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ORIGINAL ARTICLE
Plant growth-promoting bacteria (PGPBs) and copper (II) oxide (CuO)
nanoparticle ameliorates DNA damage and DNA Methylation in wheat
(Triticum aestivum L.) exposed to NaCl stress
Arash Hosseinpour
1,2
•Emre Ilhan
3
•Gu¨ller O
¨zkan
1
•Halil I
˙brahim O
¨ztu¨rk
4
•Kamil Haliloglu
1
•
Kag
˘an Tolga Cinisli
5
Received: 13 May 2020 / Accepted: 15 September 2021
ÓThe Author(s), under exclusive licence to Society for Plant Biochemistry and Biotechnology 2021
Abstract
Wheat is the second important cereal crop worldwide due to nutritional composition and role in meeting daily energy
needs. Salinity is an abiotic stress factor that restricts crop productivity through influencing plant growth and development
in arid and semi-arid regions. Nanomaterials and plant growth promoting bacteria (PGPBs) can be used in many different
areas of agriculture for different purposes. In this study, changes in cytosine methylation and DNA damage levels in wheat
(Triticum aestivum L.) exposed to salt stress (250 mM NaCl) were determined and possible preventive effects of copper
(II) oxide nanoparticles (0, 50 and 100 mg/L; CuO-Nps [100 nm) and plant growth promoting bacteria (no bacteria,
Bacillus subtilis,Lactobacillus casei,Bacillus pumilis; PGPBs) treatments were investigated. Changes in cytosine
methylation were analyzed by Coupled Restriction Enzyme Digestion-iPBS (CRED-iPBS) and genotoxic influences and
genomic stability was analyzed with the aid of inter-primer binding site (iPBS) primers. Application of 250 mM NaCl
remarkably increased polymorphism rate of iPBS profile. Besides, relieve effect of PGPBs with CuO-NPs was observed
against adverse effect of 250 mM NaCl stress. The genomic template stability values clearly increased with PGPBs with
CuO-NPs treatments, particularly Lactobacillus casei with 100 mg/L of CuO-Nps. In addition, DNA hypo-methylation was
observed in all treatments. As a conclusion, PGPBs with CuO-NPs treatments showed a strong anti-genotoxic effect against
NaCl stress and they could be used as an alternative molecule to alleviate genetic impairment in wheat under NaCl stress.
Keywords DNA methylation Genomic instability PGPBs Salt stress CuO-Nps
Abbreviations
PGPBs Plant growth-promoting bacteria
PCR Polymerase chain reaction
CuO Copper (II) oxide
NP Nanoparticle
CRED Coupled Restriction Enzyme Digestion
iPBS Inter-primer binding site
GTS Genomic template stability
&Emre Ilhan
emre.ilhan@erzurum.edu.tr
Arash Hosseinpour
arash8643@gmail.com
Gu
¨ller O
¨zkan
gullerozzkan@gmail.com
Halil I
˙brahim O
¨ztu
¨rk
hiozturk@erzincan.edu.tr
Kamil Haliloglu
kamilh@atauni.edu.tr
Kag
˘an Tolga Cinisli
kagantolgacinisli2525@gmail.com
1
Department of Field Crops, Faculty of Agriculture, Ataturk
University, 25240 Erzurum, Turkey
2
Crop and Horticultural Science Research Department, Ardabil
Agricultural and Natural Resources Research and Education
Center, AREEO, Ardabil, Moghan, Iran
3
Department of Molecular Biology and Genetics, Faculty of
Science, Erzurum Technical University, 25050 Erzurum,
Turkey
4
Health Services Vocational School, Erzincan Binali Yıldırım
University, Erzincan, Turkey
5
Department of Soil Science and Plant Nutrition, Faculty of
Agriculture, Ataturk University, 25240 Erzurum, Turkey
123
Journal of Plant Biochemistry and Biotechnology
https://doi.org/10.1007/s13562-021-00713-w(0123456789().,-volV)(0123456789().,-volV)
Introduction
Wheat (Triticum aestivum L.) is one of the major grains
feeding about 20% of the world population. Wheat yields
significantly influenced by salinity. Soil salinity is an
important abiotic stress that limits crop growth and pro-
ductivity (Abbas et al. 2018). Salinity causes an imbalance
of the cellular ions resulting in ion toxicity and osmotic
stress, leading to the generation of reactive oxygen species
(ROS). ROS alter cellular metabolism leading to lipid
peroxidation, protein denaturing, and DNA mutation
(Davenport et al. 2003; Imlay 2003). DNA methylation can
be related to epigenetic regulation in response to abiotic
stressors, such as water deficit, high-salinity, and temper-
ature shifts (Kim et al. 2015).
Wheat is a culture crop that is highly affected by
salinity. Therefore, the development of wheat germplasm
by conventional breeding or modern biotechnological
methods is extremely important for wheat production (Ri-
naldi et al. 2011). Some recent technologies such as the
progress of nano-appliance and nanomaterials have been
presented to resolve these agricultural problems (Nair et al.
2010). Wheat cells need Cu as an essential micronutrient,
and there are some methods available to increase plant Cu
uptake. Copper (Cu) is an essential element for photosyn-
thetic electron transport in chloroplasts (Maksymiec 1998).
In addition, Copper is essential for photosynthesis, plant
respiration and enzyme systems that utilize metabolism of
carbohydrate and proteins and is a component of some
enzymes and structure of cell wall which are involved in
lignin synthesis. Cu also is involved in imparting flavor and
color in leaves and flowers (Yruela 2005; Brinate et al.
2015; Printz et al. 2016).
CuO-NPs are extremely small particles which provides
them with a physical resistance, chemical reactivity, elec-
trical conductivity, magnetism, and optical effects used in a
diverse range of industries (McManus et al. 2018). There
are several reports about the interactions between salinity
and CuO-NP
S
in higher plants but sufficient information
are not available about the possible positive effects of
CuO-NPs on salt-induced damages. Additionally, there are
some other strategies such as plant genetic engineering
(Wang et al. 2007) and use of plant growth-promoting
bacteria (PGPBs) (Dimkpa et al. 2009) in order to alleviate
plant stress caused by salinity (Fu et al. 2010; Shilev et al.
2012; Yao et al. 2010). There are many methods for
determining the genotoxic effects of toxic substances such
as using comet assay, chromosome aberration assays and
micronucleus assay (Murali Achary and Panda 2009).
