Abstract
This work aims at studying the molecular mechanisms underlying the
response of Reaumuria soongorica to salt stress. We used RNA sequencing
(RNA-Seq) and Tandem Mass Tag (TMT) techniques to identify
differentially expressed genes (DEGs) and differentially expressed
proteins (DEPs) in R. soongorica leaves treated with 0, 200, and 500 mM
NaCl for 72 h. The results indicated that compared with the 0 mM NaCl
treatment group, 2391 and 6400 DEGs were identified in the 200 and 500
mM NaCl treatment groups, respectively, while 47 and 177 DEPs were also
identified. Transcriptome and proteome association analysis was further
performed on R. soongorica leaves in the 0/500 mM NaCl treatment group,
and 32 genes with consistent mRNA and protein expression trends were
identified. SYP71, CS, PCC13-62, PASN, ZIFL1, CHS2, and other
differential genes are involved in photosynthesis, vesicle transport,
auxin transport, and other functions of plants, and might play a key
role in the salt tolerance of R. soongorica. In this study,
transcriptome and proteome association techniques were used to screen
candidate genes associated with salt tolerance in R. soongorica, which
provides an important theoretical basis for understanding the molecular
mechanism of salt tolerance in R. soongorica and breeding high-quality
germplasm resources.
Keywords: Reaumuria soongorica, salt stress, transcriptome, proteome,
association analysis
1. Introduction
Due to climate change and human activities, soil salinization in arid
and semiarid regions has become increasingly severe, which has become a
major obstacle to the high-quality development of the ecological
environment and economy in these regions [[34]1]. Excessive
accumulation of soil salts inhibits plant growth, reduces species
diversity, changes the composition of plant communities, and reduces
the biological productivity and biomass of the ecosystem [[35]2,[36]3].
Plants have a series of tolerance mechanisms to cope with salt stress,
including modulation of various morpho-physiological attributes,
antioxidant machinery, osmotic balance, and phytohormones [[37]4].
Farhangi et al. [[38]5] found that the body of Phaseolus vulgaris L.
accumulates a large amount of soluble sugars to alleviate salt stress
damage to cells. Glucose and sucrose in soluble sugars play important
roles in plant growth and development and may be involved in regulating
plant response to salt as signaling substances [[39]6]. In addition,
recent findings have shown that STI is a suitable tolerance index that
can evaluate the salt tolerance of plants at different salt
concentrations and determine the salt threshold concentration of plants
[[40]7,[41]8]. Therefore, it is of great significance to understand the
perception and response of plants to salt stress in order to improve
the salt tolerance of plants.
The response of plants to abiotic stress involves a complete set of
fine expression regulation mechanisms, such as transcriptional
regulation, post-transcriptional regulation, translational regulation,
and post-translational regulation [[42]9]. The genomic resources of
plants growing under salt stress provide important benchmarks for
improving plant salt tolerance, alleviating salt damage, and improving
soils [[43]10,[44]11]. Aliakbari et al. [[45]12] analyzed the gene
expression pattern of Salicornia persica using RNA-Seq technology and
identified 1595 differentially expressed genes under salinity.
Functional annotation analysis showed that energy homeostasis and
primary metabolite synthesis play key roles in salinity adaptation.
Chen et al. [[46]13] investigated the leaf proteome of Apocynum venetum
L. under salt stress and found that differential proteins were mainly
involved in carbohydrate and energy metabolism, metabolite
biosynthesis, and signal transduction. Dehydrin 1, annexin,
pathogenesis-related protein, and peroxidase were also identified.
Zhang et al. [[47]14] used transcriptional sequencing and isobaric tag
for relative and absolute quantitation (iTRAQ) proteomics analysis to
identify 5432 genes and 43 proteins differentially expressed in
Helianthus tuberosus L. leaves under salt stress, and these genes were
mainly enriched in carbohydrate metabolism, ribosome activation and
translation, redox, and ion binding. Transcriptome and proteome
association found that the induced activity of ribosome and sugar
signaling may confer Helianthus tuberosus L. with salt tolerance.
Therefore, transcriptome and proteome techniques can be used as an
effective method to screen potential salt-tolerance genes in plants.
Since transcriptome and proteome reflect gene expression at different
levels, it is necessary to detect mRNA and protein expression levels
and perform omics data integration analysis to comprehensively explore
the complex life activities of organisms and lay the foundation for
revealing the regulatory rules of complex life activities of organisms
at the molecular level.
Reaumuria soongorica is a super xerophytic salt-tolerant small shrub.
It is a typical construction species and dominant species in the
ecosystem of arid and semiarid regions, with strong stress resistance,
grazing tolerance, sand-collecting ability, etc. [[48]15]. Its leaves
are rich in proteins, fats, and trace elements. It is the main
vegetation for the construction of fodder bushes and the cultivation of
degraded grasslands [[49]16]. The unique salt gland structure of R.
soongorica is an essential guarantee for its survival in saline
environments. Its primary function is to transport salt secreted by the
plant from the surrounding tissues to large vesicles that collect the
salt. Subsequently, the substances accumulated by the secretory cells
are transported into their small vesicles. These are constantly moving
towards the cell membrane side and are finally excreted through the
outer plasma membrane of the secretory cells, thus improving their
osmotic adjustment ability and maintaining normal plant growth under
salt stress [[50]15]. At present, a number of research teams have
conducted physiological and biochemical studies on R. soongorica
seedlings under salt stress, mainly focusing on ion absorption, seed
germination, and the antioxidant capacity of callus
[[51]17,[52]18,[53]19,[54]20,[55]21]. However, there are few studies on
the molecular mechanism of salt tolerance of R. soongorica seedlings
[[56]9,[57]22]. The study of integrated transcriptome and proteome
analysis of the response to salt stress has not been reported. In this
study, modern biological techniques were used to investigate the
differentially expressed genes and protein expression profiles of R.
soongorica responding to salt stress, the key genes and proteins
involved in the salt tolerance defense system were explored, and the
regulatory mechanism of R. soongorica responding to salt stress was
elucidated. This study not only provided a new understanding of the
molecular response mechanism of R. soongorica to salt stress but also
provided potential genetic resources for breeding R. soongorica.
2. Results
2.1. Effects of NaCl Concentrations on Growth and Development of R.
soongorica Seedling
Under the same stress treatment time, the plant height of R. soongorica
first increased and then decreased with increasing salt concentration.
Compared with the control at 24 h of stress treatments, the plant
height of all NaCl treatments showed no significant difference. At 72,
144, and 216 h of stress treatments, plant height was highest under the
200 mM NaCl concentration, and plant height was the lowest under the
500 mM NaCl concentration. In the same salt concentration treatment,
plant height showed an increasing trend with increasing days of stress.
Compared to 24 h of stress, plant height increased by 36.62%, 37.67%,
44.43%, 28.45%, 17.59%, and 13.26% under different concentration
treatments at 216 h of stress ([58]Table 1). Furthermore, it can be
seen from [59]Table 1 that the root length of R. soongorica seedlings
first increased and then decreased with increasing NaCl treatment
concentration. At 24 h and 72 h of stress, the root length under the
200 mM NaCl treatment increased by 6.98% and 4.09% compared with the
control, respectively. At 144 h and 216 h of stress, the root length
gradually decreased with increasing NaCl concentration.
