Du ZY et al / Acta Pharmacol Sin 2003 Sep; 24 (9): 864-872

Analysis of triptolide-regulated gene expression in Jurkat cells by complementary DNA microarray1

DU Ze-Ying, LI Xiao-Yu2, LI Yuan-Chao3, WANG Shun-You

Department of Pharmacology, 3Department of Medicinal Chemistry, Shanghai Institute of Materia Medica, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China

1 Project supported by Special Funding for Life Science and Biotechnology from Chinese Academy of Sciences (STZ-00-05).

2 Correspondence to Prof LI Xiao-Yu. Phn 86-21-6433-5163. E-mail xyli@mail.shcnc.ac.cn

Received 2002-12-17 Accepted 2003-06-16

KEY WORDS cDNA microarrays; triptolide; Jurkat cells; gene expression

ABSTRACT

AIM: To investigate the global gene expression profile changes in Jurkat cells after triptolide treatment in order to find the possible triptolide targets. Methods: Jurkat cells were treated with or without triptolide 10 µg/L for 2 h. Total RNA were isolated and used as templates for reverse transcriptional labeling of fluorescent cDNA probes. High density DNA microarray chips with a set of 13 872 human genes/Ests were used to generate the expression profile of triptolide-treated or untreated control Jurkat cells by hybridizing with fluorescent labeled probes. Array image was acquired and analyzed with array analyzing software GeneSpring. Results: Triptolide significantly suppressed expression of 117 genes in Jurkat cells. Among these 117 genes, 30 % were Ests or genes without known functions, 13 % were transcription factors, 9 % were signal transduction pathway regulators, and 9 % were DNA binding proteins. Notably, the expression of mitogen-activated protein kinase kinase kinase kinase 5 (MAP kinase 5) and phosphoinositide-3-kinase (PI-3 kinase) was inhibited more than 100-fold. Moreover, the expression of genes involved in lipid transportation and metabolism was down-regulated by triptolide. Conclusion: High-density microarray provided an effective approach to identify drug targeting molecules. It is suggested that the widely known immune suppressive and antitumor effects of triptolide were mediated at least in part by suppression of MAP kinase and PI-3 kinase gene expression.

INTRODUCTION

Triptolide is an effective ingredient of the Chinese herb Tripterygium wilfordii Hook F (TWHF), which has been historically used in traditional Chinese medicine for the treatment of rheumatoid arthritis, chronic nephritis, and other pulmonary diseases[1,2]. TWHF is a multi-functional drug and has been reported to have immunosuppressive and anti-inflammatory[1-3], antitumor[4-7], and antifertility activities[8]. Recently, the molecular mechanism of the immunosuppressive and anti-inflammatory effects of TWHF has been investigated. It had been found that TWHF inhibited IL-2 production by activated T-cells via a pathway that is different from cyclosporin A[9]. TWHF also suppressed IL-2 receptor expression induced by phorbol 12-myristate 13-acetate and CD40 ligand expression induced by ionomycin[10]. Triptolide, a chloroform/methanol extract of TWHF, inhibits mitogen or antigen-induced proliferation of human peripheral blood T-cells and B-cells, IL-2 production by T-cells and immunoglobulin production by B cells[11]. Triptolide has a potent inhibitory effect on the clonogenic response of human bone marrow cells to exogenous hematopoietic growth factors by suppression of the activation of NF-B[12]. Further-more, triptolide induces apoptosis of T-cell hybridomas and peripheral T-cells by increasing caspase activity[3]. Several groups had reported that TWHF inhibited tumor cell growth in vitro and in vivo[5,7]. Triptolide reduced the number of soft-agar clone formation by more than 70 % in breast cancer MCF-7 and BT-20 cells, stomach cancer MKN-45 and MKN-7 cells[7]. Triptolide inhibits cell growth, induces apoptosis, and suppresses NF-B and AP-1 transactivation in gastric cancer through the p53 pathway[5]. Though the above-mentioned studies shed some lights on triptolide actions, there are still many gaps left and hard to explain why triptolide has such a broad biological functions.

Recently, complementary DNA (cDNA) micro-array has been used to identify gene expression patterns in a variety of organisms. cDNA microarray provides an efficient method to analyze gene expression profile with a high throughput of thousands of genes in parallel. In contrast to the traditional molecular techniques that focus on one to a few genes at a time, cDNA microarray allows gene expression patterns to be analyzed on a genomic scale[13]. In this study, the global gene expression changes in Jurkat T-cells treated with triptolide were investigated by this modern high density microarray technique.

MATERIALS AND METHODS

Drug treatment Triptolide was first dissolved in Me2SO (0.1 g/L) and then diluted with culture medium to 1 mg/L. The acute T-cell leukemia cell line Jurkat cells were obtained from the American Type Culture Collection (ATCC) and were maintained in RPMI- 1640 supplemented with 10 % fetal bovine serum. Cells were grown at 37 ºC in a humidified 5 % CO2 atmo-sphere. Triptolide was added to the medium in a final concentration of 10 µg/L for 2 h at the cell concentration of 2×109 /L. Cells treated with the same concentration Me2SO were used as controls. Both cells were centrifuged at 300×g for 5 min. The pellets were used for total RNA isolation.

