Genome-Scale Transcriptome Analysis in Response to Nitric Oxide in Birch Cells: Implications of the Triterpene Biosynthetic Pathway
Genome-Scale Transcriptome Analysis in Response to Nitric Oxide in Birch Cells: Implications of the Triterpene Biosynthetic Pathway
Fansuo Zeng 0 1 2 3
Fengkun Sun 0 1 3
Leilei Li 0 1 3
Kun Liu 0 1 3
Yaguang Zhan 0 1 2 3
0 Citation: Zeng F , Sun F, Li L, Liu K, Zhan
1 Editor: David D. Roberts, Center for Cancer Research, National Cancer Institute , United States of America
2 State Key Laboratory of Tree Genetics and Breeding (Northeast Forestry University) , Harbin 150040, China,
3 College of Life Science, Northeast Forestry University , Harbin 150040 , China
some cases, controversial. To study the role of NO at the transcriptional level in Betula platyphylla cells, we conducted a genome-scale transcriptome analysis of these cells. The transcriptome of untreated birch cells and those treated by sodium nitroprusside (SNP) were analyzed using the Solexa sequencing. Data were collected by sequencing cDNA libraries of birch cells, which had a long period to adapt to the suspension culture conditions before SNP-treated cells and untreated cells were sampled. Among the 34,100 UniGenes detected, BLASTX search revealed that 20,631 genes showed significant (E-values#1025) sequence similarity with proteins from the NR-database. Numerous expressed sequence tags (i.e., 1374) were identified as differentially expressed between the 12 h SNPtreated cells and control cells samples: 403 up-regulated and 971 down-regulated. From this, we specifically examined a core set of NO-related transcripts. The altered expression levels of several transcripts, as determined by transcriptome analysis, was confirmed by qRT-PCR. The results of transcriptome analysis, gene expression quantification, the content of triterpenoid and activities of defensive enzymes elucidated NO has a significant effect on many processes including Evidence supporting nitric oxide (NO) as a mediator of plant biochemistry continues Funding: This work was financially supported by The Fundamental Research Funds for the Central triterpenoid production, carbohydrate metabolism and cell wall biosynthesis. Universities (NO: 2572014DA04) and the National Natural Science Foundation of China (NO: 31070531, J1210053 and 31200463). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Nitric oxide (NO) is a noxious free radical gas, which in the late 1980s was
discovered to exist physiologically in mammalian systems. Notably, the idea that a
simple gas could act as a messenger revolutionized the understanding of signal
transduction [1, 2]. NO could be produced by nitric oxide synthase (NOS) and
nitrate reductase (NR) pathways within plants [3, 4]. Recently, NO was shown to
mediate diverse plant physiological processes such as germination, root growth,
flowering, stomatal closure, and resistance to biotic as well as abiotic stresses [5
8]. NO is also a key molecule in signal transduction pathways that initiates
secondary metabolite biosynthesis in plants [9, 10]. Parani et al (2004) showed
that NO modulated the expression of a substantial number of genes at the
transcriptional level in Arabidopsis thaliana. Hierarchical clustering revealed 162
genes showing a dose-dependent increase in signal from 0.1 mM SNP to 1.0 mM
SNP treatment . Although the evidence supporting NO as a mediator of plant
physiological processes continues to grow, its functions at the molecular level
remain poorly understood.
Genome-scale transcript analysis aims to capture an unbiased view of the
complete RNA transcript profile of a species, allowing the transcriptional level of
each gene in a given tissue at a given point in its life cycle to be monitored .
Transcriptome analysis is also an efficient means of analyzing the overall
transcript levels within specific tissues and organs, which not only generates large
numbers of expressed sequence tags (ESTs) but also builds gene expression
profiles . The gene expression level can be determined by its relative reads per
kilobases per million reads (RPKM) values, which is a measurement of the
number of RNA-sequencing reads mapped to the constitutive exons of a certain
gene and reflects whether a gene is transcribed and its relative abundance.
Therefore, the construction and analysis of a transcriptome can provide rapid and
improved understanding of gene expression and aid in the discovery of novel
genes involved in various cellular processes .