However, these methods have limitations in respect to
sensitivity and ability in detection. More sensitive and
selective DNA analysis methods have been developed with
the advent of molecular marker technology. There are dif-
ferent molecular markers to determine polymorphism and
iPBS can be employed effectively for determination of dif-
ferent toxicity in plants (Hosseinpour et al. 2019). Poly-
merase chain reaction (PCR) based inter-primer binding site
(iPBS) amplification is based on the essential presence of a
tRNA complement as a reverse transcriptase primer-binding
site (PBS) in long terminal region (LTR) retrotransposon s. In
particular, the iPBS amplification technique has been
demonstrated to be a notable DNA fingerprinting technology
not requiring sequence data. The use of the iPBS marker is an
easy and rapid method for monitoring the changes in the
DNA profile of plants (Nemli et al. 2015). Coupled
Restriction Enzyme Digestion (CRED) involving the pro-
filing of DNA with molecular markers is a technique used to
determine the changes in cytosine methylation in plant
genome (Hosseinpour et al. 2020). CRED has been suc-
cessfully used for determination of cytosine methylation in
plant genome or toxicity caused by abiotic stresses such as
salinity and heavy metal (Demirkiran et al. 2013; Saleh 2016;
Taspinar et al. 2017; Zhang et al. 2014; Erturk et al. 2015a,b;
Erturk et al. 2014a; Erturk et al. 2014a,b; Erturk et al. 2015b;
Hossein-Pour et al. 2018).
Present literature reviews revealed that there aren’t any
reports showing a protective effect of CuO-NPs and PGPBs
against NaCl toxicity. In addition, the CRED-iPBS method
was employed to identify DNA methylation status by iPBS
markers. The objectives of this work were directed towards
understanding whether CuO-NPs and PGPBs have any
protective effect on genomic instability and DNA methy-
lation of wheat under NaCl stress.
Materials and methods
Plant material and growth conditions
Wheat (Triticum aestivum L. cv ‘‘Kirik’’) seeds were
obtained from the Department of Field crops, Faculty of
Agriculture, Ataturk University (Erzurum, Turkey).
Seed germination and treatments
Wheat seeds were grown in plastic boxes containing quartz
sand and peat moss (1: 3) mix. After 14 days of germina-
tion, five seedlings were transplanted into pots containing
quartz sand and peat moss (1: 3) mix. Salt stress was
induced in plants by application of 20 ml of 250 mM
sodium chloride (NaCl) to each pot for three times in a
week. Control plants were grown without any salt solutions
and any PGPBs with various concentration of CuO-Nps.
Experiments were conducted in completely randomized—
Journal of Plant Biochemistry and Biotechnology
123
factorial experimental design with four replications. The
first factor was application of four different plant growth
promoting bacteria (PGPBs) which were 1) no bacteria 2)
Bacillus subtilis (1 910
9
cfu/ml), 3) Lactobacillus casei
(1 910
9
cfu/ml) and 4) Bacillus pumilis (1 910
9
cfu/ml)
and the second factor was application of three different
concentrations [0 (control: distilled water), 50 and 100 mg/
l] of copper (II) oxide nanoparticles. CuO-NPs obtained
from Sigma-Aldrich were dissolved in deionized water.
There were also control plants (no salt stress and no
application of PGPBs and CuO-Nps) and only salt-stressed
plants (only 250 mM NaCl applied and no application of
PGPBs and CuO-Nps). Application of CuO-NPs with
PGPBs was performed in the rhizosphere area of plants in
pots by injection (20 ml) twice a week. All plants were
grown in a greenhouse under a day/night cycle of 16/8 h
natural light, 25/18 °C temperature and 60/70% relative
humidity. Fresh leaves were collected prior to the flowering
stage and stored at -80 °C temperature to be used for fur-
ther experiments.
Phenotypic assay
Wheat seeds were sown in plastic boxes containing quartz
sand and peat moss (1: 3) mix. After 14 days of germina-
tion, five seedlings were transferred to pots containing
quartz sand and peat moss (1: 3) mix. Salt stress in plants
were induced by application of 20 ml of 250 mM sodium
chloride (NaCl) to each pots for three times in a week.
Control plants were grown without any salt solution and
any PGPBs with various concentration of CuO-Nps. This
study was conducted as factorial experiment with com-
pletely randomized design of four replications. In the
study, 3 different species of bacteria [1-no bacteria,2-
Bacillus subtilis (1 9109 cfu/ml), 3-Lactobacillus casei
(1 9109 cfu/ml) and 4-Bacillus pumilis (1 9109 cfu/m)]
and 3 different concentrations [0 (control: distilled water),
50 and 100 mg/l] of copper (II) oxide nanoparticles were
used. CuO-NPs obtained from Sigma-Aldrich were dis-
solved in deionized water. Also, control plants (no salt
stress and PGPBs and CuO-Nps application) and plants
only exposed to salt stress (only 250 mM NaCl applied)
were included in the study to compare with bacteria, salt
and CuO-Nps application. Application of CuO-NPs with
PGPBs was performed into rhizosphere area of plants in
pot by injection (20 ml) twice a week. All plants were
grown in a greenhouse under a day/night cycle of 16/8 h
natural light, 25/18 °C and 60/70% relative humidity. To
measure phenotypic data, number of leaves (NL), Leaf
fresh weight (LFW) (g/plant), leaf dry weight (LDW)
(g/plant), stem fresh weight (SFW) (g/plant), stem dry
weight (SDW) (g/plant), spike length (SL) (cm), 100 Grain
weight (HGW) (g) and Grain yield (GY) (g/plant) were
measured using a ruler and precision scales. Fresh leaves
were collected prior to the flowering stage and stored at
-80 °C until further analysis.
Genotype assessment
Isolation of genomic DNA
Genomic DNA was extracted following Zeinalzadehtabrizi
et al. (2015). Concentration and quality of genomic DNA
was determined using Nanodrop spectrophotometer
(Thermo Fisher Scientific) and by electrophoresis of the
DNA on a 1.5% agarose gel.
iPBS and CRED-iPBS PCR assays
Twenty-two primers were tested for iPBS-PCR amplifica-
tion (Kalendar et al. 2010). For iPBS analysis, PCR reac-
tion was carried out in a total volume of 20 ll PCR mix
containing 10 X PCR buffer, 25 mM MgCl
2
, 10 mM dNTP
mix, ddH
2
O, 10 pmol random primer, 1 U Taq DNA
polymerase and 50 ng/ml sample DNA. After vortexing,
tubes were placed in a thermocycler (Sensoquest GmbH,
Labcycler Gradient, Germany) for amplification. PCR steps
consisted of 5 min of pre-denaturation step at 95 °C, fol-
lowed by 40 cycles of 1 min for denaturing at 95 °C, 1 min
for annealing at 51–56 °C, 2 min for extension at 72 °C,
subsequently 10 min final primer extension at 72 °C, then
dropped to 4 °C. Out of 22 primers, only 10 iPBS
oligonucleotide primers resulted in specific and
stable DNA profiles in all three wheat cultivars (Table 1).
