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. 2018 Jul 16;8(8):320. doi: 10.1007/s13205-018-1352-6

Transcriptome analysis of abscisic acid induced 20E regulation in suspension Ajuga lobata cells

Yan-chen Wang 1, Yue-yue Yang 1, De-fu Chi 1,✉
PMCID: PMC6047952  PMID: 30034984

Abstract

Ajuga lobata D. Don is a medicinal plant rich in 20-hydroxyecdysone (20E), alkaloids, and other active substances. In this study, the cell suspension was incubated for 7 days, followed by the analysis on the effects of abscisic acid (ABA) on the regulation of 20E synthesis. Then A. lobata suspension cells treated with 0.15 mg/l ABA were used as material, with the Illumina technology applied for transcriptome sequencing. Digital analysis on the gene expression profile was carried out on ABA treated and control samples, respectively. Finally, transcriptomics was applied to assess the molecular response of A. lobata induced by ABA through applying transcriptomics by evaluating differentially expressed genes. The results suggested that ABA promoted 20E accumulation, while longer processing time caused cell browning. A total of 154 genes were significantly regulated after ABA treatment, with 99 up-regulated and 55 down-regulated, respectively. In addition to 20E-related pathways, the genes belonged to the ko00900 (terpenoid backbone biosynthesis) pathway (six differentially expressed genes [DEGs]), ko00100 (steroid biosynthesis) pathway (four DEGs), and ko00140 (steroid hormone biosynthesis) pathway (six DEGs). Providing a better understanding of the 20E biosynthetic pathway and its regulation, in particular in plants, this study is necessary.

Keywords: Ajuga lobata D. Don, Cell suspension, 20-Hydroxyecdysone, Transcriptomics, Gene expression

Introduction

Ajuga lobata D. Don belongs to Lamiaceae in the order of Lamiales; Originating from the United States of America, it is mainly distributed in the southern part of China (Coll et al. 2007; Coll and Tandron 2008). A. lobata is a medicinal plant rich in sterones, alkaloids and other active substances; it is used for the treatment of inflammation, blood pressure, detoxification heat (Guo et al. 2005; Xiong et al. 2012; Cai et al. 2014). Ajuga contains 20-hydroxyecdysone (20E), which is the molting hormone of most arthropods, distributed in the plant kingdom and can be used as insecticide and insect growth regulator (Fekete et al. 2004; Rharrabe et al. 2009). It was demonstrated that 20E could cause deformity of larva or pupa in insects, resulting in death; in addition, it could impose antifeedant effects on insects as well (Ufimtsev et al. 2003; Marion-Poll et al. 2005; Selvaraj et al. 2007).

The commercial anabolic preparations and 20E supply for agricultural and therapeutic uses are mainly extracted from collected wild plants making it necessary to develop more reliable and sustainable means for 20E production and other bioactive ecdysteroids. Plant tissue and cell cultures can be alternatively used for the production of ecdysteroids (Lev et al. 1990; Wang et al. 2013).

The structure of 20-hydroxyecdysone is characterized by a cis-A/B ring junction, a 7-en-6-one conjugated system, and polyhydroxyl groups. Accumulated evidences in insects suggest that 20-hydroxyecdysone is biosynthesized from cholesterol via 7-dehydrocholesterol and 3β, 14α-dihydroxy-5β-cholest-7-en-6-one (5β-ketodiol) (Fujtmoto et al. 1997).

It was recently proposed that 3β-hydroxy-5β-cholestan-6-one (5β-ketone) was involved in 20HE biosynthesis in the hairy roots of Ajuga reptans var. atropurpurea (Lamiaceae) (Fujimoto et al. 2015). Cholesterol was converted to the 5β-ketone with the migration of hydrogen from the C-6 to the C-5 position. These findings, along with the previous observation that the ketone was efficiently converted to 20-hydroxyecdysone, strongly suggest that the 5β-ketone is an intermediate immediately formed after cholesterol during 20-hydroxyecdysone biosynthesis in Ajuga sp. (Fujimoto et al. 2015).

It was shown that CYP71D443 has C-22 hydroxylation activity for the 5β-ketone substrate through a yeast expression system. The hydroxylated product, 22-hydroxy-5β ketone, had a 22R configuration in agreement with that of 20E. Furthermore, labeling experiments indicated that (22R)-22-hydroxy-5β-ketone could be converted to 20E in Ajuga hairy roots. Based on those results, a possible 20E biosynthetic pathway in Ajuga plants involved CYP71D443 is proposed (Tsukagoshi et al. 2016).

In contrast to the ability of synthesizing the cholesterol de novo of vertebrate animals and plant, insects must obtain steroid precursor from their diet, which is attributed to the absence of the enzymes involved in squalene synthesis (Kircher 1982; Iga and Kataoka 2012). Carnivorous insects can take cholesterol directly from their prey, whereas in phytophagous insects, phytosterols are the first dealkylated to cholesterol (Gilbert et al. 2002; Gilbert and Warren 2005).

However, it has been proposed that the mechanism of the construction of the characteristic 5β-H-7-en-6-one structure is different in insects and plants (Davies et al. 1980, 1981; Nagakari et al. 1994). It is generally accepted that 7-dehydrocholesterol is derived from cholesterol of insects (Sakurai et al. 1986). Accumulated evidences indicate that the biosynthesis of ecdysone in the prothoracic gland of insects proceeds via 7-dehydrocholesterol and 3β,14α-dihydroxy-5β-cholest-7-en-6-one (ketodiol), followed by the successive hydroxylation at C-25, C-22 and C-2 to yield ecdysone of Ketodiol, which is converted into 20-hydroxyecdysone in peripheral tissues such as the fat-body (Rees 1995; Huang et al. 2008).