Birch (Betula platyphylla Suk.) is a broad-leaved pioneer tree species native to
eastern Asia, and it grows and regenerates quickly in disturbed habits. Plant cell
cultures are useful systems for the production of specific and valuable secondary
metabolites. Triterpenoids such as oleanolic acid, betulin, and betulinic acid are
pharmaceutical secondary metabolites with antibacterial, antiviral, and antitumor
properties, which can be extracted from B. platyphylla Suk .
The objective of this study was to investigate the role of NO at the
transcriptional level in B. platyphylla cells by genome-scale transcriptome analysis.
Here, we present a de novo transcriptome assembly of birch cells treated with
sodium nitroprusside (SNP) using Solexa data. Data were collected by sequencing
cDNA libraries of birch cells, which had a long period to adapt to the suspension
culture conditions before SNP-treated cells and untreated cells were sampled. We
specifically examined gene expression dynamics in this species in response to SNP
treatment and identified a core set of NO-related transcripts. The acquired
information should facilitate attempts to elucidate the response of secondary
metabolites when NO is present. We believe that this transcriptome analysis,
combined with observations of cellular triterpenoid content, and activities of
antioxidant defense enzymes, will shed light on the diverse roles of NO that affect
Materials and Methods
Birch Cell Culture
B. platyphylla cell was cultivated on optimized NagataTakebe medium
supplemented with 0.1 mgL21 6-benzyladenine, 0.01 mgL21 thidiazuron, and
20 gL21 sucrose according to our previous research . The pH of the medium
was adjusted to 5.56.0 and the medium was then sterilized by autoclaving at
121C for 20 min. The suspension culture (100 mL) was maintained in 250-mL
Erlenmeyer flasks incubated on a rotary shaker (110 rpm) at 25C, and inoculated
with 4.0 g fresh weight of 8-day-old cell suspension cultures. Illumination was
regulated to provide 14 h of light (photophase 06:0020:00 h) via fluorescent
tubes (a combination of Osram Fluoro and Osram Daylight types) with a photon
flux density (400700 nm) and intensity of 2000 lux.
RNA Extraction, Quality Determination, and Real-Time qRT-PCR
Cells (0.2 g) were collected by filtration from the culture medium and frozen in
liquid nitrogen. Total RNA was isolated using the CTAB-based method and
treated with RNase-free DNase I (Takara, Dalian, China) to remove genomic
DNA according to the manufacturers protocols. After DNase treatment, only the
RNA itself was amplified with the same primers to control the absence of DNA in
the RNA preparation. The quality of the RNA was verified on an 0.8% agarose gel
by using standard procedures. RNA (2.55 mg) was loaded onto the gels, and it
showed a sharp distinction at the small side of both the 18S and 28S rRNA bands.
The absorbance ratios (260 nm/280 nm) of the RNA samples dissolved in 10 mM
Tris (pH 7.6) ranged from 1.9 to 2.1. The integrity of RNA samples was examined
with an Agilent 2100 Bioanalyzer, and their RIN (RNA integrity number) values
ranged from 8.6 to 10.0, with no sign of degradation. One microgram of total
RNA was reverse-transcribed into first-strand complementary DNA (cDNA) by
using the reverse transcriptase M-MLV (Promega, Medison, USA) with
oligo(dT) primers, according to the manufacturers protocols. To verify the
transcriptome analysis results, quantitative RT-PCR was performed to quantify
the expression levels of the target genes. Quantitative RT-PCR was performed
using a Bio-Rad iCycler Real-Time PCR machine. Actin was used as an internal
control [19, 20]. The sequences of primers are listed in S1 Table. The PCR
reaction was carried out in a final volume of 20 mL, containing 2 L cDNA, 10 mL
of SYBR Premix Ex Taq II (Takara), 0.4 mL ROX Reference Dye II (506), 0.8 mL
each of forward and reverse primers. DNA was amplified with an initial
denaturation step of 30 s at 94C, followed by for 40 cycles consisting of 95C for
30 s, 60C for 34 s, and 72C for 1 min. The melting curves were generated (15 s
at 95C, 1 min at 60C, 15 s at 95C) after the final PCR cycle. The relative gene
expression levels of treatments were compared with the controls by the 22DDCt
method. For the control group, an equal volume of sterile water instead of SNP
was added. All measurements were performed in triplicate.