RNA isolation Total RNA was extracted using standard Trizol RNA isolation protocol (Life Technologies, Inc, Grand Island, NY). Briefly, 1 mL of Trizol reagent was mixed with Jurkat cell pellet per 107 cells by repeated pipetting. DNA and protein were excluded by chloroform phase separation. RNA in the aqueous phase was precipitated with isopropanol and then resuspended in DEPC water.

Reverse-transcriptional labeling The first strand cDNA synthesis was performed with CyScribe first strand cDNA labeling kit (Amersham Pharmacia Biotech). Briefly, 25 µg of total RNA was denatured in the presence of 1 µL of anchored oligo dT(18)VN primer in 10 µL at 70 ºC for 3 min followed by quenching on ice. The RNA from both control and triptolide samples were reciprocally labeled with Cy3-dCTP and Cy5-dCTP separately in a volume of 20 µL in the presence of 1× CyScript buffer, DTT 10 mmol/L, 1 µL dCTP nucleotide mix, 1 µL Cy3/Cy5-dCTP and 1 µL CyScript reverse transcriptase. The reaction was carried on at 42 ºC for 2 h in water bath in the dark. To degrade RNA, 2 µL of NaOH 2.5 mol/L was added into labeling reactions and incubated at 37 ºC for 15 min. NaOH in the solution was neutralized with 10 µL of HEPES 2 mol/L free acid. The labeling products were purified with PCR purification columns (Qiagen, Hilden, Germany).

Microarray hybridization Cy3- and Cy5-labelled cDNA were dried in a speedvac concentrator in amber microcentrifuge tubes and resuspended in 11 µL of nuclease free water. Having been denatured by heating at 95 ºC for 2 min, the labeled cDNA was incubated with 1 µL of polyA 5 g/L, 3 µL of human Cot-1 DNA 10 g/L at 75 ºC for 45 min. Following incubation, 15 µL of 4×microarray hybridization buffer and 30 µL of 100 % (v/v) formamide were mixed to the above solution and then gently applied onto the microarray slides on which 14 000 oligoes corresponding to known genes and EST were printed in duplicates (Operon, Alameda, California, USA) and covered with a cover slip. Hybridization was performed in a humid hybridization chamber at 42 ºC for 14-18 h. After hybridization, the slides were first washed with 1×SSC with 0.2 % SDS at RT for 10 min using a rotatory shaker, followed by washing with 0.1×SSC with 0.2 % (w/v) SDS twice at RT for 10 min. After final wash in distilled water for 10 s, the slides were dried with gentle air stream and scanned with a microarray scanner.

Array quantification and data process Cy3 and Cy5 images were acquired separately. Each spot was defined by manually positioning a grid of circles over the array image. For each fluorescent image, the average pixel intensity within each circle was determined. The local background was computed for each spot equal to the median pixel intensity in a circle of 5 pixels in width around the signal area. Net signal was determined by subtraction of this local background from the average intensity for each spot. Spots deemed that they were unsuitable for accurate quantification because array artifacts were manually flagged and excluded from further analysis. Signal intensities were first normalized by dividing all intensities measured with the median fluorescence intensity (MFI) in the same channel, and then the computed intensity of each spot was further divided by mean of the same spot from two different channels. This effectively defined the signal intensity-weighted "average" spot on each array to have a ratio of 1.0. To minimize the possibility of fault positive, only those genes with a signal intensity 300 and the standard division between duplicated spots <1 were used for further consideration. A gene was considered to be differentially expressed when the difference of normal-ized MFI between the two fluorochromes was more than 5-fold in two separated experiments with reciprocally labeled cDNA. Except the expressed sequence tags, the differentially expressed genes were further divided into groups based on their molecular functions and biological processes reported in the literature.

Statistical analysis The calculation of fluorescence intensity, standard division of duplicated spots and normalization between different arrays were performed by specialized array analyzing software Gene-Spring from Silicon Genetics.

RESULTS

Global expression analysis of genes regulated by triptolide The overall expression of the 13 872 genes in Jurkat cells was shown (Fig 1). A representative partial array image was shown (Fig 2). The fluroscence intensity was correlated with the brightness of spots. Each gene/Est was deposited as duplicate for statistic analysis and quality control. The arrowhead indicated differentially expressed gene in untreated (Fig 2A) and triptolide-treated Jurkat cells (Fig 2B). There 547 (4 %) genes were expressed in a high abundance (the signal fluorescence intensity ranges from 1000 to 64 000), 7072 (51 %) genes were expressed from low to intermediate high level (fluorescence intensity ranges from 100 to 1000), 6253 genes (45 %) were either not expressed or in the margin level of expression (fluorescence intensity less than 100).

Fig 1. Global expression of genes in Jurkat cells. The expression level of 13 872 genes in Jurkat cells as indicated by fluorescence intensity by array analysis. About half were expressed at an intermediate level (100-1000 pixels), half were expressed at low level or not expressed at all. Less than 4 % genes were high abundant in transcript.