The genes encoding the P450 enzymes that catalyze these hydroxylations have been characterized in insects (Huang et al. 2008). Conversion of cholesterol into 7-dehydrocholesterol (7dC) is mediated by a Rieske oxygenase Neverland (Yoshiyama et al. 2006; Yoshiyama-Yanagawa et al. 2011).

In Drosophila melanogaster and Bombyx mori, it has been proven that CYP307A1/A2 (Spook/Spookier, Spo/Spok) and CYP6T3 will be involved in the conversion of 7-dehydrocholesterol into 2,22,25-trideoxyecdysone (ketodiol). Moreover, a paralog Spookiest (Spot, CYP307B1) was also found in CYP307 family (Gilbert and Warren 2005; Namiki et al. 2005; Ono et al. 2006; Ou et al. 2011). In contrast, the biosynthetic mechanism of 20-hydroxyecdysone in plants is much less acknowledged than that in insects (Festucci-Buselli et al. 2008). It was shown that hydroxylation of ecdysone at the C-20 position to form 20E is a cytochrome P450-dependent reaction occurring predominantly in the microsomal fraction in spinach (Spinacia oleracea) leaves (Grebenok et al. 1996). The early step mechanism in Ajuga hairy roots may distinct from that of insects (Lockley et al. 1975; Davies et al. 1981). Ajuga hairy roots are capable of introducing a double bond at the 7-position at the late stage of 20-hydroxyecdysone biosynthesis, suggesting the possibility of an alternative biosynthetic pathway without the involvement of 7-dehydrocholesterol as an obligatory intermediate (Hyodo and Fujimoto 2000).

20-Hydroxyecdysone biosynthesis is mainly through mevalonate (MVA) and DOXP/MEP pathways, in which the former pathway, as a major plant synthetic pathway begins with acetyl CoA condensation, followed by reduction to mevalonate, resulting in the production of steroid ketones and terpenes. Meanwhile, the latter pathway utilizes pyruvic acid and GA-3P as the starting substrates to produce terpenes. Although isopentenyl pyrophosphate (IPP) and its isomer dimethylallyl pyrophosphate (DMAPP) are intermediate products in both pathways, the mechanisms by which DMAPP and IPP are synthesized are different, so is the intracellular locations of metabolic end products (Adler and Grebenok 1995; Báthori and Pongrácz 2005; Ma et al. 2006).This synthetic pathway is complex with many compounds involved in it, but the specific synthesis pathway of 20E remains unclear (Dinan 2001).

Cholesterol and lathosterol are first metabolized into 7-dehydrocholesterol, followed by the conversion into 20-hydroxyecdysone via 7-dehydrocholesterol 5α, 6α-epoxide in the hairy roots of A. reptans var. atropurpurea (Ohyama et al. 1999). It is generally accepted, both in insects and plants, that the early stage of biosynthesis of 20-hydroxyecdysone from cholesterol yields an intermediate with a cis-A/B ring structure, which is then hydroxylated at the C-2, -20, -22 and -25 positions to furnish. It was reported that C-20, C-22 and C-25 hydroxylations were catalyzed by P450 mono-oxygenase enzymes, whereas a different type mono-oxygenase was responsible for C-2 hydroxylation (Nakagawa et al. 1997).

It was suggested that CYP307A1, CYP307A2 and non-molting glossy/shroud (a short-chain dehydrogenase/reductase) should be involved in the conversion of 7-dehydrocholesterol to 5b-ketodiol (Namiki et al. 2005; Rewitz et al. 2007; Niwa et al. 2010). Functioning as a carbon 25 hydroxylase CYP306A1 plays an essential role in ecdysteroid biosynthesis during insect development, which converts ketodiol into ketotriol via carbon 25 hydroxylation (Niwa et al. 2004). Cytochrome P450 enzymes catalyzing the final steps of ecdysteroid biosynthesis have been identified by mutations in the ‘‘Halloween’’ gene family of D. melanogaster: phantom (CYP306a1; 25-hydroxylase), disembodied (CYP302a1; 22-hydroxylase); shadow (CYP315a1; 2-hydroxylase); and shade (CYP314a1; 20-hydroxylase) (Chavez et al. 2000; Gilbert et al. 2002; Warren et al. 2002, 2004; Petryk et al. 2003; Gilbert 2004; Niwa et al. 2004). The hydroxylation at C25 is mediated by CYP306A1 (Phantom: Phm) located in the endoplasmic reticulum, followed by hydroxylations at C22 and C2 carried out in the mitochondria by CYP302A1 (Disembodied: Dib) and CYP315A1 (Shadow: Sad), respectively (Gilbert and Warren 2005). Final conversion of E to 20E is catalyzed by a fourth hydroxylase, CYP314A1 (Shade: Shd, the ecdysone 20-monooxygenase), variously located in the endoplasmic reticulum and the mitochondria of peripheral target tissues (Petryk et al. 2003).