NO-Related Chemical Reagents, Screening for the Optimal
Concentration of SNP, and Treatment Process
After suspended cells were cultured for 8 days, the SNP (Sigma, St. Louis, MO,
USA) was added into the culture medium at final concentrations of 0.01, 0.1, 1,
and 10 mM respectively. For the controls, the SNP was replaced with an equal
volume of sterile water. The cells with 0.01, 0.1, 1, or 10 mM SNP were harvested
at 6, 12, 24, 48, 72, 120 and 168 h. The collected cells were then used to measure
the total concentration of oleanolic acid. SNP-treated cells (1 mM) and control
cells were harvested after incubation for 12 h. Then, the collected cells were used
for transcriptome analysis. To verify our results from transcriptome analysis,
NOspecific scavenger 2-(4-carboxyphenyl)-4,
4,5,5-tetramethylimidazoline-1-oxyl-3oxide (cPTIO) (Sigma, St. Louis, MO, USA) was used in the experiments at the
final concentration of 150 mM. Eight-day-old cells were pretreated with cPTIO
20 min prior to SNP treatment. The controls received only the vehicle water. The
concentrations of NO-related chemical reagents were selected based on previous
reports and the results of our preliminary experiments [21, 22]. All determinations
were carried out in triplicate.
Illumina Library Preparation and Solexa Sequencing
For cDNA synthesis and Solexa sequencing, mRNA was isolated from total RNA
(20 mg) by using poly-T oligo-attached magnetic beads (Illumina, San Diego, CA,
USA) and sheared to small fragments using divalent cations (Illumina) at 94C for
5 min. cDNA was synthesized using random primers and mRNA fragments as
templates. Three paired-end cDNA libraries with 200-bp insert sizes were
constructed, and then, the cDNA was sequenced using an Illumina Genome
Analyzer (Illumina) according to the manufacturers protocols.
The reads obtained were randomly clipped into 17-bp K-mers for assembly using
de Bruijn graph and SOAPdenovo software (version 1.04) with standard
parameters and steps . Briefly, SOAPdenovo first combined the clean reads
with 16-mer (K017 bp, do not set the R and M option) length of overlap
to form longer fragments without N (i.e., contigs). Subsequently, the reads were
mapped back to the contigs. From the paired-end reads, it is possible to detect not
only contigs from the same transcript but also the distances between these contigs.
Furthermore, SOAPdenovo connects contigs from the same transcript, using N to
represent unknown sequences between the two contigs, thus forming scaffolds.
Paired-end reads are used again for gap filling within scaffolds to obtain sequences
that have the fewest Ns and cannot be extended at either end. To obtain distinct
gene sequences, the scaffolds were clustered using TGI Clustering tools; these are
defined as UniGenes . To determine the gene abundance, the RPKM value of
each gene was calculated as described by Mortazavi and Wang [14, 25].
Individual tentatively unique genes (TUGs) were subjected to BLASTX analysis
against the protein databases of NR, Swiss-Prot, KEGG, and COG of NCBI to
search for similarity. TUGs with a BLASTX E-value .1025 were discarded for
functional annotations. Functional annotations using gene ontology (GO) terms
were analyzed by the Blast2GO program . After obtaining GO annotations for
all UniGenes, WEGO software was used  to perform GO functional
classification for all UniGenes according to their molecular functions,
involvement in biological processes, and cellular components. Furthermore, the
conserved functional motifs of TUGs were also analyzed with InterProScan
(http://www.ebi.ac.uk/interpro/scan.html) using default parameters.
Measurement of Total Triterpenoid Content, Oleanolic Acid
Content, Intracellular O22, and Antioxidant Enzyme Activities
The total triterpenoid content was determined by spectrophotometry  at
551 nm, and the results are expressed as milligrams per gram dry weight (DW).