For CRED-iPBS analysis, 1 mg of sample DNAs from
each treatment were separately digested with 1 lL (1 FDU)
HpaII and 1 lL (1 FDU) MspI (Thermo Scientific)
endonucleases at 37 °C for 2 h according to manufacturer’s
guidelines. Digested DNA (for each endonuclease) was
added in PCR mix instead of nondigested gDNA. The
primers listed in Table 1were employed for amplification.
PCR steps were the same as iPBS analysis described above.
Electrophoresis
The iPBSs and CRED-iPBS PCR products were separated
with 1.5% agarose gel containing 0.05 ml/ml ethidium
bromide in electrophoresis using in 1X SB buffer in 100 V
for 90 min. Then, 100–1000 bp (Sigma Aldrich No:
P1473-1VL) DNA ladder was used to estimate the
molecular weight of the fragments. The gels were pho-
tographed under UV light in a Universal Hood II (Bio-Rad,
Hercules, CA, USA).
Journal of Plant Biochemistry and Biotechnology
123
Analysis
Statistical analysis
Analysis of variance (ANOVA) was performed using the
general linear model (GLM) procedure in SPSS version 20
(SPSS. Chicago, USA). Each pot was considered as an
experimental unit. In each pot, three plants were selected to
measure of all characters. Means treatments were com-
pared using Fisher’s Duncan test.
Genetics analysis
The iPBS and CRED-iPBS banding patterns were analyzed
using TotalLab TL120 software (Nonlinear Dynamics
Ltd
R
). Polymorphism in the iPBS profiles was expressed as
the disappearance of a normal band and the appearance of a
new band as compared to the control. The average poly-
morphism was calculated for each experimental group (salt
treatment with CuO-NPs and PGPBs applications) and
changes in these values were calculated as a percentage of
their value in the control (set to 100%) (Hossein-Pour et al.
2018). The genomic template stability (GTS %) which is a
quantitative measurement was calculated for iPBS with the
following formula: GTS = 1 a
n
100; where ais the
average number of polymorphic bands found in each
treated template, and nis the number of total bands in the
control (Sigmaz et al. 2015; Hosseinpour et al. 2019).
For the CRED–iPBS analysis, the average values of
polymorphism (%) were calculated for each concentration
using the formula, 100 9a/n.
Results
Statistical analysis
Variance analysis on experimental data shown that there
were significant differences in FLW, PH, SD, LFW, LDW,
RFW and RDW (P \0.01) (Table 2). The highest mean
FLW, PH, SD, LFW, LDW, RFW and RDW were obtained
in salinity stress ?lactobacillus Casei ?40 mg
-1
CuO-
NPs (12.33 number, 31.09 g/plant, 12.60 g/plant,
5.66 g/plant, 5.00 g/plant and 10.33 g/plant, 4.02 g/plant
and 30.54 g/plant respectively) and the lowest mean values
were showed in 250 mM NaCl stress (5.33 number,
18.23 g/plant, 6.89 g/plant, 3.30 g/plant, 2.33 g/plant and
6.00 g/plant, 2.63 g/plant and 17.98 g/plant, respectively).
Although Salinity stress ?Bacillus subtilis ?0mg
-1
CuO-NPs) application reduces salt stress, some morpho-
logical features ((LFW (g/plant), DW (g/plant), SFW
(g/plant), SDW (g)/plant), HGW (g/plant)] was found to be
lower than the control group. In addition, all applications
provided an increase in grain yield (g/plant) compared to
both salt stress (250 mM NaCl) and the control group.
According to the data obtained, the most effective bacteria
species to reduce the effect of salt stress are Lactobacillus
casei, Bacillus pumilus and Bacillus subtilis, respectively.
The use of Lactobacillus casei and Bacillus pumilus toge-
ther with increasing CuO-NPs doses had a more positive
effect on the morphological parameters in plants (Table 2).
Genetics analysis
iPBS analysis
The iPBS analysis was achieved to determine the effects of
co-application of PGPBs with CuO-NPs treatments on
wheat gDNA. Twenty-two iPBS primers were used in
iPBS-PCR reactions. In the iPBS procedure, only 10 pri-
mers yielded sufficient polymorphism, specific and
stable band profiles in all treatments (Table 1).
As shown in Table 2, total 73 bands were seen in the
control treatment and the greatest number of bands was
achieved with iPBS-2388 (9 bands) while the lowest
number bands were achieved with iPBS-2387 and iPBS-
2392 (6 bands). The molecular sizes of polymorphic bands
ranged from 100 (iPBS-2278) to 655 (iPBS-2375) bp.
Table 1 Reactive primers used
in iPBS -PCR and their
annealing (Ta) temperatures
No Primer name Sequence (5’–3’) Tm (°C) CG (%) Optimal annealing, Ta (°C)
1 2077 CTCACGATGCCA 46.1 58.3 55.1
2 2276 ACCTCTGATACCA 42.7 46.2 51.7
3 2278 GCTCATGATACCA 42.3 46.2 51.0
4 2375 TCGCATCAACCA 45.1 50.0 52.5
5 2384 GTAATGGGTCCA 40.9 50.0 50.0
6 2387 GCGCAATACCCA 47.3 58.3 51.5
7 2388 TTGGAAGACCCA 43.4 50.0 51.0
8 2390 GCAACAACCCCA 47.6 58.3 56.4
9 2392 TAGATGGTGCCA 43.1 50.0 52.2
10 2393 TACGGTACGCCA 47.1 58.3 51.0
Journal of Plant Biochemistry and Biotechnology
123
There were significant differences in iPBS profiles in
control, 250 mM NaCl treatment and PGPBs with CuO-
NPs treatments as well. These differences were formed as
appearance ( ?) or disappearance (–) of the bands (as
shown ±in Table 3and Fig. 1a). As compared to control,
total 150 new bands were appeared while 93 bands were
disappeared in experimental groups.