Abscisic acid could regulate plant dormancy, flowering, maturity, aging and stomatal movement (Cutler et al. 2009), exerting inhibitory effects on cell growth and extension (Hansen and Grossmann 2000). ABA is also considered a stress hormone, the content of which rises under environmental stress, initiating the defense system to enhance plant resistance (Anderson et al. 1994; Hauser et al. 2011; Ren et al. 2012). In recent years, studies have shown that ABA regulates and stimulates the production of secondary metabolites such as chlorogenic acid, phenols, flavonoids and terpenoid substances (Sandhu et al. 2011; Buran et al. 2012). The up-regulation expression of 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR) are involved in the biosynthesis under the treatment of various elicitors, such as methyl jasmonate (MeJA) or AgNO3, which are responsible for 20E accumulation in cell cultures of Cyanotis arachnoidea (Wang et al. 2014).

In contrast, little is known about the last few steps of planting 20E biosynthesis, and no biosynthetic 20E gene about those steps has been reported thus far (Tsukagoshi et al. 2016). It is based on the establishment of a preliminary suspension culture system of A. lobata (Zhao et al. 2011; Li et al. 2013). Through identifying key genes of the 20E synthesis pathway and assessing their corresponding expression variability after adding exogenous ABA, the study aims to explore the mechanism by which exogenous ABA affects 20E synthesis.

A better understanding of the 20E biosynthetic pathway and its regulation, in particular in plants, is necessary. This is the first report about the isolation, characterization of a novel HMGR gene and the establishment of A. lobata cell suspension cultures for 20E production.

Materials and methods

Materials

The A. lobata cell suspension culture system was established by Insect laboratory of Northeast Forestry University and the suspension culture callus was used as the experimental material.

Methods

A. lobata suspension cell culture and screening for optimal ABA concentration

The basic liquid medium for A. lobata cell suspension culture was Murashige and Skoog culture medium (MS), 2,4-dichlorophenoxyacetic acid (2,4-D) 0.4 mg/l. The pH was adjusted to 5.8, with an inoculation ratio of 10% (5 g cells in 50 ml medium). Cells were cultured under a 16/8-h light/dark cycle with 2000-l× light intensity at 25 °C and 70% humidity, with culture flasks shaken at 120–130 rpm (Zhao et al. 2011; Li et al. 2013).

ABA was added to the suspension culture system at the seventh day after inoculation of A. lobata cells. Based on previous experiments, ABA concentrations in the suspension cultures were set at 0.05, 0.1, 0.15, and 0.2 mg/l, respectively, followed by the screen of the optimum concentration of ABA for 20E accumulation. Sampling was carried out every 24 h after ABA addition and 5 parallel samples were collected for each treatment.

Extraction and quantitation of 20E

20E content was assessed by high-performance liquid chromatography (HPLC). A. lobata cells were dried at 60 °C in a high temperature drying oven for 12 h, followed by the operation of soaking 0.2 g dry suspension cell in 5 ml methanol for 24 h, the sonicating for 1 h at 40 kHz (YH-200DH, produced by YUHAO in China), and digested with a microwave digestion system (WT-8000, Shanghai YaRong biochemical instrument factory, conditions: T = 50 °C, p = 2 P0, T = 10 min, W = 300 × 2). The digestion mixtures were filtered using organic filtration membrane. The filtrates were analyzed by HPLC (American, Waters Company) with the following conditions: UV–visible detection wave length range, 190–800 nm; detection wavelength, 242 nm; mobile phase, 1:1 formal dehyde: water; mobile phase flow rate, 0.8 ml/min; injection volume, 10 µl. Samples (5 per treatment group) were collected every 24 h; detection of each standard was repeated 3 times.

20E standards with concentrations of 0.8, 0.4, 0.2, 0.1, and 0.05 g/l were prepared. With average peak area as ordinate and mass concentration as abscissa, a regression equation for 20E was obtained (y = 18498 + 226.2x, R2 = 0.999).

cDNA library construction and transcriptome analysis

Suspension A. lobata cell scultured under the optimal ABA concentration, were screened as described above, with the collection of samples at 48 h after addition of ABA, for of cDNA library construction and transcriptome analysis. In the control group, suspension A. lobata cells were cultured in basic liquid medium. Three samples were collected from untreated or treated suspension A. lobata cells, respectively, mixed and kept separately, and used in subsequent experiments.

Total RNA was isolated from mixed samples using TRIzol reagent according to the manufacturer’s instructions. Transcriptome sequencing was carried out on Illumina. The Trimmomatic (v0.30) software was used to analyze raw sequencing data, in which adapter and low-quality sequences were removed to obtain clean data for further analysis (Grabherr et al. 2011). Sequencing data quality assessment was carried out with the Fast QC (v0.10.1) software, and TransDecoder was employed for ORF detection (Garg et al. 2011; Ness et al. 2011).

Functional annotation of transcripts was performed using BLASTX to compare nucleotide sequences in the NCBI’s NR protein database (tHoen et al. 2008; Morrissy et al. 2008). All predicted genes were assigned to different functional categories using Blast2GO (http://www.blast2Go.org/) to facilitate global gene expression analysis (Conesa et al. 2005). A categorization into functional groups was performed automatically through the KEGG pathway database, the annotation of which was carried out with the online KEGG Automatic Annotation Server (KAAS), using the comparison method for bidirectional best hit (BBH). The functional classification by KEGG provided valuable information for investigating specific processes, functions, and pathways.