The oleanolic acid content was measured by high-performance liquid
chromatography (HPLC) under the following conditions: sample volume of 20 mL,
mobile phase was 9 1 v/v acetonitrile-water, flow rate of 1 mL/min, column
temperature of 25C, and detection wavelength of 210 nm. Peroxidase (POD)
activity was tested according to the rate of guaiacol oxidation. The POD assay
mixture contained 0.1 M phosphate buffer (pH 6.1), 4 mM guaiacol as donor,
3 mM H2O2 as substrate, and 1.0 mL crude enzyme extract. The total reaction
volume was 3.0 mL. The rate of change in absorbance at 420 nm was measured,
and the enzyme activity was expressed as the difference in absorbance (OD).
Ascorbate peroxidase (APX) activity was measured according to the method of
Nakano and Asada . The level of superoxide anion (O22) was measured after
trichloromethane extraction by detecting the absorbance at 530 nm with the UV
All experiments were repeated three times. The data (mean standard error)
obtained were statistically analyzed using SPSS version 19.0. Data from
experiments were analyzed using a Students t-test for simple comparisons
between each treatment and its control, and a two way ANOVA with post-hoc
Tukey test for the multiple comparisons between means. Differences at P,0.05
were considered statistically significant.
Results and Discussion
Optimization of SNP Concentration
The oleanolic acid content increased in a time- and dose-dependent manner when
cells were treated with 0.01, 0.1 and 1 mM SNP within 72 h. Oleanolic acid
concentrations were observed to be higher in the 1-mM SNP treatment group
than that in the other groups, from 12 h to 72 h (Fig. 1). Therefore, 1 mM was
used as the optimal concentration of SNP to investigate the effect of exogenous
NO in regulating triterpenoid synthesis.
De novo Assembly and Quantitative Assessment of Illumina ESTs
In order to obtain a comprehensive view of the changes in gene expression
patterns in response to NO, transcriptome analyses were performed. A total of
12,570,361 reads were obtained by Solexa analysis, containing 6.21 Gb. The
percentage of N in the total nucleotide (nt) count was 0.54%, and the percentage
of GC in the transcriptome of the birch cell was 39.07%. The high-quality reads
were subjected to cluster analysis using the SOAPdenovo program. First, all reads
were grouped into contigs. In total, 229,575 contigs were generated, with a total
length of 71,768,587 nt and an average length of 312 nt. Nearly 50% of contigs
were between 100 and 200 nt. The paired-end contig sequences were grouped into
scaffolds, which were grouped into TUGs, and reads were used for gap filling. The
longest sequence was 39,247 nt. In total, 104,449 TUGs (.150 bp) were
generated, with an average length of 537 bp. Finally, we identified a total of 34,100
high-quality UniGene sequences.
Functional Annotation of Unique Genes
A BLASTX search was used for the functional annotation of the genes. Among the
34,100 UniGenes, 20,631 genes showed significant (E-values#1025) sequence
similarity with proteins from the NR-database. The proteins that most highly
matched the putative birch proteins were derived from various plants, particularly
Vitis vinifera L. (7621), Ricinus communis L. (4994), and Populus sp. (4836)
(Fig. 2). However, there were relatively few genes that matched proteins from
model plants such as Arabidopsis thaliana L. (346) and Oryza sativa L. (144)
(Fig. 2). These results suggest that birch shares a high degree of protein sequence
similarity with V. vinifera. Using the best hits found by BLASTX, an inferred
putative function was assigned to the sequences and they were sorted into major
functional categories (Fig. 3). These genes were classified into three main
functional groups: genes involved in biological processes, genes encoding cellular
components, and genes involved in molecular functions.
Transcript Differences between Control and SNP-Treated Cells
According to the applied criteria (two-fold or greater change and P,0.001), 1,374
ESTs were identified as differentially expressed between the 12-h SNP-treated cells
Fig. 1. Changes in oleanolic acid content among the control (CK), 0.01 mM, 0.1 mM, 1 mM, and 10 mM SNP groups at different times. Different
letters represent significant difference (P,0.05).