The polymorphism rate was detected as 43.83% for
250 mM NaCl stress. Each PGPBs with different concen-
tration of CuO-NPs gave different responses to the poly-
morphism rate showing increase in the polymorphism rate
with higher concentrations of CuO-Nps. Enhancement
effect of PGPBs with CuO-NPs against NaCl stress on
polymorphism were proved with polymorphism rates of
39.72%, 30.13%, 28.76% for Bacillus Pumilus with 0, 50
and 100 mg/L CuO-NPs application respectively. Treat-
ment of Lactobacillus Casei as PGPBs with 0, 50 and
100 mg/L CuO-NPs application enhanced the polymor-
phism rate as 38.35%, 32.87% and 24.65%, respectively. In
addition, treatment of Bacillus Subtilis with 0, 50 and
100 mg/L CuO-NPs treatments resulted in also
enhancement of polymorphism rate as 39.72%, 30.13% and
26.02%, respectively. In addition, the different concentra-
tion of CuO-NPs gave different response for the GTS
value. There was a clear increase in the GTS value with the
increasing concentration of CuO-NPs in all PGPBs appli-
cations. GTS values varied among experimental groups.
The lowest GTS value (56.16%) was observed in 250 mM
NaCl stress. There were obvious increases in GTS values in
treatments of PGPBs with CuO-NPs as compare to
250 mM NaCl treatment. GTS values were determined as
60.27%, 69.86%, 71.23% for Bacillus Pumilus with 0, 50
and 100 mg/L CuO-NPs application, while 61.64%,
67.12% and 73.97% in Lactobacillus Casei with 0, 50
and100 mg/L CuO-NPs application, and 60.27%, 69.86%
and 75.34% in Bacillus Subtilis with 0, 50 and100 mg/L
CuO-NPs application, respectively. The results strongly
showed that application of all PGPBs with100 mg/L CuO-
NPs (particularly Lactobacillus Casei with 100 mg/L CuO-
NPs treatments) had an enhancement effect against
250 mM NaCl stress in wheat (Table 3).
Table 2 Mean comparison of different studied traits after application of different PGPB and CuO-NPs concentrations in the wheat under salinity
stress conditions
Experimental groups NL
1
LFW
(g/plant)
LDW
(g/plant)
SFW
(g/plant)
SDW
(g/plant)
SL
(cm)
HGW
(g/plant)
GY
(g/plant)
Control 7.66
d2
25.16
ef
10.69
e
4.36
bc
3.33
cd
7.66
c
3.65
bc
22.20
f
250 mM NaCl 5.33
e
18.23
g
6.89
f
3.30
d
2.33
d
6.00
d
2.63
f
17.98
g
Salinity stress ?Bacillus pumilus ?0
mgl
–1
CuO-NPs
8.33
cd
26.89
cd
10.75
cde
4.66
bc
4.33
abc
8.66
b
3.10
e
24.18
d
Salinity stress ?Bacillus pumilus ?20
mgl
–1
CuO-NPs
9.00
c
27.18
c
11.05
cde
5.00
ab
4.60
ab
9.00
b
3.50
cd
24.80
d
Salinity stress ?Bacillus pumilus ?40
mgl
–1
CuO-NPs
10.33
b
28.97
b
11.50
bcd
5.33
ab
4.72
ab
9.33
ab
3.80
abc
26.49
c
Salinity stress ?Lactobacillus casei ?0
mgl
–1
CuO-NPs
10.66
b
29.03
b
11.62
bc
4.33
bc
4.33
abc
9.00
b
3.96
ab
27.64
c
Salinity stress ?Lactobacillus casei ?20
mgl
–1
CuO-NPs
11.33
ab
29.83
b
11.96
b
5.33
ab
5.00
a
9.66
ab
3.99
a
29.10
b
Salinity stress ?Lactobacillus casei ?40
mgl
–1
CuO-NPs
12.33
a
31.09
a
12.60
a
5.66
a
5.00
a
10.33
a
4.02
a
30.54
Salinity stress ?Bacillus subtilis ?0
mgl
–1
CuO-NPs
8.00
cd
24.18
f
10.41
e
4.00
c
3.33
cd
8.66
b
3.10
e
23.25
ef
Salinity stress ?Bacillus subtilis ?20
mgl
–1
CuO-NPs
8.66
cd
24.14
f
10.51
e
4.33
bc
3.66
bc
9.00
b
3.30
de
23.15
ef
Salinity stress ?Bacillus subtilis ?40
mgl
–1
CuO-NPs
9.00
c
25.97
ef
11.59
bcd
4.66
c
4.66
ab
9.33
ab
3.70
bc
23.34
ef
F value 26.61
**3
98.02
**
28.20
**
5.00
**
4.73
**
12.82
**
19.47
**
68.36
**
1
NL: Number of leaves, LFW Leaf fresh weight (g/plant), LDW Leaf dry weight (g/plant), SFW Stem fresh weight (g/plant), SDW Stem dry
weight (g/plant), SL Spike length (cm), HGW 100 Grain weight (g/plant) and Grain yield (g/plant)
2
Similar letters in each column shows non- significant difference according to Duncan multiple range tests at 1% level (this explanation states
what the letters mean.)
3
Means indicated with different letters are significantly different at (pB0.01) (this explanation indicates what the ‘‘**’’ symbol means.)