Screening of differentially expressed genes

Gene expression data were evaluated using the Rsemsoftware. The DESeq software was used to screen the differentially expressed genes (DEGs), with false discovery rate (FDR) corrected p value of 0.05, with the adoption of a cut off of twofold regulation (Audic and Claverie 1997; Eisen et al. 1998; Saldanha 2004).

Analysis on differentially expressed genes

The identified DEGs were used for GO and KEGG pathway analysis. The GO enrichment analysis on functional significance was performed using the Gene Ontology database (http://www.geneontology.org/), evaluating gene numbers for every term and using a hypergeometric test to identify significantly enriched GO terms in DEGs. The following formula was used. The P-value of a significantly enriched GO term should be lower than 0.05; the P-value was corrected by Bonferroni

p=1-∑i=0m-1MiN-Mn-iNn

N = all genes with a GO annotation, n = DEGsin N, M = all genes annotated to certain GO terms, m = DEGsin M.

Compared with the whole-genome background, the KEGG pathway enrichment analysis identified significantly enriched metabolic pathways or signal transduction pathways in the DEGs (Kanehisa et al. 2015). The formula of the significantly enriched pathway was the same as that used for GO enrichment analysis.

Results

Effect of ABA on 20E content

The changes of 20E content are shown in Fig. 1. Treatment with 0.05 mg/l ABA showed no significant difference compared with that in the control group. Meanwhile, 0.1 mg/l ABA showed a significant difference at 48 h (p < 0.05); treatment with 0.15 mg/l ABA showed significant differences compared with that in the control group at 48 and 72 h, with 23.49 and 14.73% higher 20E contents compared with those in the control group respectively. Treatment with 0.2 mg/l ABA showed a trend of decline up to 20E content after an initial increase, with lower amounts than that in the control group at 72 h. Therefore, 0.15 mg/l ABA was selected as the optimal concentration for further experiments.

Fig. 1.

Fig. 1

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20E contents in different ABA treatment groups. Note: **significant difference between ABA treatment and control groups

Effect of ABA on A. lobata suspension cell activity

At 72 h, suspension A. lobata cells grew well after the addition of 0.15 mg/l ABA. The suspension culture system was light yellow, uniform and loose. However, A. lobata suspension cells were brown at 96 h. After being treated with ABA, dry weight was increased during the non-browning period. Dry weights were significantly higher than those in the control group at 24 h (p < 0.05). There was no significant difference in the dry weight at 48 and 72 h between treated and control groups. However dry weights were significantly reduced compared with that in the control group at 96 h (p < 0.05). Growth status is shown in Fig. 2, while biomass changes are summarized in Table 1.

Fig. 2.

Fig. 2

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Growth status of A. lobata suspension cells

Table 1.

Cell biomass variations

Dry cell weight/g
24th hours* 48th hours 72th hours 96th hours*
CK 0.480 ± 0.0071 0.542 ± 0.0192 0.567 ± 0.0157 0.635 ± 0.0212
ABA 0.505 ± 0.0141 0.555 ± 0.0096 0.577 ± 0.0149 0.512 ± 0.0068
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*Significant difference between ABA treatment and control groups

Illumina sequencing and data analysis

In this study, two cDNA libraries for A. lobata suspension cells treated with 0.15 mg/l ABA for 48 h and untreated, respectively, were generated on the Illumina HiSeq2000 platform. The statistics of raw data are shown in Table 2; clean reads were generated after removing adapter sequences, duplicate sequences, ambiguous reads, and low-quality reads (Table 3). Each library reached the saturation level of gene identification and a tag density sufficient for quantitative gene expression analysis. Of all the clean reads, 60.56% were matched to unique genomic locations; the uniquely matched reads were used for gene expression analysis. A comparison of clean reads and unigenesis is shown in Table 4. The distribution of the gene sequence length of all 119,359 genes detected by the RNA-Seq technology is shown in Fig. 3. For these genes, gene sequence length distribution was divided into five grades, along with the presentation of the total numbers and percentages of all genes. The proportion of long sequences was high among these genes, with 26,378 genes exceeding 1000 bp in length.

Table 2.

Statistical table showing raw data

Sample Length Reads Bases Q20 (%) Q30 (%) GC (%) N (ppm)
CK 125 53,286,482 6,660,810,250 97.55 95.04 45.535 561.23
ABA 125 51,046,352 6,380,794,000 94.23 88.49 46.5654 137.15
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Table 3.

Statistical table of clean data

Sample Length Reads Bases Q20 (%) Q30 (%) GC (%) N (ppm)
CK 123.43 48,405,691 5,968,647,065 99.32 98.11 45.34 1.14
ABA 119.95 41,896,665 5,023,735,715 98.235 95.21 46.155 0.455
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Table 4.

Comparison of clean reads and unigenes

Samples Total clean reads Total mapped Unique mapped Multi mapped Mapped (%) Unique (%)
CK 48,405,691 44,820,522 35,810,118 9,010,404 77.86 62.20
ABA 41,896,665 30,542,782 24,623,874 5,918,908 73.06 58.92
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Fig. 3.

Fig. 3

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Unigene interval distribution of different length

Gene expression and functional classification of the detected genes

A total of 45,150 unigenes were annotated to the Nr protein database successfully. Owing to the fact that a gene could be matched to multiple proteins the 45,150 unigenes were matched to 265,156 proteins with data redundancy. A total of 173,520 matched proteins with high homology (E value < 1E−30) making up 65.44% of all proteins. Meanwhile, 122,860 matched proteins showed higher homology (E value < 1E−60), i.e. 46.36% of all proteins. The highest matched species Vitisvinifera accounted for 23.23%, followed by Ricinuscommunis (14.35%), Solanumlycopersicum (14.30%), Populustrichocarpa (8.78%), Prunuspersica (8.35%) and Ricinuscommunis (6.51%), Glycine max (6.34%), Arabidopsis thaliana (3.71%) and Oryza sativa (2.35%).