Fig. 2. Distribution of UniGenes among different plant species.
Fig. 3. GO categories for the birch cell UniGenes. The percentage and total number of UniGenes in each category is shown.
and control cells samples: 403 up-regulated and 971 down-regulated. This 12-h
SNP treatment had apparently modified the expression of almost 4.03% of the
total UniGenes. Therefore, it is obvious that birch cells respond to SNP treatment
by moderate reprogramming of its transcriptome. We have clustered the
differentially expressed genes according to known functions. Genes can have more
than one particular function assigned, so some genes can appear in more than one
group. Additionally, a GO analysis was performed using Blast2GO to determine
gene enrichment and overrepresentation in the three categories: molecular
function, biological processes, and cellular components (Fig. 4). Taken together,
these experiments were used to analyze the specific differences in transcript
expression induced by NO.
Protection against Reactive Oxygen Species (ROS)
ROS are chemically reactive molecules that contain oxygen, such as superoxide
anion radical (O22) and hydrogen peroxide (H2O2). These highly reactive
chemicals are natural by-products of aerobic metabolism, and ROS
overproduction is toxic as it causes damage to carbohydrates, lipids, proteins, and
DNA . The data from our transcriptome analysis revealed that transcript
abundance of genes coding for different components of the ROS scavenging
machinery does differ dramatically between control cells and SNP-treated cells.
A total of 30 genes encoding proteins with antioxidant properties were
upregulated during NO treatment. These predicted proteins were glutathione
Stransferases (GST) 1, 2, and 3, thioredoxin peroxidase (TPx), superoxide
Fig. 4. GO categories of differentially expressed ESTs.
dismutase (SOD), ascorbate peroxidase (APX), and peroxidase (POD). These
upregulated genes also include four NADP-dependent oxidoreductases, a
transcription factor LONG HYPOCOTYL 5 (HY5) and thioredoxin (Trx), all of which
play a role in the active synthesis of ROS or in antioxidant defense [32, 33].
The levels of intracellular H2O2 and O2 were analyzed among the control, SNP
+ cPTIO and KFeCN groups at 12 h (Fig. 5). The content of O2 in cells treated
with 1 mM SNP were indeed higher than the control group. There was no
significant difference in the contents of intracellular H2O2 among the control,
SNP + cPTIO and KFeCN groups. To verify our results from transcriptome
analysis, qRT-PCR was also performed first to quantify the expression levels of
BpFeSOD (Fe superoxide dismutase), BpMnSOD (Mn superoxide dismutase),
BpCZSOD (copper/zinc superoxide dismutase), and BpHO (heme oxygenase)
(Fig. 6). The NO scavenger (SNP + cPTIO group) and SNP structural analogue
(KFeCN group) treatments were used as controls to reveal the response of these
genes to NO signal. In addition, the gene expression dynamics of birch cells in
Fig. 5. Changes in H2O2 and O22 contents among the control (CK), SNP, KFeCN, and SNP + cPTIO groups (S + cPTIO). Different letters represent
significant difference (P,0.05).
response to SNP treated after 6, 12, 24, and 48 h were analyzed to define the
timedependence for selected genes. The results showed that four genes were
significantly up-regulated after the 6-h SNP treatment. Except for BpFeSOD after
24 h SNP treatment that was expressed at a lower level than that of the control,
expression of other genes was higher than that of the control at different time
points in response to SNP. Our qRT-PCR analysis indeed indicated that several
SOD genes were up-regulated in cells by NO treatment. Enzyme activity analysis
was performed to examine the increased levels of POD and APX in cells treated
with NO (Fig. 7). Consistent with mRNA levels, enzyme activity analyses
indicated that APX was expressed predominantly in cells treated by NO. Enzyme
activity of POD was lower upon SNP treatment at 12 h, but it was higher than
control from 24 h to 168 h (data not shown). Taken together, the results from
qRT-PCR and enzyme activity analyses were consistent with our initial
transcriptome analysis. Therefore, it is concluded that NO could cause oxidative
stress in these cells, and regulate transcription of genes encoding antioxidant
Fig. 6. Relative expression levels of antioxidant genes in the groups treated with 1 mM SNP for 6, 12, 24, and 48 h (left); relative expression levels
of antioxidant genes in the SNP, KFeCN, and SNP + cPTIO groups (S + cPTIO) (right). Different letters represent significant difference (P,0.05).