Journal of Plant Biochemistry and Biotechnology
123
Table 3 Molecular sizes (bp) of appeared/disappeared bands in iPBS profiles of application of different PGPBs and CuO- NPs treated wheat under the salt stress of NaCl
iPBS Primer ±Control Experimental groups
250 mM
NaCl
250 mM NaCl ?Bacillus pumilus 250 mM NaCl ?Lactobacillus casei 250 mM NaCl ?Bacillus subtilis
0 mg/L
CuO-NPs
50 mg/L
CuO-NPs
100 mg/L
CuO-NPs
0 mg/L
CuO-NPs
50 mg/L
CuO-NPs
100 mg/L
CuO-NPs
0 mg/L
CuO-NPs
50 mg/L
CuO-NPs
100 mg/L
CuO-NPs
2077 ?8 – 269; 211 326; 280 428; 391; 298;
185
– 528 – 285; 205;
125
250; 205;
160
214
– 345 – 296; 125 580 125 150 – – – –
2276 ?7 539; 425 350; 225 454 518; 183 314; 288 395; 281;
203
530; 350; 128 420; 217 605;550 512
– 250 120 250; 120 300 380; 250 400; 250 380 400; 300 480; 250 400; 300
2278 ?8 372; 250 350; 185 165 – 520 335 470; 320; 115 605; 495 585; 420 –
– 320; 292 328; 291 – – – 100 – 451 – 315
2375 ?7 655 520 648 415; 153 471; 309;
205
384; 205 520 588; 128 320 140
– 250; 180 128 112 385 312; 112 115 – 128 260 –
2384 ?8 535; 320 432; 380 452 452 288; 220 520 – 450 320 –
– 380 160 385 305 – 318 – 185 – 132
2387 ?6 524; 216 320 224; 165 – 350 324 316; 118 526; 435;
146
– 505; 402
– 295; 260 525; 150 186 – 180 405 486 – 486 –
2388 ?9 630; 350;
175
650 465; 350 – 580; 275 335 587 530; 480;
332
565; 190 525; 480
– 320 – – 580 587 565 665 175 – –
2390 ?7 352; 255;
365
452 – 350; 230 340; 280 – – 274 – 112
– 280 330; 150 – – 472 – 515 – 440; 250 –
2392 ?6 337 417; 292;
185
583; 305 427 525; 400 600; 580 480; 270 450 325 400; 320
– 500; 205 500 284; 125 320 185 – – 633; 596 596 500
2393 ?7 625 350; 230 – 520; 357 350; 270 414; 256 406; 320 330; 207 411; 300 417
– 590; 482 255; 120 315 – 230; 120 215; 156 130 320 160 220; 156
Total band 73 32 29 22 21 28 24 19 29 22 18
Polymorphism
(%)
43.83 39.72 30.13 28.76 38.35 32.87 26.02 39.72 30.13 24.65
GTS value 56.16 60.27 69.86 71.23 61.64 67.12 73.97 60.27 69.86 75.34
The meaning of the bold values are given at the beginning of the line. These values are average values and are in bold for attention
Journal of Plant Biochemistry and Biotechnology
123
a
1;100-1000 bp DNA ladder, 2; Control, 3; 250 mM NaCl, 4; Salinity stress + Bacillus pumilus+0mgl
–1 CuO-NPs, 5; Salinity stress
+Bacillus pumilus+20 mgl
–1 CuO-NPs, 6; Salinity stress + Bacillus pumilus+40 mgl
–1 CuO-NPs, 7; Salinity stress + Lactobacillus
Casei +0mgl
–1 CuO-NPs, 8; Salinity stress + La ctobacillus Casei +20mgl
–1 CuO-NPs, 9; Salinity stress + Lactobacillus Casei +
40 mgl–1 CuO-NPs, 10; Salinity stress + Bacillus subtilis+ 0 mgl–1 CuO-NPs, 11; Salinity stress + Bacillus subtilis + 20 mgl–1 CuO-
NPs, 12; Salinity stress + Bacillus subtilis+ 40 mgl–1 CuO-NPs.
b
1;100-1000 bp DNA ladder, 2; Control Hpa II, 3; Control Msp I, 4; 250 mM NaCl Hpa II, 5; 250 mM NaCl Msp I, 6; Salinity stress
+ Bacillus pumilus+0mgl
–1 CuO-NPs Hpa II, 7; Salinity stress + Bacillus pumilus +0mgl
–1 CuO-NPs Msp I, 8; Salinity stress +
Bacillus pumilus+20mgl
–1 CuO-NPs Hpa II, 9; Salinity stress + Bacillus pumilus+20mgl
–1 CuO-NPs Msp I, 10; Salinity stress +
Bacillus pumilus+ 40 mgl–1 CuO-NPs Hpa II, 11; Salinity stress + Bacillus pumilus+40 mgl
–1 CuO-NPs Msp I, 12; Salinity stress +
Lactobacillus casei +0mgl
–1 CuO-NPs Hpa II, 13; Salinity stress+ Lactobacillus casei + 0 mgl–1 CuO-NPs Msp I, 14; Salinity stress
+Lactobacillus casei +20mgl
–1 CuO-NPs Hpa II, 15; Salinity stress + Lactobacillus casei+ 20 mgl–1 CuO-NPs Msp I, 16; Salinity
stress+ Lactobacillus casei +40mgl
–1 CuO-NPs Hpa II, 17; Salinity stress + Lactobacillus casei +40mgl
–1 CuO-NPs Msp I, 18;
Salinity stress + Bacillus subtilis +0 mgl
–1 CuO-NPs Hpa II, 19; Salinity stress + Bacillus subtilis +0mgl
–1 CuO-NPs Msp I, 20;
Salinity stress + Bacillus subtilis +20 mgl
–1 CuO-NPs Hpa II, 21; Salinity stress + Bacillus subtilis+20mgl
–1 CuO-NPs Msp I, 22;
Salinity stress+ Bacillus subtilis+ 40 mgl–1 CuO-NPs Hpa II, 23; Salinity stress + Bacillus subtilis +40 mgl
–1 CuO-NPs Msp I.