Table 1.
Effects of NaCl stress on the plant height and root length of R.
soongorica seedlings.
Growth Index NaCl Concentration (mM·L^−1) Treatment Time/h
24 72 144 216
Plant height (cm) 0 9.42 ± 0.231 a 10.33 ± 0.207 bc 10.86 ± 0.210 c
12.87 ± 0.378 c
100 9.77 ± 0.061 a 10.79 ± 0.096 b 11.12 ± 0.253 bc 13.45 ± 0.258 b
200 9.97 ± 0.558 a 11.37 ± 0.252 a 11.78 ± 0.491 a 14.40 ± 0.150 a
300 9.70 ± 0.387 a 10.07 ± 0.113 c 11.50 ± 0.452 ab 12.46 ± 0.314 c
400 9.55 ± 0.444 a 10.12 ± 0.150 c 10.73 ± 0.111 c 11.23 ± 0.469 d
500 9.35 ± 0.229 a 9.54 ± 0.611 d 10.10 ± 0.155 d 10.59 ± 0.213 e
Root length (cm) 0 8.60 ± 0.200 bc 9.53 ± 0.368 ab 10.42 ± 0.187 a
11.27 ± 0.436 a
100 8.85 ± 0.141 ab 9.82 ± 0.104 a 10.17 ± 0.262 ab 10.98 ± 0.366 ab
200 9.20 ± 0.586 a 9.92 ± 0.295 a 10.06 ± 0.213 abc 10.53 ± 0.530 bc
300 9.40 ± 0.305 a 9.65 ± 0.202 ab 9.82 ± 0.369 bc 9.97 ± 0.337 cd
400 8.42 ± 0.092 bc 9.2 ± 0.162 bc 9.51 ± 0.413 cd 9.74 ± 0.114 d
500 8.15 ± 0.218 c 8.78 ± 0.144 c 9.04 ± 0.291 d 9.36 ± 0.240 d
[60]Open in a new tab
Notes: Data are presented as average ± SE (n = 3). Different lowercase
letters denote significant differences at the 0.05 probability level
according to the Duncan test.
[61]Figure 1A shows that different NaCl treatment concentrations
significantly changed the soluble sugar content in R. soongorica
leaves. The soluble sugar content decreased with the increase in NaCl
treatment concentration at 24 h of treatment, and the soluble sugar
content showed a trend of first increasing and then decreasing with the
increase in NaCl treatment concentration at 72 h of treatment. The
soluble sugar content gradually increased with the increase in NaCl
treatment concentration at 144 and 216 h of treatment. The soluble
sugar content seemed to increase at different rates during the whole
treatment cycle, especially when the soluble sugar content in leaves
increased to the maximum after 144 h of the 500 mM NaCl treatment and
then remained at a high level. [62]Figure 1B shows that the tolerance
index of R. soongorica seedlings to NaCl was significantly lower than
that of other treatments at 400 and 500 mM NaCl for 24 h. Except for
the 24 h NaCl treatment, the tolerance index of seedlings to NaCl first
increased and then decreased with increasing NaCl concentration at the
other treatment time. The tolerance index of seedlings was the highest
under the 200 mM NaCl treatment, and then it started to decrease
gradually. With the prolongation of salt stress time, the tolerance
index of seedlings was gradually decreased under the 400 and 500 mM
NaCl treatments. When the treatment concentration reached 500 mM NaCl
after 216 h of NaCl treatment, the tolerance index of the seedlings was
only 58.42%.
Figure 1.
[63]Figure 1
[64]Open in a new tab
Physiological changes in R. soongorica leaves under salt stress. (A)
Effect of NaCl stress on the soluble sugar content of R. soongorica
leaves. (B) Changes in salt tolerance coefficient of R. soongorica
under NaCl stress. N0: 0 mM NaCl; N100: 100 mM NaCl; N200: 200 mM NaCl;
N300: 300 mM NaCl; N400: 400 mM NaCl; N500: 500 mM NaCl. Different
lowercase letters indicate significant differences from different salt
levels (p < 0.05).
2.2. De Novo Assembly and Annotation of the R. soongorica Transcriptome
To comprehensively understand the transcriptomic profiles of R.
soongorica and to identify differentially expressed genes (DEGs) in
response to salt stress, we sequenced the transcriptomes of nine
different R. soongorica libraries, and (A1, A2, A3), (B1, B2, B3), and
(C1, C2, C3) were three biological replicates of 0 mM NaCl (control),
200 mM NaCl, and 500 mM NaCl, respectively ([65]Figure 2). First, total
RNA was extracted from the 0 mM NaCl (control), 200 mM NaCl, and 500 mM
NaCl-treated samples, and RNA sequencing was performed by Illumina
Hiseq. A total of 388,789,330 clean reads were obtained from nine
samples using low-quality (Q-value < 20) and multiple N-base filtered
reads ([66]Table S3). The filtered clean reads were assembled using
Trinity 2.5.1 software and the longest transcripts were selected as
unigenes. After isoform detection, a total of 79,307 unigenes longer
than 300 bp were obtained from these nine libraries. All single gene
sequences were identified using Blastx and compared with NR (NCBI
non-redundant protein sequences), GO, KEGG, egg NOG (Evolutionary
genealogy of Genes: Non-supervised Orthologous Groups), Swiss-Prot and
Pfam databases, and the annotation rates were 37.65%, 16.88%, 15.26%,
21.90%, 35.79%, and 28.58%, respectively ([67]Figure 3).
Figure 2.
[68]Figure 2
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A representative figure of the phenotypic differences of R. soongorica
seedlings under different treatments.
Figure 3.
[70]Figure 3
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Annotation statistics of Unigene in R. soongorica leaves under NaCl
stress.
2.3. Transcriptome Data Profiling of R. soongorica Leaves
The expression levels of the same gene in different samples and the
expression patterns of DEGs in the same sample are based on RNA-Seq
data. A heat map was constructed based on the Euclidean method to
calculate distances and the hierarchical clustering longest distance
method (complete linkage) to analyze quantitative differences in the
expression levels of DEGs in all comparison groups ([72]Figure 4B). The
cluster analysis results showed significant differences between the
control and the salt-treated groups. In addition, principal component
analysis (PCA) was performed on each sample according to the expression
level ([73]Figure 4A). Significant differences were found between the
transcriptomes of R. soongorica leaves under different salt treatments,
and the data were well reproducible within groups. Statistical results
of DEGs between the 0, 200, and 500 mM NaCl treatment groups are shown
in [74]Figure 4C: compared with the 0 mM NaCl treatment, under the 200
mM NaCl treatment, i.e., 2391 (1057 up-regulated/1334 down-regulated)
DEGs, compared with the 500 mM NaCl treatment, i.e., 6400 (3093
up-regulated/3307 down-regulated) DEGs, and the 500 mM NaCl treatment
compared to the 200 mM NaCl treatment, i.e., 3642 (2169
up-regulated/1473 down-regulated) DEGs ([75]Table S4). The
comprehensive results showed that there were more down-regulated genes
than up-regulated genes under the salinity treatment compared to the 0
mM NaCl treatment, while the number of DEGs of R. soongorica leaves
treated with high NaCl concentrations was significantly higher than
that of leaves treated with low NaCl concentrations.
