO
4+
3.274
FeEDTA
-
88.537
FeOHEDTA
-2
0.684
40 µM Cd
FeOH
+2
0.013
Fe(OH)
2+
0.47
FeHPO
4+
0.212
FeEDTA
-
98.537
FeOHEDTA
-2
0.759
1500 µM Mn
Fe(OH)
2+
0.292
FeHPO
4+
0.127
FeEDTA
-
98.779
FeOHEDTA
-2
0.784

Genes
Time points
0 150 225 90 110 5 20 100 150 1250 1500
MYB72 3d 1751.3*** 347.9 *** 572.2 *** 53.5 *** 65.0 *** 16.1 *** 11.4 *** 10.1 ** 15.1 *** 4.1 * 4.4 *
6d 378.7 *** 37.2 *** 65.7 *** 45.0 *** 49.1 *** 11.3 *** 8.4 *** 10.2 *** 36.4 *** 3.2 * 9.3 *
9d 59.2 *** 24.1 ** 27.6 *** 8.1 * 5.1 * 3.2 * 2.3 * 2.9 * 4.7 ** 1.2
n.s.
2.1 n.s.
bHLH100 3d 946.1 *** 147.6 *** 227.0 *** 164.7 *** 82.0 *** 11.7 ** 13.0 ** 44.9 *** 124.5 *** 13.6 ** 17.0 ***
6d 508.7 *** 47.9 *** 42.9 *** 39.2 ** 40.1 *** 32.8 *** 30.3 *** 8.9 ** 45.4 *** 2.2 * 3.9 **
9d 28.3 *** 18.7 ** 27.0 *** 5.3 * 6.1 * 3.5 * 3.8 * 1.4
n.s.
5.6 *** 0.2 * 0.3 *
bHLH39 3d 27.9 *** 9.9 *** 11.4 *** 6.5 *** 3.6 ** 5.5 ** 4.3 * 3.5 ** 3.1 ** 3.8 *** 2.8 **
6d 37.5 *** 7.4 *** 11.6 *** 4.3 *** 4.5 ** 10.5 *** 11.9 *** 1.4
n.s.
4.0 ** 1.6
n.s.
2.8 *
9d 18.3 *** 12.8 *** 11.9 *** 8.0 *** 4.1 * 7.1 ** 5.6 ** 1.6
n.s.
2.6 * 1.0
n.s.
1.7 n.s.
bHLH38 3d 56.5 *** 31.3 *** 39.7 *** 18.0 *** 14.5 *** 6.4 *** 5.1 *** 6.4 ** 9.2 *** 5.4 ** 7.3 **
6d 86.9 *** 18.4 *** 26.1 *** 8.6 *** 10.1 *** 15.5 *** 18.4 *** 3.9 * 10.3 *** 3.3 * 4.4 **
9d 25.6 ** 17.5 *** 15.0 ** 2.9 ** 4.9 ** 6.4 ** 6.0 * 2.5 * 4.0 ** 0.7
n.s.
1.2 n.s.
bHLH101 3d 55.1 *** 20.6 *** 31.8 *** 13.3 *** 14.0 *** 4.0 *** 5.0 *** 4.5 * 5.0 ** 3.1 * 3.8 *
6d 176.1 *** 33.3 *** 55.7 *** 18.2 ** 22.9 ** 18.7 *** 33.1 *** 3.9 ** 8.8 ** 5.6 ** 8.5 **
9d 68.4 *** 23.7 ** 27.5 *** 12.0 *** 8.6 ** 11.6 *** 15.2 *** 2.7 * 3.5 * 2.5 * 4.8 **
IRT1 3d 24.7 *** 9.1 *** 10.7 *** 13.5 *** 15.9 *** 3.7 ** 2.5 * 7.1 *** 5.8 *** 2.6 ** 3.6 *
6d 10.8 *** 4.6 *** 5.1 ** 2.8 *** 1.8 ** 3.6 ** 2.4 * 1.5
n.s.
2.0 *** 0.7
n.s.
1.3 n.s.
9d 3.6 * 4.4 ** 4.1 ** 1.1
n.s.