The annotations were verified manually and integrated based on the gene ontology (GO) classification. 24,026 of the detected genes had at least one GO annotation based on sequence similarity. These annotated genes were categorized based on the secondary classification of GO terms, assigning them to 69 functional groups of the three main GO classification categories (Fig. 4). Genes assigned to “cellular component” accounted for the majority of GO terms (24), followed by “biological process” (23) and “molecular function” (22). The terms “single-organism process” and “metabolic process”, accounting for 24.98% and 13.28%, respectively, were the dominant GO terms. The terms “cellular process” (10.31%), “biological regulation” (8.39%) and “response to stimulus” (6.91%) were also common. Only a few genes were clustered in the way of “Channel regulator activity” and “cell killing”.

Fig. 4.

Fig. 4

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GO function classification of unigenes

Pathway-based analysis can be used to examine the biological functions and interactions of genes. We mapped the detected genes to reference canonical pathways in the KEGG pathway database to perform functional classification and pathway assignment. As a result, 8427 unigenes were assigned to 126 KEGG pathways (Table 5). among which the metabolism pathway was the largest category, followed by the ribosome, spliceosome and purine metabolism pathways. These results indicated that A. lobata cells were involved in the genetic and active metabolic processes. Moreover, in addition to the pathway related to 20E synthesis, terpenoid backbone biosynthesis (50 genes), steroid biosynthesis (21 genes) and steroid hormone biosynthesis (28 genes) pathways were identified.

Table 5.

KEGG pathway analysis

Pathway ID Pathway Number of unigenes
ko01100 Metabolic pathways 2315
ko03010 Ribosome 346
ko03040 Spliceosome 208
ko00230 Purine metabolism 165
ko04141 Protein processing in endoplasmic reticulum 157
ko00190 Oxidative phosphorylation 157
ko03013 RNA transport 156
ko00240 Pyrimidine metabolism 140
ko00500 Starch and sucrose metabolism 133
ko04075 Plant hormone signal transduction 130
ko04120 Ubiquitin-mediated proteolysis 120
ko03015 mRNA surveillance pathway 110
ko04110 Cell cycle 110
ko00010 Glycolysis/gluconeogenesis 109
ko03018 RNA degradation 104
ko00520 Amino sugar and nucleotide sugar metabolism 101
ko04111 Cell cycle—yeast 91
ko04144 Endocytosis 90
ko03008 Ribosome biogenesis in eukaryotes 89
ko04626 Plant-pathogen interaction 89
ko04146 Peroxisome 85
ko00564 Glycerophospholipid metabolism 81
ko00330 Arginine and proline metabolism 77
ko04113 Meiotic division 75
ko00620 Pyruvate metabolism 73
ko00270 Cysteine and methionine metabolism 70
ko04145 Phagosome 69
ko00480 Glutathione metabolism 64
ko00970 Aminoacyl-tRNA biosynthesis 62
ko00860 Porphyrin and chlorophyll metabolism 61
ko00260 Glycine, serine, threonine metabolism 60
ko03420 Nucleotide excision repair 59
ko00680 Methane metabolism 58
ko00980 Metabolism of xenobiotics by cytochrome 58
ko00940 Phenylpropanoid biosynthesis 57
ko00195 Photosynthesis 55
ko00040 Pentose and glucuronateinterconversions 55
ko00510 N-Glycan biosynthesis 54
ko00710 Carbon fixation in photosynthetic organisms 54
ko00051 Fructose and mannose metabolism 52
ko03440 Homologous recombination 52
ko00030 Pentose phosphate pathway 52
ko00250 Alanine, aspartate and glutamate metabolism 51
ko00562 Inositol phosphate metabolism 51
ko04142 Lysosome 51
ko00630 Glyoxylate and dicarboxylate metabolism 51
ko00900 Terpenoid backbone biosynthesis 50
ko03030 DNA replication 48
ko00360 Phenylalanine metabolism 48
ko03022 Basal transcription factors 48
ko00020 Citrate cycle (TCA cycle) 47
ko00561 Glycerolipid metabolism 46
ko00053 Ascorbate and aldarate metabolism 45
ko03060 Protein export 44
ko04130 SNARE interactions in vesicular transport 43
ko00400 Phenylalanine, tyrosine and tryptophan biosynthesis 43
ko03430 Mismatch repair 43
ko03050 Proteasome 42
ko00052 Galactose metabolism 42
ko00563 Glycosylphosphatidylinositol(GPI)-anchor biosynthesis 41
ko03410 Base excision repair 40
ko04010 MAPK signaling pathway 39
ko00071 Fatty acid metabolism 39
ko00280 Valine, leucine and isoleucine degradation 36
ko00640 Propanoate metabolism 35
ko00830 Retinol metabolism 33
ko00920 Sulfur metabolism 33
ko00600 Sphingolipid metabolism 33
ko00350 Tyrosine metabolism 32
ko00310 Lysine degradation 31
ko00061 Fatty acid biosynthesis 31
ko00410 beta-Alanine metabolism 30
ko00770 Pantothenate and CoA biosynthesis 30
ko00513 Various types of N-glycan biosynthesis 29
ko00130 Ubiquinone and other terpenoid-quinone biosynthesis 29
ko00380 Tryptophan metabolism 29
ko01040 Biosynthesis of unsaturated fatty acids 28
ko00140 Steroid hormone biosynthesis 28
ko04650 Natural killer cell mediated cytotoxicity 28
ko04122 Sulfur relay system 27
ko04712 Circadian rhythm—plant 27
ko02020 Two-component system 26
ko00790 Folate biosynthesis 26
ko00592 alpha-Linolenic acid metabolism 25
ko00910 Nitrogen metabolism 24
ko04140 Regulation of autophagy 24
ko00340 Histidine metabolism 24
ko00590 Arachidonic acid metabolism 22
ko00100 Steroid biosynthesis 21
ko00906 Carotenoid biosynthesis 20
ko00460 Cyano amino acid metabolism 20
ko00670 One carbon pool by folate 20
ko00760 Nicotinate and nicotinamide metabolism 20
ko00196 Photosynthesis antenna proteins 19
ko00511 Other glycan degradation 19
ko00780 Biotin metabolism 19
ko00290 Valine, leucine and isoleucine biosynthesis 19
ko00062 Fatty acid elongation 19
ko00624 Polycyclic aromatic hydrocarbon degradation 17
ko00730 Thiamine metabolism 17
ko02010 Transporters ABC 17
ko00960 Tropane, piperidine and pyridine alkaloid biosynthesis 16
ko00300 Lysine biosynthesis 15
ko00450 Selenocompound metabolism 14
ko00591 Linoleic acid metabolism 14
ko00904 Diterpenoid biosynthesis 11
ko00941 Flavonoid biosynthesis 11
ko00750 Vitamin B6 metabolism 11
ko00740 Riboflavin metabolism 10
ko00603 Glycosphingolipid biosynthesis - globo series 10
ko04710 Circadian rhythm 10
ko00531 Glycosaminoglycan degradation 10
ko00430 Taurine and hypotaurine metabolism 9
ko00440 Phosphonate and phosphinate metabolism 9
ko03450 Non-homologous end-joining 8
ko00908 Zeatin biosynthesis 7
ko00909 Sesquiterpenoid and triterpenoid biosynthesis 6
ko00073 Cutin, suberine and wax biosynthesis 6
ko00785 Lipoic acid metabolism 6
ko00514 Other types of O-glycan biosynthesis 6
ko00905 Brassinosteroid biosynthesis 5
ko00072 Synthesis and degradation of ketone bodies 4
ko00944 Flavone and flavonol biosynthesis 3
ko00965 Betalain biosynthesis 2
ko00942 Anthocyanin biosynthesis 1
ko00633 Nitrotoluene degradation 1
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Identification of differentially expressed genes