Figure 4.
[76]Figure 4
[77]Open in a new tab
Identification and analysis of DEGs in R. soongorica leaves under 0,
200, and 500 mM NaCl. (A) The similarity of gene expression was
compared in three-sample groups using PCA. (B) Cluster analysis of DEGs
in R. soongorica leaves under different NaCl treatments. (C) Common or
unique DEGs are compared using the Venn diagram.
GO enrichment analysis was performed on the DEGs treated with different
concentrations of NaCl, and GO classification was performed according
to molecular function, biological process, and cellular component. The
top 10 GO terms with the most significant enrichment in each GO
classification were selected for display, and the results are shown in
[78]Figure 5A,B. Compared with the 0 mM NaCl treatment, DEGs in the 200
mM and 500 mM NaCl treatment groups were significantly enriched in the
extracellular region, cell wall, photosystem, oxidoreductase and
peroxidase activity, xyloglucan metabolic process, flavonoid metabolic
process, etc. Compared with the 200 mM NaCl treatment group, DEGs in
the 500 mM NaCl treatment group were significantly enriched in the
apoplast, 3-dehydroquinate dehydratase activity, dioxide-reduction
process, flavonoid biosynthesis process, and so on ([79]Figure 5C). In
addition, KEGG enrichment analysis showed that DEGs in mannose-type
O-glycan biosynthesis, anthocyanin biosynthesis, flavone and flavonol
biosynthesis, photosynthesis-antenna proteins, brassinosteroid
biosynthesis, etc., were significantly enriched after the 200 mM and
500 mM NaCl treatments compared with the 0 mM NaCl treatment
([80]Figure 5D,E). Comparing the 500 mM and 200 mM NaCl treatment
groups, DEGs in flavone and flavonol biosynthesis, linoleic acid
metabolism, festoon antenna proteins, and other pathways were
significantly enriched ([81]Figure 5F). These results suggest that R.
soongorica leaves respond to salt stress primarily by regulating
cellular metabolism and photosynthesis.
Figure 5.
[82]Figure 5
[83]Open in a new tab
GO classification and KEGG pathway of DEGs under different salt
concentration stresses. (A–C) GO classification of DEGs in R.
soongorica leaves under different NaCl treatments. (D–F) KEGG pathway
enrichment of DEGs in R. soongorica leaves under different NaCl
treatments.
2.4. Proteomic Data Profiling of R. soongorica Leaves
A total of 236,522 chromatograms were obtained from the mass
spectrometry experiment. After analysis by Proteome Discoverer 2.2
software, 32,743 chromatograms were matched: 4432 proteins and 22,447
peptides were identified, including 21,011 TMT-labeled peptides. The
peptide labeling efficiency was 93.6% ([84]Figure 6A). PCA shows that
PC1, which explains 42.3% of the total variation, cleanly separates
plants from the 200 mM NaCl treatment from those from the 500 mM and 0
mM NaCl treatments, and the data within the group have good
repeatability. PC2, which explained 23.9% of the total variation,
showed differences between the 0 mM and 500 mM NaCl treatments
([85]Figure 6B). Statistical results of differentially expressed
proteins (DEPs) between the 0, 200, and 500 mM NaCl treatments are
shown in [86]Figure 6C. Comparison of salt-treated plants with the 0 mM
NaCl treatment revealed differential expression of 47 (36
up-regulated/11 down-regulated) and 177 (126 up-regulated/51
down-regulated) DEPs at 200 and 500 mM NaCl treatment, respectively.
Compared to the 200 mM NaCl treatment, 69 up-regulated and 67
down-regulated proteins were recorded in the 500 mM NaCl treatment
([87]Table S5). By analyzing different DEPs, it was found that the
number of DEPs induced by 500 mM NaCl was significantly higher than
that induced by 200 mM NaCl compared with the 0 mM NaCl treatment.
Figure 6.
[88]Figure 6
[89]Open in a new tab
Identification and analysis of DEPs in R. soongorica leaves under 0,
200, and 500 mM NaCl. (A) Protein information identified by TMT. (B)
The similarity of protein expression was compared in three sample
groups using PCA. (C) Common or unique DEPs are compared using the Venn
diagram.
GO functional enrichment analysis of the DEPs in the three comparison
groups showed that there were 10, 12, and 11 significant enrichment
items (p < 0.05) in the biological processes of the 0/200, 0/500, and
200/500 comparison groups, respectively ([90]Figure 7A–C). They mainly
included metabolic processes, response to osmotic stress, biological
regulation, etc. In the 0/200 comparison group ([91]Figure 7A), 11
items were enriched in molecular function, mainly involving transferase
activity, ion binding, protein binding, etc. There were 16 items
enriched in cellular component, mainly involving membrane, endomembrane
system, cytosol, etc. In the 0/500 comparison group ([92]Figure 7B), 11
items were enriched in molecular function, mainly involving ion
binding, hydrolase activity, protein binding, etc. There were 16 items
enriched in cellular component, mainly involving membrane, cytosol,
nucleus, etc. In the 200/500 comparison group ([93]Figure 7C), 14 items
were enriched in molecular function, mainly involving ion binding,
protein binding, hydrolase activity, etc. There were 17 items enriched
in cellular component, including membrane, cytosol, and
protein-containing complex. According to the above data, the DEPs of R.
soongorica leaves respond to a variety of biological functions under
salt treatment.
Figure 7.
[94]Figure 7
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GO classification and KEGG pathway of DEPs under different salt
concentration stresses. (A–C) GO classification of DEPs in R.
soongorica leaves under different NaCl treatments. (D–F) KEGG pathway
enrichment of DEPsin R. soongorica leaves under different NaCl
treatments.
To further understand the biological functions of the proteins, KEGG
enrichment analysis was performed on the annotated DEPs. The results
showed that compared with 0 mM NaCl treatment, the DEPs in the 200 mM
NaCl treatment group were significantly enriched in sesquiterpenoid and
triterpenoid biosynthesis, glucosinolate biosynthesis, and other
pathways ([96]Figure 7D). In the 500 mM NaCl treatment group, DEPs were
significantly enriched in linoleic acid metabolism, porphyrin,
chlorophyll metabolism, and other pathways ([97]Figure 7E). Compared
with the 200 mM treatment group, DEPs in the 500 mM NaCl treatment
group were significantly enriched in glucosinolate biosynthesis,
nitrogen metabolism, SNARE interactions in vesicular transport, and
other pathways ([98]Figure 7F).
2.5. Transcriptomic and Proteomic Association Analysis
To correlate transcript and protein expression profiles, accession
numbers were extracted from the proteome and compared to annotated
RNA-Seq libraries ([99]Table S6). According to the association
analysis, there were 5, 32, and 10 genes with the same protein and mRNA
changes in the 0/200, 0/500, and 200/500 mM NaCl comparison groups,
respectively. There were zero, eight, and two genes with opposite
trends in protein and mRNA expression, respectively. The genes with
differentially expressed proteins but no differentially expressed mRNA
were 40, 118, and 122, respectively, indicating that only a few
proteins were directly regulated at the transcriptional level.