Fig. 7. Changes in antioxidant enzyme activities, including POD and APX among the control (CK), SNP, KFeCN, and SNP + cPTIO (S + cPTIO)
groups. Different letters represent significant difference (P,0.05).
In addition, the genes related to plantfungus interactions are overrepresented
in the genes preferentially expressed in cells treated by NO. These include two
genes encoding Pathogen-related protein (PR1C, PRPX), a gene encoding Allene
oxide synthase, an enzyme responsible for salicylic acid (SA) biosynthesis, and a
gene coding for indole-3-acetic acid amido synthetases (GH3.6). Members of the
GH3 family encode enzymes that catalyze adenylation of both Indole-3-acetic acid
(IAA) and SA . Overexpression of GH3 induces disease resistance [35, 36].
Overall, we conclude that the transcriptome in cells treated by NO resembles that
of biotic stress responses. It is possible that biotic defense responses are activated
developmentally independent of exposure to NO.
The enzymatic ROS scavenging system includes superoxide dismutase (SOD),
catalase (CAT), ascorbate peroxidase (APX) and peroxidase (POD). FeSOD,
MnSOD, and CZSOD are the three isozymes of SODs in plants . Plant heme
oxygenases (HOs) regulate the biosynthesis of phytochrome, which accounts for
photo-acceptance and -morphogenesis. Recent studies have demonstrated that
plant HOs also regulate many other physiological processes including response to
environmental stimuli and ROS .
Carbohydrate Metabolism and Cell Wall Biosynthesis
One characteristic GO category found in cells treated with NO, is carbohydrate
metabolism and cell wall biosynthesis. The expression of beta-D-xylosidase (BXL1,
2), Aldose 1-epimerase (GALM), UDP-glucose 4-epimerase (GALE2), Sucrose
synthase 2 (SUS2), which are involved in carbohydrate metabolism were enhanced
by NO treatment. In the study, genes for cellulose synthase (CESA8), cellulose
synthase-like proteins (CSLE6), xyloglucan endotransglycosylases (XETs), caffeic
acid 3-O-methyltransferase (COMT1), and 4-coumarateCoA ligase-like 9
(4CLL9), and inositol oxygenase 4 (MIOX4) are more abundantly expressed in
cells treated with NO as compared to control cells. MIOX, which is a key enzyme
in UDP-glucuronic acid biosynthesis, is involved in cell wall synthesis.
Fig. 8. Relative expression levels of genes related to cell wall synthesis in the groups treated with 1 mM SNP for 6, 12, 24, and 48 h (left). Relative
expression levels of genes related to cell wall synthesis in SNP, KFeCN, and SNP + cPTIO (S + cPTIO) groups (right). Different letters represent significant
To verify our results from transcriptome analysis, qRT-PCR was performed to
quantify the expression levels of BpSUS2, BpCESA8, BpMIOX4, BpCOMT1, and
BpBXL1 (Fig. 8). The NO scavenger (SNP + cPTIO group) and SNP structural
analogue (KFeCN group) treatments were used as controls to reveal the response
of these genes to NO exposure. The results showed the expression levels of
BpSUS2, BpCESA8, BpMIOX4, BpCOMT1, and BpBXL1 in the SNP group was
higher than those in the KFeCN and SNP + cPTIO groups. The gene expression
dynamics of birch cells in response to SNP treatment for 6, 12, 24, and 48 h were
also analyzed to define the time-dependence for selected genes. The results showed
that five genes were significantly up-regulated after 6-h SNP treatment. The
expression levels of BpSUS2, BpMIOX4, and BpCOMT1 were highest at 12 h SNP
treatment. The expression of other genes was also higher in SNP-treated cells as
compared to control cells. Our qRT-PCR did indeed indicate that these genes
were up-regulated in cells as a result of NO treatment.