The analysis on differentially expressed genes (DEGs) between samples can be accomplished using RNA-SEq. In this study, DEGs were defined based on fold change of the normalized (RPKM) expression values, leading to the fact that there is a total of 154 genes exhibiting significant differential expression between the two samples. When comparing the control and ABA treatment group libraries, it can be found that 99 genes were up-regulated and 55 down-regulated (Fig. 5).

Fig. 5.

Fig. 5

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Statistics of DEGs

GO analysis of DEGs

All DEGs were mapped to GO terms in the database based on GO functional classification, followed by the comparison to the genomic background. The GO enrichment analysis on 81 genes is shown in Table 6 (agene could be mapped to multiple GO terms). We categorized the DEGs between the samples according to the secondary GO term classification. In all, 7, 10, and 8 functional groups were in the cellular component, molecular function, and biological process categories, respectively. In the biological process category, “metabolic process” was the dominant group, indicating that extensive metabolic activities occurred in ABA treated A. lobata cells. “Binding” and “catalytic activity” were highly represented in the molecular function category, while “cell part” was dominant in the cellular components category.

Table 6.

Significant differences of the GO terms

Cluster GO term Cluster frequency
Cellular component Cell part 24 out of 24 genes, 100%
Intracellular part 22 out of 24 genes, 91.66%
Cytoplasm 22 out of 24 genes, 91.66%
Organelle 18 out of 24 genes, 75%
Membrane-bounded organelle 16 out of 24 genes, 66.7%
Plastid 6 out of 24 genes, 25%
Chloroplast 6 out of 24 genes, 25%
Molecular function Catalytic activity 9 out of 22 genes, 40.91%
Hydrolase activity 8 out of 22 genes, 36.36%
Hydrolase activity, hydrolyzing O-glycosyl compounds 6 out of 22 genes, 27.27%
Binding 9 out of 22 genes, 40.91%
Hydrolase activity, acting on glycosyl bonds 4 out of 22 genes, 18.18%
Ion binding 3 out of 22 genes, 13.63%
Small molecule binding 3 out of 22 genes, 13.63%
Nucleotide binding 3 out of 22 genes, 13.63%
Nucleoside phosphate binding 3 out of 22 genes, 13.63%
Oxidoreductase activity 7 out of 22 genes, 31.81%
Biological process Metabolic process 32 out of 35 genes, 91.425%
primary metabolic process 27 out of 35 genes, 77.14%
Organic substance metabolic process 20 out of 35 genes, 61.9%
Response to stimulus 5 out of 35 genes, 14.28%
Lipid metabolic process 5 out of 35 genes, 14.28%
Carboxylic acid metabolic process 6 out of 35 genes, 17.14%
Aromatic compound biosynthetic process 16 out of 35 genes, 45.71%
Heterocycle biosynthetic process 14 out of 35 genes, 40%
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KEGG pathway analysis of DEGs