Meanwhile, correlation analysis was performed for the DEPs and DEGs
with consistent expression levels in the three control groups, and the
Pearson correlation coefficients (r) were 0.977 ([100]Figure 8A), 0.833
([101]Figure 8B), and 0.881 ([102]Figure 8C), respectively. Further
analysis of the differentially expressed genes screened from the 0/500
mM NaCl treatment group ([103]Figure 8D) showed that 18 of the 32 genes
with consistent mRNA and protein expression trends were up-regulated
and 14 were down-regulated ([104]Table 2).
Figure 8.
[105]Figure 8
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Correlation analysis based on proteomics and transcriptome. (A–C)
Correlation analysis plots for different concentrations of NaCl
comparison groups, with DEP expression levels labeled on the horizontal
axis and DEG expression levels labeled on the vertical axis. (D)
Expression pattern clustering analysis of 40 differentially expressed
mRNAs and proteins. fc: fold of change. Red represents up-regulated and
green represents down-regulated.
Table 2.
DEPs and DEGs with identical expression patterns identified at the mRNA
and protein levels in the 0/500 comparison group.
Accession
Number Gene Name Gene
Log[2] Value Up/
Down Protein Fold Change Up/
Down Protein Description
[107]D3THI6 UGT71A15 −1.75 down 0.51 down UDP-glycosyltransferase 71A15
[108]Q9ZSA7 DLO2 −1.93 down 0.53 down Protein DMR6-LIKE OXYGENASE 2
[109]O24370 LOX2.1 −2.15 down 0.53 down Linoleate 13S-lipoxygenase 2-1,
chloroplastic
[110]Q7X999 RCA2 −1.58 down 0.57 down Ribulose bisphosphate
carboxylase/oxygenase activase 2, chloroplastic
[111]Q8L5A7 SOT15 −2.36 down 0.58 down Cytosolic sulfotransferase 15
[112]O49675 CCD4 −3.34 down 0.58 down Probable carotenoid cleavage
dioxygenase 4, chloroplastic
[113]P49107 PSAN −1.86 down 0.59 down Photosystem I reaction center
subunit N, chloroplastic
[114]P27522 CAB8 −1.17 down 0.59 down Chlorophyll a-b binding protein
8, chloroplastic
[115]P20152 Vim −2.17 down 0.60 down Vimentin
[116]K4BW79 EO −3.53 down 0.61 down 2-methylene-furan-3-one reductase
[117]Q9LR64 PSB27-1 −1.11 down 0.61 down Photosystem II repair protein
PSB27-H1, chloroplastic
[118]Q9SQT8 EMB3004 −2.39 down 0.64 down Bifunctional 3-dehydroquinate
dehydratase/shikimate dehydrogenase, chloroplastic
[119]Q9SSK9 MLP28 −4.00 down 0.65 down MLP-like protein 28
[120]Q9ZQI8 LTPG12 −2.27 down 0.66 down Non-specific lipid-transfer
protein-like protein At2g13820
[121]P11432 ELIP 2.88 up 1.51 up PEA early light-induced protein,
chloroplastic
[122]O49432 QRT3 1.51 up 1.52 up Polygalacturonase QRT3
[123]Q9XJ57 CHS2 1.20 up 1.53 up Chalcone synthase 2
[124]Q9SF29 SYP71 1.03 up 1.56 up Syntaxin-71
[125]Q9SR86 At3g08860 2.16 up 1.60 up Alanine--glyoxylate
aminotransferase 2 homolog 3, mitochondrial
[126]Q8L856 CYB561A 1.01 up 1.63 up Transmembrane ascorbate
ferrireductase 1
[127]Q08507 ACO3 1.09 up 1.64 up 1-aminocyclopropane-1-carboxylate
oxidase 3
[128]Q6Z1G7 Os08g42410 1.20 up 1.65 up Pyruvate dehydrogenase E1
component subunit beta-1, mitochondrial
[129]Q94JX5 WLIM1 1.10 up 1.73 up LIM domain-containing protein WLIM1
[130]Q9SXA6 ENDO1 1.79 up 1.78 up Endonuclease 1
[131]P53800 FDFT 1.02 up 1.84 up Squalene synthase
[132]A6QP05 DHRS12 1.28 up 1.90 up Dehydrogenase/reductase SDR family
member 12
[133]Q04980 LTI65 1.61 up 2.12 up Low-temperature-induced 65 kDa
protein
[134]P22242 PCC13-62 3.90 up 2.26 up Desiccation-related protein
PCC13-62
[135]Q8LPS2 ACD6 6.09 up 2.51 up Protein ACCELERATED CELL DEATH 6
[136]Q94BZ1 ZIFL1 2.80 up 2.79 up Protein ZINC-INDUCED FACILITATOR-LIKE
1
[137]Q55874 sll0103 10.12 up 3.03 up Uncharacterized protein sll0103
[138]O80433 CS 1.01 up 3.89 up Citrate synthase, mitochondrial
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Using the KEGG pathway database, pathway enrichment analysis was
performed on the DEPs with the same gene expression trend in the 0/500
comparison group to identify the major metabolic and signaling pathways
involved in the proteins. The results showed that 13 of the 32 DEPs
were distributed over 19 pathways ([140]Table 3). The DEPs were
involved in cysteine and methionine metabolism, citrate cycle (TCA
cycle), SNARE interactions in vesicular transport and photosynthesis,
etc. Through the above association analysis, some target genes that
might be related to the salt stress response of R. soongorica were
screened out, such as SYP71, CS, PCC13-62, PASN, ZIFL1, and CHS2
([141]Table 4). These differential genes may play a key role in the
molecular mechanism of salt stress response in R. soongorica.
Table 3.
KEGG classification for differential protein with the same trend of
mRNA expression change in the 0/500 comparison group as in the 0/500
comparison group.