Fig 2. A representative partial microarray image from control cDNA (A) and triptolide-treated cDNA (B). Brightness of spots corresponding to fluorescence intensity and abundance of gene expression. indicate the genes that were differentially expressed by two samples.

Genes suppressed by triptolide Among the 13872 genes/Ests in the array set, 117 were identified as triptolide-suppressed genes/Ests which showed decreased expression of at least 5-fold in triptolide-treated Jurkat cells than control. Among those, the expressions of 20 genes/Ests were inhibited more than 100-fold (Tab 1). Based on their molecular functions, these 117 genes were classified into 21 different groups (Fig 3A). The group with most genes (34 genes, 29 % of total suppressed genes) did not have reported functional data and classified as molecular function unknown. Other groups were transcription factors (15 genes, 13 %), nucleic acid binding proteins (11 genes, 9 %), and regulatory molecules (11 genes, 6 %). Some examples of the genes in the above mentioned last three groups include U33761 S-phase kinase-associated protein 2 (p45), U77129 mitogen-activated protein kinase kinase kinase kinase 5, X77794 cyclin G1, and S67334 phosphoino-sitide-3-kinase. In accordance with classification by molecular function, the 171 triptolide-suppressed genes/Ests had similar distribution as classified by biological process (Fig 3B). Thirty-three genes/Ests belonged to a group of protein without reported biological functions. The other 83 genes were grouped into 21 different subgroups according to the biological processes. In these subgroups, most of the genes (28 genes, 24 % of total) belong to molecules that were involved in nucleoside, nucleotide and nucleic acid metabolism including DNA replication, mRNA transcription, and pre-mRNA processing. Other subgroup genes were protein metabolism and modification (9 genes, 8 %), electron transport (7 genes, 6 %), and signal transduction (7 genes, 6 %).

Tab 1. Triptolide-suppressed genes.

Fig 3. Distribution of genes down-regulated by triptolide according to their molecular function or biological process. A) The 117 genes down-regulated by triptolide were subgrouped into 21 different classes according to their molecular functions reported. B) The same genes were subgrouped into 22 different classes according to the biological process.

DISCUSSION

Triptolide had been reported to be a multifunctional compound that could induce apoptosis of T-lymphocytes[3], prostate epithelial cells[4], breast and gastric cancer cells[5,7]. It also had profound effects on male fertility, immune and inflammation[1,14,15]. Here, we reported the molecular profile changes of triptolide treatment on acute human T-cell leukemia cell line Jurkat cells by high density DNA array.

Our present results show that there are at least half of transcripts among the 13 872 genes/Ests represented in the array set expressed in Jurkat cells (Fig 1). Among those expressed transcripts, 171 genes/Ests were shut off or down-regulated at least 5-folds by triptolide in Jurkat cells. Some of the most significantly regulated genes (more than 100 times lower in triptolide-treated cells, Tab 1), U33761 S-phase kinase-associated protein 2 (p45), U77129 mitogen-activated protein kinase kinase kinase kinase 5, S67334 phosphoinositide-3-kinase, and X77794 cyclin G1 were suppressed more than 100-fold by triptolide. All these genes are well-known signal transduction pathway components and involved critically in a broad spectrum of biological process such as cell cycle, gene transcription, cell survival and cell death. Down-regulation of these molecules provided a new insight for the molecular mechanisms of triptolide-induced cell death, antifertility and immun-suppression. Triptolide treatment may also influence chromatin structure by inhibiting genes that either directly interact with or regulate chromatin remodulation complex such as U76638 BRCA1-associated RING domain 1 and U29175 SWI/SNF regulator of chromatin. Another class of genes suppressed by triptolide were oxidoreductase and electron transport protein, namely AF053070 NADH dehydrogenase flavoprotein, AF038406 NADH dehydrogenase, and AL021878 cytochrome P450. It remains to be illustrated whether this is the direct effects of triptolide or resulted from reduced metabolic activity of triptolide-treated cells. In addition to the suppressive effects, triptolide also activated or up-regulated gene transcription. The 43 genes/Ests were up-regulated, however most of them are either molecular function unknown or biological procession unknown. The few known genes, U27266 myosin-binding protein H, AJ238098 Sm protein F, Z80782 H2B histone family member K may represent non-specific cell response to triptolide treatment (data not shown).

In accordance with previous reports, our data indicated that the inhibitory effects of triptolide on immune responses were at least partially mediated by suppressing T-cell activation (L41067 nuclear factor of activated T-cells), reducing production of immunoglobulin (AB007935 immunoglobulin superfamily), and inhibiting interferon pathway (M13755 interferon-stimulated protein)[9]. In spite of the immune suppressive effect, triptolide may also affect lipid metabolism. At least 3-lipid and cholesterol metabolism related genes (AF034544 7-dehydrocholesterol reductase, M64098 high density lipoprotein binding protein, M63959 low density lipoprotein-related protein) were shown to be down-regulated in our experiment. The significance of this discovery deserves further investigation.

REFERENCES