1.1
n.s.
1.6
n.s.
1.2
n.s.
1.1
n.s.
0.9
n.s.
1.5
n.s.
1.9 *
FRO2 3d 38.6 *** 20.8 *** 30.4 *** 22.8 *** 30.2 *** 6.6 * 4.3 *** 10.3 *** 6.8 *** 3.2 * 3.9 *
6d 12.9 *** 5.4 ** 6.7 ** 3.1 ** 2.6 * 3.1 * 2.5 * 0.9
n.s.
1.6
n.s.
0.5
n.s.
1.3 n.s.
9d 4.6 * 9.9 ** 4.6 ** 1.9
n.s.
1.4 * 2.0
n.s.
1.0
n.s.
1.1
n.s.
1.1
n.s.
0.9
n.s.
1.8 n.s.
FRO3 3d 7.0 *** 4.8 *** 8.4 *** 6.9 *** 7.9 *** 3.9 ** 2.6 * 3.8 ** 3.4 * 2.1 * 2.4 *
6d 12.7 *** 5.3 *** 7.5 *** 3.8 *** 3.2 *** 5.6 *** 4.1 *** 1.3
n.s.
3.3 *** 1.5
n.s.
1.6 *
9d 4.7 ** 5.5 * 3.2 * 1.2
n.s.
1.2
n.s.
2.3 * 2.4 *** 1.1
n.s.
1.5 * 0.6 * 0.9 n.s.
PYE 3d 6.8 *** 2.3 * 2.9 ** 2.8 * 3.4 ** 1.4
n.s.
1.6
n.s.
1.6 * 1.8 * 2.7 *** 2.4 **
6d 4.9 *** 2.5 *** 3.2 *** 2.0 ** 1.9 ** 2.1 ** 1.8 * 1.0
n.s.
1.6 ** 1.5 * 1.6 *
9d 3.5 * 4.7 ** 4.6 ** 1.8 ** 2.0 ** 2.0 * 2.1 * 1.4 * 1.6 ** 1.4 * 1.7 **
BTS 3d 3.9 * 2.4 * 2.3 * 1.3 1.4 1.1 1.1 1.0 0.7 1.0 1.3
6d 5.8 ** 2.2 * 2.6 * 1.7 * 2.0 * 2.7 * 3.2 * 0.9 1.7 * 1.0 1.5 *
9d 3.2 * 2.3 * 2.9 * 1.5 1.5 * 1.9 * 1.8 * 1.1 * 1.3 * 0.8 1.2
NAS4 3d 15.7 ** 2.9 3.9 * 3.1
n.s.
2.7
n.s.
1.8
n.s.
2.0
n.s.
1.0
n.s.
1.2
n.s.
2.1
n.s.
2.2 n.s
.
6d 8.8 *** 2.4 *** 3.0 ** 4.0 *** 3.6 *** 3.1 *** 4.1 *** 0.8
n.s.
2.5 *** 1.4
n.s.
1.8 **
9d 2.9 ** 3.5 * 3.0 ** 3.9 *** 4.5 ** 2.2 * 3.5 ** 1.4
n.s.
2.8 * 1.0
n.s.
0.8 n.s
.
FIT 3d 2.3 * 2.0 * 2.1 * 2.0 * 1.8 * 1.4
n.s.
1.2
n.s.
1.4
n.s.
1.0
n.s.
1.6
n.s.
1.5 n.s
.
6d 4.0 *** 2.6 ** 2.6 ** 1.2
n.s.
1.1
n.s.
2.1 ** 2.3 ** 0.9
n.s.
0.7
n.s.
1.2
n.s.
1.5 *
9d 2.8 * 2.8 ** 3.3 ** 0.7
n.s.
0.9
n.s.
1.6
n.s.
1.4
n.s.
0.7
n.s.
1.0
n.s.
1.2
n.s.
1.6 *
F6'H1 3d 3.3 * 2.1 * 2.2 * 2.5 ** 3.9 ** 1.4
n.s.
1.2
n.s.
1.7 ** 1.9 ** 1.4
n.s.