Another enriched GO category in the genes preferentially expressed in cells treated
by NO, are those of secondary metabolism, especially for the terpenoid
biosynthesis pathway. Genes for chalcone synthase (CHS), isoflavone reductase,
isoflavone 29-hydroxylase are expressed most abundantly in the cells treated by
NO. The expression of 1-deoxy-D-xylulose-5-phosphate synthase (DXS),
3hydroxy-3-methylglutaryl-coenzyme A reductase (HMGR), cytochrome P450;
secologanin synthase (SLS), cycloartenol synthase (CAS), squalene synthetase
(SQS), b-amyrin synthase (AMS), allene oxide synthase (AOS), which are
involved in triterpenoid synthesis, are abundantly expressed in cells exposed to
NO as compared to control cells.
The oleanolic acid and triterpene contents in KFeCN, and SNP + cPTIO groups
were significantly reduced when compared to the SNP group, which suggested
that NO could promote triterpenoid synthesis (Fig. 9). The expression of some
Fig. 9. Changes in total triterpene and oleanolic acid content in the control (CK), SNP, KFeCN, and SNP + cPTIO (S + cPTIO) groups. Different letters
represent significant difference (P,0.05).
key genes in the triterpenoid synthesis were analyzed by qRT-PCR to verify our
results from transcriptome analysis. The expression levels of BpHMGR, BpDXR,
BpSQS, BpAMS, and BpCYP716A in the SNP group were 2.73, 4.99, 3.92, 3.41 and
9.00 times higher, respectively, than the corresponding levels in the KFeCN group
(Fig. 10). The expression levels of these genes were significantly reduced in the
SNP + cPTIO group, which suggested that NO could mediate triterpenoid
synthesis by regulating the expression of the key enzymes. The time-dependence
for the key genes in the triterpenoid synthesis was also revealed by the gene
expression dynamics of birch cells in response to SNP treatment. The results
showed that five genes were significantly up-regulated after the 6-h SNP
treatment. The expression levels of BpAMS and BpCYP716A were highest at 6 h of
SNP treatment. The expression of BpDXR and BpSQS were highest after 24 h of
The isopentyl diphosphate and dimethylallyl diphosphate are the common
precursors for triterpenoid biosynthesis, which come from mevalonic pathway
and methylerythritol 4-phosphate pathway . The acetyl coenzyme A could
form mevalonate under the catalysis of 3-hydroxy-3-methylglutaryl coenzyme A
reductase (HMGR) and the formation of methylerythritol 4-phosphate is
catalyzed by deoxy-xylulose phosphate isomerase (DXR) [42, 43].
2,3Oxidosqualene can be synthesized in the presence of squalene epoxidase (SQS)
and then formation of oleanolic acid is catalyzed by b-amyrenol and cytochrome
P450 enzyme (CYP716A) . Therefore, HMGR, DXR, SQS, AMS, and
CYP716A are key enzymes in the triterpenoid biosynthesis pathway. These results
clearly indicated that NO is a key molecule in signal transduction for secondary
metabolite biosynthesis in plants, which is similar to results found in other studies
Fig. 10. Relative expression levels of genes related to triterpene synthesis in the groups treated with 1 mM SNP for 6, 12, 24, and 48 h (left).
Relative expression levels of genes related to triterpene synthesis in the SNP, KFeCN, and SNP + cPTIO (S + cPTIO) groups (right). Different letters
represent significant difference (P,0.05).