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Fig. 1 (a) iPBS and (b) CRED-iPBS profiles for various experimental groups with iPBS-2276 primers in wheat
Journal of Plant Biochemistry and Biotechnology
123
Table 4 Results of CRED-iPBS analysis; molecular size of bands and polymorphism percentage
iPBS Primer M*/
H*
±Control Experimental groups
250 mM
NaCl
250 mM NaCl ?Bacillus pumilus 250 mM NaCl ?Lactobacillus casei 250 mM NaCl ?Bacillus subtilis
0 mg/L
CuO-NPs
50 mg/L CuO-
NP
100 mg/L
CuO-NP
0 mg/L
CuO-NPs
50 mg/L
CuO-NP
100 mg/L
CuO-NP
0 mg/L
CuO-NPs
50 mg/L
CuO-NP
100 mg/L
CuO-NP
2077 M ?7 350 – – 225 380; 258;
160
– 600; 480 450; 358;
105
180 450; 320;
125
– 180 – – – 305 – – 590; 350 450;390 320
H?6 350; 220 – 405 180 280;170 380 580; 380 – – –
– 320 180 190 300; 215;
125
452; 320 225 290 – 350; 285 –
2276 M ?8 375;
280;180
350; 252;
105
(800)750; 400;
250(200)
450; 350 820; 690;
520
500; 385 – 385; 285;
200
350; 184 500; 480;
320
– – 750;
475(450)
315 405; 320 250 250;
150;100
150 532; 450 755 –
H19 – – 250; 180 – – 320; 250;
125
500; 250;
300
430; 340;
205
800; 100 –
– 450 750; 620 450 450; 305 405 – 400; 360 – – 702; 500;
401
2278 M ?7 622; 328;
225
750; 450 620; 405; 170 378; 195 478; 354 495; 130 520 375; 209 550; 214 375
– 400; 226 502; 420 495; 322; 250 – 514; 467 514; 460 305 395; 120 515; 402;
295; 162
–
H?6 565; 404;
103
375; 209 582; 456; 325;
200
400; 158 425; 382 500 – 450 – 779; 625;
375;
– 515; 349;
250
474; 345 302 350 570; 510 390; 375 490; 205;
105
579; 414 679; 614;
553; 509
130
2375 M ?8 760; 576 454; 247 463; 304 350 523; 400 459; 216;
150
280; 210 504; 485 316; 20; 105 3436; 225;
112
– 408 – 565;; 284 300; 260 332; 120 33; 232 320: 228 332 539 454; 400;
110
H?7 – 520; 402 428 342 – – – 340 356 –
– 525; 350;
112
254 384 384 445; 300 384; 100 168; 284;
135
345; 284;
320
410 620
2384 M ?10 524; 357 180 533; 167 430; 386 331; 298 430; 326 531; 415 403; 351 – –
– 280; 165 535; 420 545 27; 257 – – – – – 320; 250
H?11 426; 304 323 – 230 229 362; 260 408; 400 487;220;
178
438; 350 254
– 290 320; 354 – 2450 325; 260 43; 320 205 228 – 316
Journal of Plant Biochemistry and Biotechnology
123
Table 4 (continued)
iPBS Primer M*/
H*
±Control Experimental groups
250 mM
NaCl
250 mM NaCl ?Bacillus pumilus 250 mM NaCl ?Lactobacillus casei 250 mM NaCl ?Bacillus subtilis
0 mg/L
CuO-NPs
50 mg/L CuO-
NP
100 mg/L
CuO-NP
0 mg/L
CuO-NPs
50 mg/L
CuO-NP
100 mg/L
CuO-NP
0 mg/L
CuO-NPs
50 mg/L
CuO-NP
100 mg/L
CuO-NP
2387 M ?8 750; 560;
440
420; 386;
358
480 433; 315;
175
344; 260 380; 322;
150
423; 244 354; 280 330; 280 650
– 612; 480;
270
365 330 552; 332 490 480 – 260 542; 416 424
H?9 580; 240 350; 200 290 520; 458;
262; 130
462 302; 236 453; 330 663; 513;
415
554; 407 260
– 180 100 413 284; 163 513; 384;
250
– 232 340 232; 130 323
2388 M ?5 529; 402 650; 520;
400; 130
350; 280; 233 568; 440;
320
602; 580;
206
504; 364 641; 474;
270
655; 502;
180
433; 347;
239
709; 652
– 475; 327 500; 268 560; 440 569; 375 449; 307;
250
615; 280 300 324; 227 547; 350 349; 125
H?6 603; 554;
121
657; 455 750;516; 480 569; 417 439 706 366 646; 448;
320
679; 450 641; 427
– 250; 130 351 360; 254 539; 425 522; 360 360; 420;
315
239 439; 378 485; 422 339
2390 M ?8 662; 550 350; 228 572; 350; 250 552; 323;
154
360; 270;
125
310; 120 462 558; 505;
350
206; 256 316
– 727; 480;
310; 130
602; 560 180; 120 157; 120 650; 250 650 300 394 362; 307 529
H?9 770; 541;
219; 250
395; 221;
202
412; 310; 250 479; 322 459; 470;
125
728 129 242 300; 218;
150
436
– 549; 216;
120
689; 588;
490
620; 450 260 350 165 – 476 428 323
2392 M ?7 587; 315;
100
850; 380;
325; 281
610; 560 700; 507 583; 330;
200; 125
625; 350;
140
600; 400;
281
708; 574;
350
580 602; 574
– 442; 250 350 480; 364; 280 138 423; 150 250 250; 164 450 557; 562 480; 360
H?6 541; 314; 587; 500;
400
150 319; 181 576; 243;
120
150 300; 160 508; 245 458 503
– 378; 180 150 170; 150 – 750; 652;
312
214 610; 264;
202
650 720; 600;
450
281
2393 M ?8 585; 235;
125
520; 326;
254
604; 500; 481; 250 717; 587 500; 450;
320
317; 125 580; 520;
361
478; 330;
250
780; 580
– 522; 204;
100
423 144 487; 144 320 228 244; 106 542; 223;
144
323; 244 –
Journal of Plant Biochemistry and Biotechnology
123
CRED-iPBS analysis
Among 22 iPBS primers, 10 of them produced specific and
stable bands and were used for the CRED-iPBS analysis
(Table 4). CRED-iPBS analysis enabled to observe any
possible cytosine methylation caused by 250 mM NaCl
stress and enhancement in cytosine methylation due to
treatments of PGPBs with CuO-Nps. The results of the
CRED-iPBS analysis as the average polymorphism per-
centage in respect to HpaII and MspI digestions to deter-
mine cytosine methylation for experimental group are
presented in Table 4and Fig. 1b. Total 76 and 78 bands
were observed in MspI and HpaII digested control treat-
ment, respectively.
According to the results of CRED-iPBS pattern, MspI
polymorphism percentage was found to be higher than
HpaII polymorphism percentage in application 250 mM
NaCl stress as well as PGPBs with CuO-NPs treatments.
While 59.14% MspI polymorphism percentage was
observed in 250 mM NaCl stress, they decreased and
ranged between 39.11 and 57.75% in application of PGPBs
with different concentration of CuO-Nps. In terms of
polymorphism percentage of HpaII digestion, it was
54.79% in 250 mM NaCl salt application and it decreased
and ranged from 29.36% to 49.47% in application of
PGPBs with different concentration of CuO-NPs treat-
ments under 250 mM NaCl stress (Table 4). In general, it
was found that 250 mM NaCl treatment gave rise to higher
polymorphism percentage in both MspI and HpaII digested
CRED-iPBS assay. Contrarily, application of PGPBs with
different concentration of CuO-NPs treatments under
250 mM NaCl stress caused the decreases in both HpaII
and MspI polymorphisms percentage. In other words, the
results indicated that the tested 250 mM NaCl treatment
had an impact on cytosine methylation status and could be
classified as hyper-methylation when the average poly-
morphism percentage for MspI digestion was taken into
consideration. When different PGPBs with various con-
centration of CuO-NPs were applied with 250 mM NaCl,
clear decrease in average polymorphism percentage and
methylation statue was observed, which can be concluded
that PGPBs with various concentration of CuO-NPs had
protective role under stress conditions.