We mapped all DEGs to reference canonical pathways in the KEGG pathway database so as to identify the significantly enriched genes involved in metabolic or signal transduction pathways. By comparing with the whole transcriptome background, 18 pathways were significantly enriched, comprising 112 DEGs (Table 7). Pyrimidine metabolism and nitrogen metabolism pathways were significantly enriched with DEGs followed by RNA polymerase and biosynthesis of amino acids pathways. Among the pathways significantly enriched with DEGs, terpenoid backbone biosynthesis (6 DEGs), steroid biosynthesis (5 DEGs), steroid hormone biosynthesis (6 DEGs) pathways were identified.

Table 7.

Pathways enriched by the differential expression genes

Pathway ID Pathway DEGs with pathway annotation p value Q value
ko00603 Glycosphingolipid biosynthesis—globo series 1 0.89% 0.01663 0.001326
ko00910 Nitrogen metabolism 10 8.93% 0.000403 0.002689
ko00591 Linoleic acid metabolism 1 0.89% 0.000221 0.003847
ko04142 Lysosome 4 3.57% 0.00183 0.004108
ko00710 Carbon fixation in photosynthetic organisms 5 4.46% 0.00205 0.004108
ko03430 Mismatch repair 5 4.46% 0.0013 0.004108
ko00030 Pentose phosphate pathway 6 5.36% 0.00191 0.004108
ko00051 Fructose and mannose metabolism 7 6.25% 0.00191 0.004108
ko03020 RNA polymerase 9 8.04% 0.0013 0.004108
ko00900 Terpenoid backbone biosynthesis 7 6.25% 0.000757 0.007405
ko00010 Glycolysis /Gluconeogenesis 7 6.25% 0.00818 0.01168
ko00240 Pyrimidine metabolism 14 12.50% 0.0133 0.015823
ko00230 Purine metabolism 8 7.14% 0.0182 0.020192
ko01220 Degradation of aromatic compounds 3 2.68% 0.01803 0.021453
ko01200 Carbon metabolism 6 5.36% 0.0257 0.027032
ko00100 Steroid biosynthesis 4 3.57% 0.01453 0.033462
ko00140 Steroid hormone biosynthesis 6 5.36% 0.019623 0.037926
ko01230 Biosynthesis of amino acids 9 8.04% 0.0335 0.047735
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KEGG pathway analysis of genes related to 20E synthesis

The terpenoid backbone biosynthesis can be completed through (ko00900) two sub-pathways, namely MVA and DOXP/MEP sub-pathways (Fig. 6). The former starts with acetyl CoA condensation, while the latter with Glyceraldehyde 3-phosphate (GA-3P). The terpenoid backbone biosynthesis pathway ends with IPP and moves into the next pathway (ko00100). Compared with the ko00900 pathway of untreated A. lobata suspension cells, the terpenoid backbone biosynthesis pathway had 5 genes up-regulated and 1 down-regulated after ABA treatment (Fig. 7).

Fig. 6.

Fig. 6

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The ko00900 pathway in untreated A. lobata suspension cells. Note: the genes in untreated A. lobata suspension cell cDNA library in the pathway are shown in red. Same below

Fig. 7.

Fig. 7

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DEGs were annotated to the ko00900 pathway. Note: red, up-regulated gene; green, down-regulated gene. Same below

Corresponding to EC:1.1.1.34, the c49795_g1_i1gene was up-regulated, along with the identification as the Nicotinamide Adenine Dinucleotide Phosphate (NADPH) gene of the MVA pathway. NADPHisa, the key enzyme in the MVA pathway, converts HMF-CoA to mevalonate.

The c29419_g1_i1 gene (EC:4.6.1.12) was up-regulated, along with the identification as the 2C-methyl-d-erythritol 2,4-cyclodiphosphate synthase (MCS) gene of the DOXP/MEP pathway. MCS gene function is to convert 2-phospho-4-(cytidine5′-diphospho)-2-C-methyl-d-erythritol to 2-C-methyl-d-erythritol2,4-cyclicphosphate.

The c44766_g1_i6 gene (EC:4.6.1.12,EC:1.8.3.5) was up-regulated, and identified as the Alpha farnesene synthesis (AFS) gene, which is the intermediate enzyme in farnesyl cysteine synthesis.

The c45098_g1_i1 and c73678_g1_i1 genes (EC:2.5.1.1,EC:2.5.1.10 and EC:2.5.1.29) genes, both corresponded to geranyl geranylpyrophosphate synthetase II (GGPPS) gene, were up-regulated. The enzymatic function of GGPPS is to produce geranyl pyrophosphate (GGPP).

The c81295_g1_i1gene (EC:3.4.24.84) was down-regulated, and identified as the ste24 endopeptidase gene, which is an intermediate enzyme in farnesyl pyrophosphate (FPP) synthesis.