In the group of genes linked to growth regulation, we found nine genes to be
repressed and eight genes to be enhanced. The expression of gibberellin
2-betadioxygenase 2 (G2OX2), nitrate reductase (NR) and NO associated protein1
(NOA1), which is similar to nitric oxide synthase (NOS) in animals, was
upregulated in response to SNP exposure. G2OX2 was involved in gibberellin (GA)
synthesis. NO could be produced by the nitric oxide synthase (NOS) pathway and
the nitrate reductase (NR) pathway in plants [3, 4]. These results suggest that SNP
treatment could influence endogenous NO synthesis. Whereas, the expression of
1-aminocyclopropane-1-carboxylate synthase (ACC) was reduced when cells were
exposed to NO. This enzyme is typically involved in ethylene synthesis. Of eight
repressed genes, we detected three protein kinase genes: nucleoside diphosphate
kinase 1 (NDK1), mitogen-activated protein kinase kinase kinase 2 (M3K2),
mitogen-activated protein kinase kinase kinase ANP1 (ANP1), which involved in
mitogen-activated kinases (MAPK) pathways. The expression of another protein
kinase gene, serine/threonine-protein kinase WNK (with no lysine kinase) 4 was
up-regulated by SNP treatment. WNK kinase is involved in cell growth and
survival signaling, and can inhibit the MEK1/ERK1/2 pathway and cell
proliferation . Three genes involved in cell division and proliferation, cell
division control protein 45 (CDC45), cell division control protein 6 homolog
(CDC6), and the G2/mitotic-specific cyclin-2 (CCN2), were repressed by SNP
treatment. Genes involved in cell division were down-regulated to up to 5- to
10fold when exposed to SNP, indicating that NO affected the cell proliferation
process. Meanwhile, rhythmically related genes for transcription factor HY5,
rhythmically expressed gene 2 protein (REG2), and transcription factor HY5
homolog (HYH), which has also been reported to mediate plant responses to
hormones, cold, UV-B, and ROS signaling , were up-regulated by SNP
treatment, indicating that NO was involved in the regulation of plant growth and
development. To verify our results from transcriptome analysis, qRT-PCR was
Fig. 11. Relative expression levels of genes related to endogenous NO synthesis (BpNR and BpNOA1) and calcium signaling (BpCALM) in groups
treated with 1 mM SNP for 6, 12, 24, and 48 h (left). The relative expression levels of genes related to endogenous NO synthesis (BpNR and BpNOA1)
and calcium signaling pathways (BpCALM) in the SNP, KFeCN, and SNP + cPTIO (S + cPTIO) groups (right). Different letters represent significant
performed to quantify the expression levels of BpCALM (Calmodulin), BpNR, and
BpNOA1 (Fig. 11). The results showed that the expression levels of BpCALM,
BpNR, and BpNOA1 in the SNP group were significantly higher than those in the
KFeCN and SNP + cPTIO group at 12 h. The results of gene expression dynamics
showed that three genes were significantly up-regulated after the 6-h SNP
treatment. The expression level of BpCALM was highest after the 6-h SNP
treatment, and significantly lower than the control group at 12 h. The expression
of BpNR and BpNOA1 genes were highest after 24 h and 12 h SNP treatment,
respectively. The qRT-PCR results indeed indicated that these genes were
upregulated in cells by NO treatment, which suggested exogenous NO was involved
in the regulation of endogenous NO signal and Ca2+ levels (Fig. 11).
We examined the gene expression dynamics of Betula platyphylla in response to
SNP treatment and identified a core set of NO-related transcripts. Taken together,
the results from qRT-PCR were consistent with our initial transcriptome analysis.
Thus, the combination of transcriptome analysis, gene expression quantification
and select enzyme assays indicated that birch cell exposure to NO has a significant
effect on many processes including triterpenoid production, carbohydrate
metabolism and cell wall biosynthesis.
S1 Table. Sequences of primer pairs for quantitative real-time RT-PCR assay.
We thank Dr. Yungang Xu in Harbin Institute of Technology for his help in data
analysis. We also thank editor and anonymous reviewers for many detailed and
helpful comments that improved the quality of this manuscript.
Conceived and designed the experiments: YZ FZ. Performed the experiments: FZ
FS KL. Analyzed the data: FZ LL. Contributed reagents/materials/analysis tools:
YZ FZ. Contributed to the writing of the manuscript: YZ FZ.
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