The polymorphism percentage gradually decreased in
applications of PGPB with CuO-NPs treatments as com-
pared to 250 mM NaCl treatment (Table 4). This statue
could be explained as hypo-methylation phenomena.
Table 4 (continued)
iPBS Primer M*/
H*
±Control Experimental groups
250 mM
NaCl
250 mM NaCl ?Bacillus pumilus 250 mM NaCl ?Lactobacillus casei 250 mM NaCl ?Bacillus subtilis
0 mg/L
CuO-NPs
50 mg/L CuO-
NP
100 mg/L
CuO-NP
0 mg/L
CuO-NPs
50 mg/L
CuO-NP
100 mg/L
CuO-NP
0 mg/L
CuO-NPs
50 mg/L
CuO-NP
100 mg/L
CuO-NP
H?9 502; 420;
247
510 762; 600 520; 360 400; 272;
150
340; 170 523; 489;
250
565; 450;
125
266; 125 250; 125
– 570; 254 260 427 435 527; 431 – 250; 127 178; 140 250; 124 328
Polymorphism
%
M59.14 51.61 51.21 48.82 57.75 46.43 39.11 56.82 52.14 41.61
H54.79 41.46 42.30 41.90 49.47 35.94 44.24 43.24 45.23 29.36
The meaning of the bold values are given at the beginning of the line. These values are average values and are in bold for attention
M- Msp I, H- Hpa II, Control (without bacteria and CuO-NPs
Journal of Plant Biochemistry and Biotechnology
123
Discussion
Salinity is one the significant problems in crop production.
High salt stress cause firstly an imbalance of ions in the cell
that results in osmotic stress and ion toxicity, leading to
production of reactive oxygen species (ROS). ROS alter
cell metabolism, which leads to lipid peroxidation, denat-
uration of proteins, and mutation in DNA (Davenport et al.
2003; Imlay 2003). In addition, salt stress affects defor-
mation of nucleus (Katsuhara and Kawasaki 1996). Higher
concentration and long-term use of salt are known to cause
toxic effects in plants. NaCl toxicity induces oxidative
stress and leads to various genotoxic damages (Kumar et al.
2017; Munns and Tester 2008).
There are several reports about the toxicity of CuO-NPs
on plant morphology, germination and quality of produces,
and transpiration and translocation in plant tissues. Recent
studies of CuO-NPs toxicity showed negative impact on
seed germination and plant growth on various crop plants,
i.e., lettuce (Lactuca sativa), alfalfa (Medicago sativa),
wheat (Triticum aestivum), mungbean (Vigna radiate),
kidneybean (Phaseolus vulgaris), maize (Zea mays),
cucumber (Cucumis sativus), cilantro (Coriandrum sati-
vum), rice (Oryza sativa), spinach (Spinacia oleracea),
onion (Allium cepa), mustard (Brassica juncea), tomato
(Solanum lycopersicum), soybean (Glycine max), carrot
(Daucus carota), sweet potato (Ipomoea batatas), barley
(Hordeum vulgare), cotton-chickpea (Cicer arietinum),
radish (Raphanus sativus), and zucchini (Cucurbita pepo).
After accumulation, NPs start to affect plant growth by
lowering the germination rate, decreasing biomass, reduc-
ing the length of roots and shoots, altering the process of
photosynthesis and transpiration rate, and enhancing
chromatin condensation and lipid peroxidation (Shams
et al. 2018; Singh et al. 2017). In this study, morphologic
traits differed among experimental groups. The reason this
may be expression mRNA levels of SOD and GPX genes
under salinity stress and also could be confirmed that a
decrease in mRNA expression. (Wang et al. 2007). In this
study, the application of different PGPB (Bacillus subtilis,
Lactobacillus casei and Bacillus pumilus) and CuO-NPs at
both levels (20 and 40 mg L
-1
) both improved the mor-
phological characteristics of wheat plants under salt stress
and alleviated the negative effects of salinity. According to
the findings, it can be stated that the most effective appli-
cation that both reduces salt stress and increases morpho-
logical properties is the application of Salinity
stress ?Lactobacillus casei ?40 mg-1 CuO-NPs. In a
similar study conducted on tomatoes, it was determined
that the most effective bacteria to reduce salt stress are
Lactobacillus casei, Bacillus pumilus and Bacillus subtilis
species, respectively. In addition, it has been determined
that the most effective ZnO-NPs dose, which has a positive
effect on both reducing salt stress and morphological
properties in tomato seedling, is 40 mg L
-1
. (Hosseinpour
et al. 2020). The findings obtained by the researchers are
similar to the results obtained in our study. It appears that
the presence of combination of CuO-NPs with PGPB under
salinity stress can change the activity of morphological
traits in wheat plants and this could improve the effect of
salinity. Various species of edible plants have been studied
to understand how CuO NPs may impact agriculture.
Phytotoxicity, defined as a distinct response to abiotic
stress experienced by the plant, is evident from Cu based
nanoparticles. The toxicity appears as an oxidative stress,
in some cases inducing DNA damage, and a reduction in
root elongation and morphological change. Oxidative
stress, measured by oxidized Glutathione (Dimkpa et al.
2012), has been found to be symptomatic of CuONPs
toxicity in many species (Atha et al. 2012).
Present findings revealed that 250 mM NaCl treatment
altered genetic template stability and cytosine methylation
in wheat. In addition, it was also found that plants treated
with different PGPBs with various of CuO-NPs concen-
trations in rhizosphere improved significantly molecular
disorders caused by NaCl stress. In this study, two
approaches were combined to alleviate the adverse effects
of salt stress on DNA nanotechnology with the use of
PGPBs. Nowadays, nanotechnology can be efficiently used
in various fields of science at nanometer scale.