No Gene Name Protein Description KEGG Pathway Pathway ID
1 LOX2.1 Linoleate 13S-lipoxygenase 2-1, chloroplastic Linoleic acid
metabolism ko00591
2 LOX2.1 Linoleate 13S-lipoxygenase 2-1, chloroplastic alpha-Linolenic
acid metabolism ko00592
3 CCD4 Probable carotenoid cleavage dioxygenase 4, chloroplastic
Carotenoid biosynthesis ko00906
4 PSAN Photosystem I reaction center subunit N, chloroplastic
Photosynthesis ko00195
5 CAB8 Chlorophyll a-b binding protein 8, chloroplastic
Photosynthesis—antenna proteins ko00196
6 PSB27-1 Photosystem II repair protein PSB27-H1, chloroplastic
Photosynthesis ko00195
7 EMB3004 Bifunctional 3-dehydroquinate dehydratase/shikimate
dehydrogenase, chloroplastic Phenylalanine, tyrosine, and tryptophan
biosynthesis ko00400
8 CHS2 Chalcone synthase 2 Flavonoid biosynthesis ko00941
9 CHS2 Chalcone synthase 2 Tropane, piperidine, and pyridine alkaloid
biosynthesis ko00960
10 SYP71 Syntaxin-71 SNARE interactions in vesicular transport ko04130
11 At3g08860 Alanine--glyoxylate aminotransferase 2 homolog 3,
mitochondrial Alanine, aspartate and glutamate metabolism ko00250
12 At3g08860 Alanine--glyoxylate aminotransferase 2 homolog 3,
mitochondrial Glycine, serine and threonine metabolism ko00260
13 At3g08860 Alanine--glyoxylate aminotransferase 2 homolog 3,
mitochondrial Cysteine and methionine metabolism ko00270
14 At3g08860 Alanine--glyoxylate aminotransferase 2 homolog 3,
mitochondrial Valine, leucine and isoleucine degradation ko00280
15 ACO3 1-aminocyclopropane-1-carboxylate oxidase 3 Cysteine and
methionine metabolism ko00270
16 Os08g42410 Pyruvate dehydrogenase E1 component subunit beta-1,
mitochondrial Glycolysis / Gluconeogenesis ko00010
17 Os08g42410 Pyruvate dehydrogenase E1 component subunit beta-1,
mitochondrial Citrate cycle (TCA cycle) ko00020
18 Os08g42410 Pyruvate dehydrogenase E1 component subunit beta-1,
mitochondrial Pyruvate metabolism ko00620
19 FDFT Squalene synthase Steroid biosynthesis ko00100
20 CS Citrate synthase, mitochondrial Citrate cycle (TCA cycle) ko00020
21 CS Citrate synthase, mitochondrial Glyoxylate and dicarboxylate
metabolism ko00630
22 LOX2.1 Linoleate 13S-lipoxygenase 2-1, chloroplastic Linoleic acid
metabolism ko00591
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Table 4.
Candidate genes and their role in R. soongorica tolerance in response
to salt stress.
Gene Name Gene
Up/
Down Protein
Up/
Down Protein Description Role
PSAN down down Photosystem I reaction center subunit N, chloroplastic
PSAN is a PSI-related gene, and salt stress significantly reduces the
photochemical activity of PSI and decreases photosynthetic efficiency.
This results in the down-regulation of the PSAN gene and protein
expression.
CHS2 up up Chalcone synthase 2 Up-regulates CHS2 gene and protein
expression and increases secondary metabolites to reduce salt damage.
SYP71 up up Syntaxin-71 Under salt stress, to ensure the smooth closure
of ion channels and transporters on the plasma membrane and the
separation of harmful ions during vesicular transport. By up-regulating
the expression of the SYP71 gene and protein, which is involved in the
vesicular transport pathway in leaf cells, the effect of Na^+ and
related ions on the growth of R. soongorica was mitigated.
PCC13-62 up up Desiccation-related protein PCC13-62 The high osmotic
effect of salt stress induces physiological drought in the plant root
system, and the effect of salt stress on the growth of R. soongorica is
mitigated by the up-regulation of the PCC13-62 gene and protein
expression.
ZIFL1 up up Protein ZINC-INDUCED FACILITATOR-LIKE 1 Enhanced growth
hormone distribution and signaling to regulate R. soongorica’s response
to salt stress by up-regulating the ZIFL1 gene and protein expression.
CS up up Citrate synthase, mitochondrial CS is a core enzyme of the
mitochondrial tricarboxylic acid cycle, which is an organic acid that
regulates the tricarboxylic acid cycle and directly controls cellular
functions. By up-regulating the expression of the CS gene and protein,
the adaptation of plant cells to salt stress was improved with various
metabolic processes.
[143]Open in a new tab
3. Materials and Methods
3.1. Experimental Materials and Treatment
The research subjects were R. soongorica seeds collected from natural
growing sites in Laohukou, Wuwei, Gansu, China (102°58′ E, 38°44′ N) at
the end of October 2019. The seeds were collected according to the
Technical Regulations for Seed Collection of Rare and Endangered Wild
Plants (LYT 2590-2016) and stored in a storage cabinet (CZ-250FC, Top
Yunong, Zhejiang, China) for later use. The present study was conducted
by pot culture in 2020 at the Experimental Station of Longqu Seed
Orchard, Gansu Province Academy of Qilian Water Resource Conservation
Forests Research, in Zhangye, Gansu, China. In April 2020, seeds of the
same full size were selected, disinfected with 0.3% KMnO[4] solution
for 15 min, rinsed 5 times with deionized water, and planted in a plug
tray with a diameter of 4.5 cm and a height of 8.5 cm. The culture
medium was vegetative soil, quartz sand, and vermiculite (3:1:1), and
three seeds were planted in each plug tray. The seedlings were then
grown in a greenhouse at 25 ± 1 °C, 50% humidity, natural ventilation,
and good lighting. They were regularly irrigated with groundwater. On
15 June 2020, the uniformly sized R. soongorica seedlings were
carefully removed from the plug trays, transferred to plastic pots (20
× 23 × 25 cm) with 2.5 kg of soil, and then grown in the greenhouse.
The available phosphorus, salinity, and pH of the tested soil were 26.6
mg/kg, 0.2%, and 8.3, respectively. The smart irrigation control
systems were used to maintain the soil water content close to the field
capacity (60%). The R. soongorica seedlings were planted in a total of
1000 pots (4 seedlings per pot). After growing the seedlings for 40 d,
720 pots of seedlings with relatively uniform growth were selected as
experimental material. The R. soongorica plants were subjected to the
following six salt treatments: NaCl concentrations of 0, 100, 200, 300,
400, and 500 (mM). Four blocks of the same NaCl treatment were
performed (morphological, physiological, transcriptomic, proteomic) and
each NaCl treatment concentration was replicated on 10 pots per and
three biological replicates were performed, using a total of 180 pots
per block.
According to the experimental design, the corresponding NaCl solution
was prepared with deionized water, and the NaCl solution was poured
evenly around the root of R. soongorica with a syringe (to make sure
that there was no permeability phenomenon when the prepared NaCl
solutions were completely poured into the flowerpot). In order to avoid
osmotic shock caused by salt shock reaction, the target concentration
was reached within 24 h by gradual application of salt. Corresponding
indices were determined after NaCl treatment for 24, 72, 144, and 216
h, respectively. A total of 5 g of leaves from each treatment was
rapidly frozen in liquid nitrogen and then stored in an ultra-low
temperature refrigerator (−80 °C) for proteome and transcriptome
determination.
3.2. Determination of Morphological and Physiological Indicators
After 24, 72, 144, and 216 h of salt treatment, 3 seedlings were
randomly selected from each replicate of each treatment, and a total of
9 seedlings were gently straightened. Plant height and root length were
measured with a ruler (measuring range: 20 cm, accuracy: 0.1 cm) and
averaged.
The soluble sugar content of R. soongorica leaves was determined using
the methods described by Tan et al. [[144]23]. Briefly, 0.1 g of R.
soongorica leaves were weighed and placed in a 20 mL glass tube with a
stopper, 10 mL of distilled water was added, the extract was extracted
in boiling water for 30 min, the extract was filtered into a 25 mL
volumetric flask, and the volume was kept constant. A total of 0.5 mL
of the sample extract was absorbed into a 20 mL scale tube; 1.5 mL of
distilled water was added; 0.5 mL of anthrone ethyl acetate reagent and
5 mL of concentrated sulfuric acid were added to the tube, shaken well,
and cooled to room temperature, and the absorbance value was measured
at a wavelength of 630 nm.