1.2 n.s
.
6d 5.4 * 2.3 ** 2.5 *** 1.6 * 1.6 * 1.4
n.s.
1.7 * 1.2
n.s.
1.4
n.s.
0.9
n.s.
1.0 n.s
.
9d 2.9 * 2.5 * 2.2 * 0.7
n.s.
0.9
n.s.
1.4
n.s.
1.3
n.s.
0.9
n.s.
0.9
n.s.
0.5 * 0.4 *
IDF1 3d 1.8 * 1.1
n.s.
1.6 * 1.4
n.s.
1.4
n.s.
1.6
n.s.
1.2
n.s.
2.4 *** 2.2 *** 1.3
n.s.
1.1 n.s
.
6d 1.8 * 1.5 * 1.8 * 1.4
n.s.
1.3
n.s.
1.1
n.s.
1.9 * 1.0
n.s.
2.3 *** 1.3
n.s.
1.1 n.s
.
9d 2.5 * 1.4
n.s.
1.7
n.s.
0.7
n.s.
1.0
n.s.
1.2
n.s.
0.9
n.s.
1.0
n.s.
1.6
n.s.
1.0
n.s.
1.0 n.s
.
EIL1 3d 1.3
n.s.
1.1
n.s.
1.4
n.s.
0.9
n.s.
0.8
n.s.
1.1
n.s.
0.9
n.s.
0.9
n.s.
0.7 * 1.0
n.s.
0.8 n.s
.
6d 2.2 * 1.6 * 1.8 * 1.1
n.s.
1.1
n.s.
1.6 * 2.2 * 1.1
n.s.
1.2
n.s.
1.1
n.s.
1.2 n.s
.
9d 2.3 ** 1.5
n.s.
1.6
n.s.
0.8
n.s.
1.0
n.s.
1.3
n.s.
1.4
n.s.
0.9
n.s.
0.9
n.s.
1.0
n.s.
1.3 n.s
.
EIN3 3d 1.3
n.s.
1.0
n.s.
1.3
n.s.
1.0
n.s.
1.0
n.s.
0.9
n.s.
0.9
n.s.
0.9
n.s.
0.8
n.s.
1.1
n.s.
1.1 n.s
.
6d 1.8 *** 1.6 * 1.7 * 1.4
n.s.
1.4
n.s.
1.5 ** 2.2 ** 1.1
n.s.
1.1
n.s.
1.5 * 1.8 *
9d 2.5 ** 1.5
n.s.
1.5
n.s.
0.9
n.s.
0.9
n.s.
1.1
n.s.
1.1
n.s.
0.8
n.s.
0.9
n.s.
1.2
n.s.
1.6 *
FRD3 3d 2.2 * 1.0
n.s.
0.8
n.s.
1.1
n.s.
1.1
n.s.
1.1
n.s.
0.8
n.s.
0.9
n.s.
1.1
n.s.
0.7
n.s.
0.9 n.s
.
6d 2.8 ** 1.4
n.s.
1.4
n.s.
1.3
n.s.
1.4
n.s.
0.9
n.s.
1.0
n.s.
0.7
n.s.
1.2
n.s.
0.8
n.s.
0.7 n.s
.
9d 0.9
n.s.
0.7
n.s.
0.7
n.s.
0.7
n.s.
0.9
n.s.
0.4 ** 0.6 ** 0.5 ** 0.9
n.s.
0.4 *** 0.5 **
FER1 3d 0.1 *** 0.2 ** 0.2 *** 0.4 *** 0.3 *** 0.5 * 0.3 ** 0.9
n.s.
1.1
n.s.
0.6 ** 0.5 *
6d 0.1 *** 0.2 * 0.2 ** 0.2 ** 0.2 ** 0.3 ** 0.3 ** 0.6 * 0.4 * 0.6
n.s.
0.6 *
9d 0.3 ** 0.3 * 0.2 * 0.1 ** 0.1 * 0.3 * 0.2 ** 0.7 * 0.4 * 0.7
n.s.
0.4 **
Supplemental Table S2. Effect of 0 Fe and high heavy metal supply on expression of genes involved in Fe deficiency -related responses.