The interaction between salinity stress and micronutrient
composition in plants has not yet been well understood;
however, micronutrients are recognized to be more affected
by salinity stress (Fathi et al. 2017). Copper is a very
important micro element for plants. Although plant species
require different amounts of Cu, it is a highly toxic metal
(Michaud et al. 2008). There are mechanisms responsible
for regulating copper uptake of plants. As in every plant
cell, copper is a very important micronutrient substance for
the cells of the wheat plant and its uptake strategies.
Cooper is a key component of chloroplasts and it has
important role in photosynthetic electron transport (Mak-
symiec 1998). Cu is also a co-factor in several enzymes
and their complexes, including superoxide dismutase
(SOD), cytochrome oxidase, amino oxidase, laccase,
plastocyanin and polyphenol oxidase (Marschner 1995). In
addition, copper has an important role in mitochondrial
respiration, oxidative stress responses, cell wall metabo-
lism and hormone signaling (Marschner 1995). Nanopar-
ticles (NPs) are broadly defined as particles having a size of
at least 1 to 100 nm. Due to its many properties, NPs are
used in many fields such as energy sector, catalysts,
semiconductors, cosmetics, pharmaceutics and environ-
mental operations (Yang et al. 2017). CuO NPs in partic-
ular have a strong protective and preventive properties
Journal of Plant Biochemistry and Biotechnology
123
against fungal diseases in leaves (Elmer and White 2016)
or fertilizers (Dimkpa et al. 2017; Monreal et al. 2016), and
may find uses as drought treatments (Dimkpa et al. 2017).
CuO NPs in these applications will inevitably contact soils
through overspray/leaf litter of foliar applications or
intentional application to soil. CuO NPs may also partici-
pate into biosolids in wastewater treatment plants and be
applied to soils as post-biological treatment (Cornelis et al.
2014; Keller et al. 2013). CuO NPs may also stimulate and/
or interact with exudation of organic molecules from the
roots and bacteria. In wheat, sand, water (with a back-
ground salt) and CuO NP systems, the roots increase
exudation of organic compounds, including citrate, malate,
and the phytosiderophore 2’-deoxymugineic acid (DMA)
(McManus 2016). The increased exudation also increase
soluble Cu from the CuO NPs, and thus Cu uptake into the
shoot is positively correlated with increased exudation
(McManus 2016). Bacteria increase solubility of CuO NPs
through similar mechanisms of release of extracellular
polymeric substances (Miao et al. 2016) and possibly iron
siderophores such as pyoverdines, which complex with Cu
(Dimkpa et al. 2017).
PGPBs are microorganisms with positive effects on
plant growth by a variety of mechanisms (Vessey 2003),
which are associated with an increase in availability of
nutrients and fixation of biological nitrogen (BNF) (Gra-
ham and Vance 2000), phosphate solubilization and min-
eralization (Rodrı
´guez et al. 2006) and synthesis of plant
hormones such as indole, gibberellins or cytokinins
(Costacurta and Vanderleyden 1995). Many researchers
reported that use of PGPBs alleviated plant stress caused
by salinity (Fu et al. 2010; Shilev et al. 2012; Yao et al.
2010). Similarly, in present study, PGPBs with CuO-NPs
decreased the adverse effects of salinity stress. In addition,
this study draws different perspective with respect to
minimize the effect of cytosine methylation and improve-
ment in genomic template stability.
It was shown that 250 mM NaCl treatment caused to
decrease the GTS value pointing out that NaCl had geno-
toxic effects on wheat genome based on iPBS profiles. The
iPBS technique is known to be sensitive enough to detect
DNA damages (Citterio et al. 2002). Any changes in iPBS
profiles in relation to profiles obtained from control sam-
ples were stated as reductions in GTS (Aly 2012; Dog
˘an
et al. 2012; Gupta and Sarin 2009; Tanee et al. 2012).
DNA methylation is one of several epigenetic mecha-
nisms that cells use to control gene expression. Plants
under salt stress can reprogram their gene expression
through methylation and demethylation (Peng and Zhang
2009; Zhong and Wang 2007). Methylation makes differ-
ences between normal plants and plants under stress in
terms of iPBS band profiling. In the present study, CRED-
iPBS technique was employed to investigate how the wheat
genome alters its cytosine methylation status in response to
NaCl stress and any enhancements in DNA methylation
statue against to NaCl by using PGPBs with CuO-NPs
treatments. In this respect, the study revealed that the wheat
plants under 250 mM NaCl treatments had significant
changes in cytosine methylation status that has deduced as
hyper-methylation. There are several studies in agreement
with the present findings that abiotic stresses could alter the
cytosine methylation status and cause DNA hyper-methy-
lation such as; zinc stress (Erturk et al. 2015a,b), chro-
mium nitrate (Erturk et al. 2014a,b), arsenic trioxide
(Erturk et al. 2015b), lead sulfate solution (Erturk et al.
2014a) and aluminum chlorite (Hossein-Pour et al. 2018).
Present findings showed that application of PGPBs with
CuO-NPs advanced obviously in cytosine methylation
status that has realized as hypo-methylation under 250 mM
NaCl stress. Generally, hyper-methylation is correlated
with gene silencing but hypo-methylation is associated
with active transcription (Steward et al. 2002).
Conclusion
Wheat plants exposed to salt stress often exhibit pheno-
typic variations caused by epigenetic polymorphisms at the
cytosine methylation level. This is the first report con-
firming protective role of copper (II) oxide (CuO)
nanoparticle and different plant growth promoting bacteria
(PGPBs) against the salt stress of NaCl- exposed DNA
damage and DNA methylation in wheat. Present findings
clearly exhibit the inverse association between cytosine
methylation and NaCl tolerance gained by different PGPBs
with various concentration of CuO-NP. In conclusion,
NaCl has a genotoxic potential and causes DNA methyla-
tion in wheat plants. Application of compounds such as
CuO-NPs and PGPBs in different forms might compensate
for the negative effect of salinity on DNA damage and
cytosine methylation in wheat plants.
Authors’ contributions AH conceived and designed the experiments
and worked for writing and editing of the English of this paper. TC,
EI, GO, HIO and KH performed the experiments, collected and
analyzed the data. EI went through literature and helped in drafting
the manuscript.
Declarations
Conflict of interest The authors declare that they have no conflict of
interest.
Ethical approval This article does not contain any studies with human
participants or animals performed by any of the authors.
Journal of Plant Biochemistry and Biotechnology
123
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