[MATH:
Soluble sugar
content (μg⋅g−1)=C⋅V⋅NVt⋅W×100% :MATH]
where
[MATH: C :MATH]
represents the glucose content determined from the standard curve (
[MATH: µg :MATH]
);
[MATH: V :MATH]
is the total volume of the extract (mL);
[MATH: N :MATH]
is the dilution ratio;
[MATH: Vt :MATH]
represents the amount of sample added during the determination (mL);
[MATH: W :MATH]
represents the fresh weight of the sample (g).
The salt tolerance index (STI) was calculated according to the method
of Roshdy et al. [[145]24]. The formula is as follows:
[MATH:
STI=DWNacl/<
mrow>DWcontrast×100%
:MATH]
where
[MATH:
DWNaCl :MATH]
represents the dry weight of plants under salt treatment (g);
[MATH:
DWcontrast :MATH]
represents the dry weight of control plants (g).
3.3. RNA Sample Preparation and Transcriptome Analyses
Differential gene analysis and identification of R. soongorica leaves
was performed according to the method described by Anders et al.
[[146]25] with some modifications. Briefly, total RNA was extracted
from the collected 50 mg of R. soongorica leaves using the plant RNA
purification kit (Norgen, Thorold, ON, Canada) according to the
manufacturer’s instructions. The quality of total RNA was then measured
using an Agilent 2100 Bioanalyzer (Agilent, Santa Clara, CA, USA).
Oligo (dT) magnetic beads (Biomag, Wuxi, China) were used to enrich
mRNA with PolyA structure in total RNA, and the mRNA was cleaved into
200−300 bp fragments by ion disruption. Using the RNA as a template,
the first strand cDNA was synthesized using 6-base random primers
(Gdsbio, Guangzhou, China) and reverse transcriptase (Aidlab, Beijing,
China). The first strand cDNA was used as a template to synthesize the
second strand cDNA, and the library size was 300–400 bp. Quality
control was performed by Agilent 2100 Bioanalyzer, and double-terminal
sequencing was performed by Illumina HiSeqTM2000 (NGS Solexa Hiseq2000,
Illumina, CA, USA). All the above tests were performed by Suzhou
Panomico Biotechnology Co., LTD.
RNA-Seq raw sequencing data were converted by invoking Base, followed
by quality control of the raw reads. Cutadapt 1.16 software was used to
remove the original data to obtain clean reads, and Trinity 2.5.1
software (Broad Institute, Hebrew University of Jerusalem, Jerusalem,
IL) was used to splice clean reads to obtain transcripts. The longest
transcript under each gene is extracted as the representative sequence
of the gene after splicing, called the unigene. The unigene was used as
the reference sequence for subsequent analysis. Clean reads for each
gene were calculated and normalized to reads per kilobase per million
reads (RPKM) for gene expression analysis. Differential analysis of
gene expression was performed by DESeq screening for differentially
expressed genes with the following conditions: multiple expression
differences |log2FoldChange| > 1, significance p-value < 0.05.
Meanwhile, to verify the reliability of the transcriptome data, we
randomly selected 10 differential genes with significant changes in
expression for quantitative real-time PCR (qRT-PCR) analysis in the A
vs. B and A vs. C comparison groups, respectively. Specific primers
were designed using Primer 3.0 software ([147]Table S1) and synthesized
by Sangon Biotech (Shanghai) Co., Ltd. The internal reference gene used
was “DN11735_c0_g2”. Sample RNA was extracted using the Plant Total RNA
Extraction Kit (DP-437) (Tiangen, Beijing, China). cDNA synthesis was
performed using the PrimeScript™ RT Master Mix (Perfect Real Time) Kit
(TaKaRa, Dalian, China), and the instructions for experimental
procedures were followed. The qRT-PCR program was 95 °C for 30 s, 95 °C
for 5 s, 60 °C for 30 s, 95 °C for 5 s, 60 °C for 60 s, and 50 °C for
30 s, for a total of 40 cycles. The experiment was subjected to three
biological replications. The relative expression of each gene was
calculated using the 2^−ΔΔCt method. The results showed that the
expression trends of the 20 differential genes selected from R.
soongorica leaves were highly correlated with the RNA-Seq results
([148]Table S2). This indicates that the transcriptome data are
reliable.
3.4. Protein Sample Preparation and Proteomic Analysis
Proteins were extracted from 2 g of R. soongorica leaves according to
the method of Chen et al. [[149]26], protein quality was detected by
sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE),
and protein samples were stored in a refrigerator at −80 °C until use.
The tandem mass tag (TMT) assay was performed by Suzhou Panomic
Biotechnology Co., LTD. according to the manufacturer’s recommendations
(Applied Biosystems, Foster City, CA, USA). Briefly, 200 mL of protein
lysates were taken from each sample for typing digestion, and then the
peptides were labeled by TMT. The labeled groups were mixed and the
mixed peptides were pre-separated by strong cation exchange
chromatography. The liquid phase was separated on a SCX column after
vacuum drying. Then, mass spectrometry (LC-MS/MS) (Applied Protein
Technology, Shanghai, China) based on Orbitrap Fusion Lumos (Thermo
Fisher Scientific, Waltham, MA, USA) was performed. Peak identification
was performed on the original documents of mass spectrometry to obtain
the peak list, and then the reference database was established, and the
peptides and proteins were identified. In this study, the screening
conditions of differentially expressed proteins were as follows: when
the protein difference multiple was >1.5 or <0.66, the significance
p-value < 0.05 was used as the screening condition for differential
proteins.
3.5. Statistical and Bioinformatic Analysis
Statistical analyses were performed using SPSS 19 software. All data
are expressed as mean ± standard error (SE) of three independent
replicates. Significant mean differences between treatments were
performed by one-way analysis of variance based on Duncan’s multiple
range test at the level of p ≤ 0.05. Blast2go 2.5.0 software was used
for Gene Ontology (GO) annotation analysis of the identified
differential genes/proteins. During the analysis, the gene list and
gene number of each term were calculated using the differential genes
annotated by the GO term. Then, the p-value was calculated by the
hypergeometric distribution method. The threshold for significant
enrichment was set at p-value < 0.05. Kobas 3.0 software was used for
pathway enrichment analysis of the identified genes/proteins in the
Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database, with a
p-value < 0.05 as the screening criterion for significant enrichment.
Blast comparison was performed between the identified protein sequences
and the GO and KEGG background databases, respectively. Arabidopsis was
confirmed as the species with the best comparison results, and the
protein information of the mutual comparison was determined. Therefore,
the comparative protein information of Arabidopsis was used for the
subsequent functional enrichment analysis. The expression patterns of
DEPs and DEGs were hierarchically clustered using the MultiExperiment
Viewer (MeV) software version 4.9.0 [[150]27]. The relative ratios of
DEPs and DEGs were subjected to log[2] transformation, the Euclidean
distance similarity metric was used to define similarity, and
hierarchical clusters were assembled using the complete linkage
clustering method. The clustering results were visualized by MeV 4.9.0
software.