Next to the ko00900 pathway was the steroid biosynthesis pathway (ko00100) beginning with IPP, with squalene as intermediate, and steroid compounds as end products (Fig. 8). The steroid biosynthesis pathway had 4 genes up-regulated and 1down-regulated (Fig. 9); only c27194_g1_i2 (EC:1.1.1.170) and c34855_g1_i (EC:1.14.13.72) genes, both modifiers in the process of squalene related synthesis of steroid substances, were related to the synthesis of steroid hormones. Those two genes were both modifiers in the process of. The c27194_g1_i2 gene was identified as the 4α-carboxylic acid 3 dehydrogenase gene, while the c34855_g1_i gene was the methyl oxidase gene, which were associated with brassino steroid synthesis.

Fig. 8.

Fig. 8

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The ko00100 pathway in untreated A. lobata suspension cells

Fig. 9.

Fig. 9

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DEGs annotated to the ko00100 pathway

Next was the steroid hormone biosynthesis (ko00140) pathway (Fig. 10). After analysis, we found six DEGs that were all modifiers in the process of squalene related synthesis of steroid substances with a total of five genes up-regulated and one down-regulated (Fig. 11). Currently, the KEGG pathway database has not fully included the 20E pathway, and 20E synthetic steroid is similar to hormone synthesis included by ko00140; therefore, these genes were annotated to the ko00140 pathway with similar functions. Corresponded to the glucuronide transferase gene, the c47715_g1_i2,c47715_g1_i3, c47715_g1_i6 and c47715_g1_i7(EC:2.4.1.17) genes were up-regulated. The c21475_g1_i1 gene (EC:1.3.1.22 and1.3.1.94) was up-regulated, with identification as polyprenol reductase gene while the c40828_g1_i6gene (EC:2.4.1.17) was down-regulated, with the identification as the glucuronide transferase gene.

Fig. 10.

Fig. 10

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The ko00140 pathway in untreated A. lobata suspension cells

Fig. 11.

Fig. 11

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DEGs annotated to the ko00140 pathway

Discussion

Treatment with 0.15 mg/l ABA of A. lobata suspension cultures could promote 20E content increase in the short term but was not suitable for long-term culture, and browning was observed. In Wang et al. (2018) study, the browning also happened, which might be caused by the toxicity of ABA. In recent years, studies have shown that ABA can regulate and stimulate the production of secondary metabolites such as chlorogenic acid, phenols, flavonoids and terpenoid substances (Sandhu et al. 2011; Buran et al. 2012). The increase of these secondary metabolites is related to ABA stress inducing the defense system. It was also found that stimulus response genes differentially expressed after ABA treatment, but the relationship between stimulus response and 20E synthesis still needs further exploration.

ABA can inhibit growth, causing premature cell aging, which is responsible for the fact that A. lobata suspension cells turned brown after ABA treatment (Hansen and Grossmann 2000; Hunter et al. 2004). On the other hand, ABA produced stress stimulate the cells, and stress stimulation could promote cell browning (Dai et al. 2016). This might be one of the main causes of the browning phenomenon.

It was found in the studies 20E is mainly synthetized through the MVA and DOXP/MEP pathways. However, the full 20E synthesis pathway remains unclear; the pathways from squalene to 20E are not completely described (Adler and Grebenok 1995; Dinan 2001; Báthori and Pongrácz 2005; Ma et al. 2006). In the KEGG pathway database, we only found ko00900 and ko00100 pathways to produce squalene utilizing pyruvic acid and GA-3Pas starting points. Without including the pathway from squalene to 20E, the KEGG pathway database contains a pathway from squalene to other sterol hormones (ko00140). A. lobata cDNA library has similar genes in the ko00140 pathway. NADPH, MCS, AFS, GGPPS and STE24 endopeptidase genes in the ko00900 pathway of DEGs were all synthetase genes (Bach 1987; Adam and Zapp 1998; Kim et al. 2014; Liao et al. 2014). The 4α-carboxylic acid 3 dehydrogenase and methyl oxidase genes in the ko00100 pathway of DEGs were modifier genes. The DEGs similar to the genes in the ko00140 pathway were modifier genes widespread in plant secondary metabolism (glucuronide transferase genes). The function of those genesis glycosylation is to add sugar molecules on specific sites of metabolites (Mackenzie et al. 1997; Gachon et al. 2005; Asada et al. 2013). Glycosyl transferase has high specificity (Coutinho et al. 2003). Therefore, the relationship between glycosyl transferase gene modification and 20E synthesis also needs to be further explored.

Conclusions

The study found that ABA promoted 20E accumulation. A total of 154 genes were significantly regulated after ABA treatment, with 99 up-regulated and 55 down-regulated, respectively. In addition to 20E-related pathways, the genes belonged to the ko00900 (terpenoid backbone biosynthesis) pathway (six differentially expressed genes [DEGs]), ko00100 (steroid biosynthesis) pathway (four DEGs), and ko00140 (steroid hormone biosynthesis) pathway (six DEGs). It is hoped that these results can offer a strategy to explore a way to regulate the 20E accumulation from the molecular biological angle.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (NSFC) (Grant no.: 31370649).

Abbreviations

20E

20-Hydroxyecdysone

MVA

Mevalonic acid

DOXP/MEP

5-Phosphate-d-deoxyxylulose/2-C-methy-d-erythritol-4-phosphate

DMAPP

Dimethylallyl pyrophosphate

IPP

Isopentenyl pyrophosphate

MS

Murashige and Skoog culture medium

2,4-D

2,4-Dichlorophenoxyacetic acid

Compliance with ethical standards

Conflict of interest

No potential conflict of interest was reported by the authors.

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