Values represent fold changes f rom control ½ MS treatment. Asterisks indicate statistically significant diff erence f rom control ½ MS
treatment according to Tukey’s test (* p < 0.05; ** p < 0.01, *** p < 0.001).
Fold c hanges
Fe (µ
M)
Zn (µM)
Co (µM)
Cd (µM)
Ni (µM)
Mn (µM)
n.s.
n.s.
n.s. n.s. n.s.
n.s.
n.s. n.s.
n.s.
n.s.
n.s.n.s.
n.s.

Supplemental Table S3. List of primers used in this study
AGI ID Gene name Primer
AT2G36170 UBQ2 5'-CCAAGATCCAGGACAAAGAAGGA-3'
5'-TGGAGACGAGCATAACACTTG-3'
AT2G28390 SAND family protein 5'-AACTCTATGCAGCATTTGATCCACT-3'
5'-TGATTGCATATCTTTATCGCCATC-3'
AT5G15710 F-box protein 5'-TTTCGGCTGAGAGGTTCGAGT-3'
5'-GATTCCAAGACGTAAAGCAGATCAA-3'
AT1G56430 NAS4 5'-GCTTCGGATCTCGCGTGTAA-3'
5'-CACCTGCGAACTCCTCGATAA-3'
AT1G23020 FRO3 5'-TTCTTCCGACCTCTCAATGC-3'
5'-TTTCTCTCGGGTGACAAAGG-3'
AT2G28160 FIT1 5'-GCGGTATCAATCCTCCTGCT-3'
5'-GATGGAGCAACACCTTCTCCT-3'
AT3G13610 F6’H1 5’-TGATATCTGCAGGAATGAAACG-3'
5’-GGGTAGTAGTTAAGGTTGACTC-3'
AT4G19690 IRT1 5'-CGGTTGGACTTCTAAATGC-3'
5'-CGATAATCGACATTCCACCG-3'
AT3G56970 BHLH38 5'-AGCAGCAACCAAAGGCG-3'
5'-CCACTTGAAGATGCAAAGTGTAG-3'
AT3G56980 BHLH39 5'-GACGGTTTCTCGAAGCTTG-3'
5'-GGTGGCTGCTTAACGTAACAT-3'
AT2G41240 BHLH100 5'-AAGTCAGAGGAAGGGGTTACA-3'
5'-GATGCATAGAGTAAAAGAGTCGCT-3'
AT5G04150 BHLH101 5'-CAGCTGAGAAACAAAGCAATG-3'
5'-CAGTCTCACTTTGCAATCTCC-3'
AT3G47640 PYE 5'-CAGGACTTCCCATTTTCCAA-3'
5'-CTTGTGTCTGGGGATCAGGT-3'
AT3G18290 BTS 5'-CCAGCACTTGGCGAAAGAAC-3'
5'-GCAAGGGGTAGCACCTGAAT-3'
AT3G20770 EIN3 5'-TGTCTGGTGGAAGTTGCTCG-3'
5'-ATTCCGAGTTTCCTGCTGGG-3'
AT2G27050 EIL1 5'-GCAGGATAAGATGACGGCGA-3'
5'-CCGAGCCACAACCTCTTCTT-3'
AT3G08040 FRD3 5'-GTTATCTTCAAAGATTTAAGACATGTATTC-3'
5'-CTCTGCCACAAATGAAGTTGT-3'
AT4G30370 IDF1 5'-CGCCGTCACGAATACTCAGAT-3'
5'-TCCGTACTCTGAACTAGGCTCACA-3'
AT1G01580 FRO2 5'-GCGACTTGTAGTGCGGCTATG-3'
5'-CGTTGCACGAGCGATTCTG-3'
AT5G01600 FER1 5'-AATCCCGCTCTGTCTCC-3'
5'-AAACTTCTCAGCATGCCC-3'
AT1G56160 MYB72 5'-TCATGATCTGCTTTTGTGCTTTG-3'
5'-ACGAGATCAAAAACGTGTGGAAC-3'