3.6. Integrative Transcriptome-Proteome Analysis
The integrated transcriptome-proteome analysis calculates Pearson
correlation coefficients (r) from the fold change of expressed
transcripts and proteins to assess the correlation between the
expression levels of specific transcripts and proteins in the
transcriptome and proteome profiles of the samples [[151]28].
4. Discussion
The occurrence of soil salinization has been further exacerbated by
changes in climatic conditions, such as global warming and increased
drought [[152]29]. As one of the most detrimental factors among abiotic
stresses, salt stress has disrupted normal physiological metabolic
processes in plants, causing severe growth dysfunction in
photosynthesis, protein synthesis, and energy metabolism [[153]30].
Meanwhile, the maintenance of plant growth is directly related to the
salt tolerance of plants [[154]31]. In saline environments, halophytes
can employ a variety of morphological and physiological adaptation
strategies to reduce the excessive production of salt ions [[155]32].
For example, a study of Halogeton glomeratus found that its optimal
growth occurred under conditions of approximately 100 mM NaCl; however,
it began to decline at higher salinities [[156]11]. Rahman et al.
[[157]33] reported that salinity significantly reduced the growth and
development of Achras sapota, which was accompanied by a significant
decrease in plant height, root length, and plant STI. In the present
study, after 72 h of NaCl stress, the plant height and root length of
R. soongorica seedlings first increased and then decreased with
increasing NaCl concentration, and the highest values were found at a
200 mM NaCl concentration. However, when the NaCl concentration
exceeded 200 mM, plant height and root length decreased with increasing
NaCl concentration. This result is consistent with the findings of Wang
et al. [[158]11], but different from those of Rahman et al. [[159]33].
This difference in results is most likely due to the different
salt-adaptation strategies of the species. First of all, R. soongorica
and Halogeton glomeratus have been identified as salt-tolerant plants
and the growing areas are mainly distributed in northwestern China
[[160]11,[161]19], while Achras sapota is mainly a fruit tree native to
Central America and Mexico [[162]33]. At the same time, the main
salt-adaptation mechanism in H. glomeratus is the translocation of
sodium and some toxic ions into specific salt storage cells in the
leaves, which is the same role of the specially organized salt glands
in the leaves of R. soongorica [[163]19]. In contrast, the
salt-adaptation strategy of A. sapota is to retain sodium ions in the
roots and accumulate compatible solutes to mitigate salt-toxic effects.
Finally, it was found that both R. soongorica and H. glomeratus
possessed good salt-adapted growth at less than 200 mM NaCl stress
based on the data, while A. sapota showed a positive correlation of
growth indicators with concentration when based on salt stress. At the
same time, this study found that when treated with NaCl for 24 h, the
soluble sugar content gradually decreased with increasing treatment
concentration. When treated with NaCl for 72 h, the soluble sugar
content gradually increased with increasing treatment concentration,
had the maximum increase after 144 h, and then remained at a high
level. This is consistent with the changes in soluble sugar content in
R. soongorica leaves after different times and concentrations of NaCl
treatment by Yang et al. [[164]34], which may be due to the fact that
soluble sugar was mainly used as an energy source to ensure the normal
growth of R. soongorica in the early stages of NaCl treatment. With the
prolongation of NaCl treatment time, the intracellular ion content
increased, and soluble sugar was mainly used as an osmotic adjustment
substance to maintain the osmotic balance of cells to ensure the growth
of cells under salt stress.
In this study, the trends of gene expression and protein levels in R.
soongorica leaves under different salt treatments (0, 200, and 500 mM
NaCl) were analyzed. More differential genes and proteins were found in
the 0/500 compared group. Meanwhile, the results of DEG and DEP
analysis showed that the number of down-regulated genes was greater
than that of up-regulated genes, while slightly more up-regulated
proteins were identified.
Through association analysis of transcriptomic and proteomic data, the
internal relationship between genes and proteins can be deeply
understood, which is of great significance in mining reliable genes for
plant breeding and improvement [[165]35]. Jiang et al. [[166]27]
performed correlation analysis on the transcriptome and proteome of
cucumber seedlings treated with H[2]S under salt stress. The results
showed that the correlation coefficient of differentially expressed
proteins and genes with the same trend of change under H[2]S treatment
was 0.839, and most of the associated differential proteins were
enriched in photosynthesis, cysteine metabolism, and energy metabolism.
Ding et al. [[167]36] analyzed tomato (Solanum lycopersicum) leaves
under stress conditions by combining transcriptome and proteome and
found 79 differential proteins with the same expression trend of the
transcriptome, most of which were related to stress response and
protein folding. In this study, transcriptome and proteome association
analysis was performed on three comparison groups (0/200, 200/500, and
0/500) of R. soongorica leaves after 72 h of NaCl stress. After
screening, only a small number of R. soongorica DEPs are consistent
with the mRNA expression level. Correlation analysis revealed that DEPs
and DEGs with consistent expression levels in the three control groups
had a Pearson correlation > 8. This is because the transcription of DNA
into mRNA and the translation of mRNA into proteins are affected by a
variety of transcriptional, translational, and post-translational
factors, including changes in the amount of transcribed mRNA and in the
amount and function of proteins. This indicates that only a few
proteins are directly regulated at the transcriptional level. Thus, the
screened R. soongorica DEPs and DEGs showed a strong positive
correlation with each other based on the number of their expression
levels and their similar expression. Further analysis revealed that the
number of genes with consistent transcriptome and proteome expression
was significantly higher in the 0/500 comparison group (32) than in the
0/200 comparison group (5) and the 200/500 comparison group (10).
Therefore, the 0/500 comparison group was focused as a study and
further study revealed 32 differential proteins distributed in 19
metabolic pathways. It mainly involves cysteine and methionine
metabolism, TCA cycle, SNARE interactions in vesicular transport,
metabolism, etc. This further showed that SYP71, CS, ZIFL1, PCC13-62,
PASN, and CHS2 genes may play an important role in the molecular
mechanism of R. soongorica response to salt stress.
SNARE factors are divided into Q-SNARE and R-SNARE [[168]37]. When
plants are exposed to adverse conditions, a large number of SNARE
proteins are required to mediate the membrane fusion mechanism during
vesicle trafficking to ensure the smooth closure of ion channels and
transporters on the plasma membrane and the separation of harmful ions
[[169]38]. For example, the expression levels of R-SNARE VAMP7-type,
QC-SNARE, and Qb/c-SNARE were significantly increased in tomatoes under
salt stress [[170]39], suggesting that the SNARE-mediated vesicle
trafficking pathway plays an important role in the salt stress
response. The SYP7 family is a plant-specific family of QC-SNARE
proteins consisting mainly of SYP71, SYP72, and SYP73 homologous
proteins. [[171]40]. Rice showed stronger antioxidant and disease
resistance by overexpressing the SYP71 protein [[172]41]. In this
study, it was found that the expression levels of the SYP71 gene and
protein were significantly up-regulated in R. soongorica leaves after
the 500 mM NaCl treatment, suggesting that SYP71 may be involved in the
vesicle transport pathway in leaf cells and thus play an important role
in the response to salt stress in R. soongorica leaves. Citrate
synthase (CS) is the core enzyme of the mitochondrial TCA cycle and an
organic acid that regulates the TCA cycle, which directly controls
cellular function [[173]42]. The adaptation of plant cells to salt
stress is closely related to various metabolic processes [[174]43]. CS
can improve plant tolerance to saline-alkali soil [[175]44]. Similar to
NaCl-treated Zea mays [[176]45] and Haloxylon salicornicum [[177]46],
high NaCl stress significantly increased the abundance of citrate
synthase in R. soongorica. The abundance of the CS gene was also
significantly increased in this study, indicating that CS is a key
protein of R. soongorica in response to salt stress.
Salt stress in plants is regulated by many signaling molecules, and
auxin is a key medium for plants to respond to salt stress [[178]11],
which plays an important role in plant development and salt stress.
Studies have shown that salt stress significantly disrupts auxin
homeostasis and distribution in primary roots and inhibits auxin
signaling [[179]47]. Auxin treatment can significantly restore the
growth of Arabidopsis’s primary roots under salt stress [[180]48]. The
above results indicate that the distribution and signaling of auxin
mediate the response of plants to salt stress. ABC and MFS are two
families of transporters in the plant kingdom. Zinc-induced
facilitator-like 1 (ZIFL1), a member of the MFS family, is critical for
auxin transport [[181]49]. Overexpression of ZIF1 can enhance auxin
transport and improve stress tolerance in Arabidopsis [[182]50]. The
dehydration-related protein PCC13-62 can improve plant tolerance to
extreme drought [[183]51]. Li et al. [[184]52] found that the
expression of PCC13-62 in upland cotton was up-regulated under salt
stress based on iTRAQ proteomics techniques. In addition, Giarola et
al. [[185]53] also found that salt stress could activate the PCC13-62
promoter and increase the tolerance of Arabidopsis to salt stress. The
results of this study showed that after 500 mM NaCl treatment, the
abundance of ZIFL1 and PCC13-62 significantly increased, suggesting
that the leaves of R. soongorica could enhance the tolerance to salt
stress by up-regulating the expression of ZIFL1 and PCC13-62.
Meanwhile, our study also found that the expression of PSAN in R.
soongorica leaves decreased under salt stress. PSAN is a PSI-related
gene, and salt stress can significantly reduce the photochemical
activity of PSI, ultimately leading to lower photosynthetic efficiency
[[186]54]. This is consistent with the findings on photoinhibition of
Cinnamomum camphora L. by NaCl stress [[187]55], where salinity
resulted in the down-regulation of protein expression located on PSI
(PSAN). The expression of the PASN gene and protein in this study also
showed the same trend of down-regulation. The results showed that PSAN
may play a key role in the molecular mechanism of R. soongorica’s
response to salt stress.
Polyketide synthases (PKSs) are a family of multifunctional proteins
that exhibit remarkable versatility in structural fusion and functional
organization to produce different classes of compounds. Structurally,
chalcone synthase (CHS) is considered to be the simplest type III PKS.
This enzyme is also known to catalyze the first step of the
flavonoid/isoflavone pathway [[188]56]. Flavonoids, an important
secondary metabolite, are closely related to the antioxidant capacity
of plants [[189]13]. Since chalcone synthase is the first enzyme in the
flavonoid biosynthetic pathway, its expression and regulation are
important [[190]57]. The significant enrichment of CHS protein in
Pongamia roots under salt treatment contributes to the protection of
Pongamia with high antioxidant activity from ROS damage and promotes
root growth under high salt stress [[191]58]. The results of this study
showed that the abundance of CHS2 was significantly increased after the
500 mM NaCl treatment, indicating that R. soongorica could be used to
increase secondary metabolites to mitigate salt damage by up-regulating
the expression of CHS2.
5. Conclusions
The effects of different salt concentrations and treatment times on the
morphology and physiological indices of R. soongorica were studied. It
was found that low NaCl treatment (100, 200 mM) promoted the growth of
R. soongorica, while high NaCl treatment (400, 500 mM) inhibited its
growth. At the early stage of treatment (24 h), the soluble sugar
content in the leaves of R. soongorica decreased with the increase in
NaCl concentration, which provided an energy source for the smooth
progress of various metabolisms. After 72 h of treatment, it increased
with the increase in NaCl treatment concentration and then remained at
a higher level as an osmotic regulator to maintain osmotic balance in
vivo. When treated with 200 mM NaCl for 72 h, R. soongorica seedlings
showed the strongest salt tolerance. Furthermore, the molecular
mechanism of R. soongorica leaves was investigated under normal culture
(0 mM NaCl) and salt stress treatment (200, 500 mM NaCl) for 72 h.
Through transcriptome and proteome association analysis, 40
differential proteins with the same expression trend of differential
genes were identified, among which 25 were up-regulated and 15 were
down-regulated, and finally, SYP71, CS, PCC13-62, PASN, ZIFL1, CHS2,
and other genes were found to be potential target genes for salt
tolerance of R. soongorica. This study laid a theoretical foundation
for further understanding the molecular mechanism of R. soongorica in
response to salt stress.
Supplementary Materials
The following supporting information can be downloaded at:
[192]https://www.mdpi.com/article/10.3390/plants12203542/s1, Table S1:
Selected genes and their primers in the A vs. B and A vs. C comparison
groups; Figure S1: Expression correlation analysis of differential
genes in RNA-Seq and qRT-PCR results; Table S2: Expression correlation
analysis of differential genes in RNA-Seq and qRT-PCR results; Table
S3: Result of RNA-Seq expression profile sequencing; Table S4:
Differentially expressed genes in the transcriptome of Reaumuria
soongorica leaves; Table S5: Differentially expressed proteins in the
proteome of Reaumuria soongorica leaves; Table S6: Types of protein and
mRNA expression changes.
[193]Click here for additional data file.^ (1.3MB, zip)
Author Contributions
All authors contributed to the conception and design of the study.
Material preparation, data collection, and analysis were performed by
H.L., S.Y., P.C., Z.L., X.B. and B.T. The first draft of the manuscript
was written by H.L. and all authors commented on earlier versions of
the manuscript. All authors have read and agreed to the published
version of the manuscript.
Data Availability Statement
The dataset generated in this study is available under NCBI SRA
accession number PRJNA977833, while the mass spectrometry proteomics
data have been deposited on ProteomeXchange under accession number
PXD042784. Other data are in the [194]supplementary document.
Conflicts of Interest
The authors declare no conflict of interest.
Funding Statement
This study was supported by the National Natural Foundation of China
(32160407); the Gansu Provincial Key Research and Development Program
(23YFFA0065); the Grass Industry Open Project (KLGE202215); the
Outstanding Doctoral Projects Funded by Gansu Provincial Science and
Technology Program (23JRRA1451); the Postgraduate Innovation Star
Project (2023CXZX-643).
Footnotes
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referred to in the content.
References