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Human ATP-binding cassette transporter TaqMan low-density array: analysis of macrophage differentiation and foam cell formation.

ATP-binding cassette (ABC) transporters cause various human monogenic and polygenic diseases and regulate many physiologic processes, such as lipid homeostasis, iron transport, and immune mechanisms (1). Numerous ABC transporters are involved in bile acid, phospholipid, and sterol transport (2), and expression of the genes that encode these transporters is itself controlled by lipids. Several ABC proteins mediate drug export in compound-treated tumor cells and thereby promote the development of multidrug resistance (3). Thus, ABC transporter mRNA profiling may become an integral part of lipidomics, molecular clinical diagnosis, and monitoring of drug effects in cancer patients (4).

We recently described a real-time reverse transcription-PCR method for detection and quantification of 47 of the 48 currently known members of the ABC transporter superfamily (5). This analysis was based on relative quantification using the Standard Curve Method and allowed monitoring of RNA samples in a 384-well format with only 50 ng of total RNA. We have successfully used the method to quantify ABC transporter mRNA in 20 different human tissues.

We have now extended, improved, and simplified the quantification of all 47 ABC transporters by creating a Human ATP-Binding Cassette Transporter TaqMan[R] Low-Density Array based on an Applied Biosystems 7900HT Micro Fluidic Card. The method allows simultaneous analysis of 47 human ABC transporters and the reference gene 18S rRNA in 2 replicates of 4 different samples per run. The 2-[micro]L small-volume design of each reaction well substantially decreases sample and reagent consumption, and the precaptured primers and probes save time by reducing labor-intensive pipetting steps.

To evaluate this method for lipidomic research and to further characterize the patterns of ABC transporters produced in cells relevant for atherosclerosis research, we monitored expression of mRNA in human primary monocytes, in vitro-differentiated macrophages, and cells stimulated with the liver-X-receptor (LXR) and retinoid-X-receptor (RXR) agonists T0901317 and 9-cis retinoic acid (RA) to mimic sterol loading and foam cell formation.

Human monocytes were obtained from 3 healthy donors by leukapheresis and counterflow elutriation. The cells were cultured on plastic petri dishes in macrophage serum-free growth medium (Gibco BRL) and allowed to differentiate for 5 days in the presence of 50 [micro]g/L recombinant human macrophage colony-stimulating factor (R&D Systems) in a 5% [CO.sub.2] atmosphere at 37[degrees]C. Macrophages were stimulated for 24 h with a 5 [micro]mol/L combination of the LXR ligand T09013179 (Sigma) and the RXR ligand 9-cis RA (Sigma). Control macrophages were kept 24 h in the presence of solvent (ethanol).

Harvesting of cells, RNA extraction, and DNase digestion were carried out with the RNeasy Midi Kit (Qiagen), according to the manufacturer's instructions. RNA purity and integrity were assessed on the Agilent 2100 bioanalyzer with the RNA 6000 Nano LabChip[R] reagent set (Agilent Technologies). The RNA was quantified spectrophotometrically and then stored at -80[degrees]C.

cDNA synthesis was performed with the Reverse Transcription System from Promega. The master mixture contained 5 mmol/L Mg[Cl.sub.2], 1x Reverse Transcription Buffer, 1 mmol/L deoxynucleotide triphosphate mixture, 1 unit/[micro]L recombinant RNasin[R] ribonuclease inhibitor, 0.75 U/[micro]L AMV Reverse Transcriptase, and 1 [micro]g of Random Hexamer Primers. We added 1 [micro]g of total RNA and sterile [H.sub.2]O to a final volume of 20 [micro]L. The reaction mixture was incubated at 42[degrees]C for 60 min, followed by heat inactivation of the enzyme at 95[degrees]C for 5 min. After cooling on ice for 5 min, the cDNA was stored at -20[degrees]C.

The TaqMan probe and primer sets for 47 human ABC transporters and 18S rRNA as a reference gene were carefully selected from predesigned TaqMan Gene Expression Assays (Applied Biosystems). The minor groove binding probes were 5'-labeled with a 6-carboxyfluorescein dye and a nonfluorescent quencher at the 3' end. The exact locations and the sequences of the oligonucleotides used in all assays can be downloaded from the Applied Biosystems website (https://myscience.appliedbiosystems.com) by selecting the Assays IDs (see Table 1 in the Data Supplement that accompanies the online version of this Technical Brief at http://www.clinchem.org/content/vol52/issue2/). All ABC transporter assays span exon-intron boundaries and cover the major transcript forms. The sets were factory-loaded into the 384-well plate to create the TaqMan Low-Density Array (see Fig. 1 in the online Data Supplement). The specific configuration presented here is available as a Human ATP-Binding Cassette Transporter TaqMan Low-Density Array.

We mixed 2 [micro]L of single-stranded cDNA (equivalent to 100 ng of total RNA) with 48 [micro]L of nuclease-free water and 50 [micro]L of TaqMan Universal PCR Master Mix. After we loaded 100 [micro]L of the sample-specific PCR mixture into 1 sample port, the cards were centrifuged twice for 1 min at 280g and sealed to prevent well-to-well contamination. The cards were placed in the Micro Fluidic Card Sample Block of an ABI Prism 7900 HT Sequence Detection System (Applied Biosystems). The thermal cycling conditions were 2 min at 50[degrees]C and 10 min at 95[degrees]C, followed by 40 cycles of 30 s at 97[degrees]C and 1 min at 59.7[degrees]C. Each Micro Fluidic Card has a unique barcode, and Sequence Detection System plate documents store information on the plate type, detector, sample/target gene configurations, thermal cycling conditions, data collection, and raw fluorescence data at each cycle.

Micro Fluidic Cards were analyzed with RQ documents and the RQ Manager Software for automated data analysis. Experiments for 3 different donor cells, carried out in duplicate, were analyzed together as 1 relative quantity (RQ) study. Expression values for target genes were normalized to the concentration of 18S rRNA, which showed the least variation among reference genes in our monocyte/macrophage/foam cell model. Gene expression values were calculated based on the comparative threshold cycle (Ct) method (6), in which RNA samples were designated as calibrators to which the other samples were compared. In short, the Ct data for all human ABC transporters and 18S rRNA in each sample were used to create [DELTA]Ct values ([Ct.sub.ABC transporter] - [Ct.sub.18S rRNA]). Thereafter, [DELTA][DELTA]Ct values were calculated by subtracting the [DELTA]Ct of the calibrator from the Ct value of each target. The RQs were calculated with the equation: RQ = [2.sup.-[DELTA][DELTA]Ct]. For calculating the RQ of ABC transporter mRNA in macrophages compared with monocytes, monocyte RNAs were designated as calibrators. To analyze the RQ amounts of ABC transporters as an effect of 9-cis RA/TO901317 stimulation, macrophage RNAs were used as calibrators. The SDs for [DELTA]Ct and [DELTA][DELTA]Ct values were calculated from the single Ct values with the equation: SD[DELTA]Ct = [square root]([SD.sub.1.sup.2] + [SD.sub.2.sup.2]). The [DELTA]Ct values (SD) for the expression of all ABC transporter genes in monocytes are given in Table 1 (also see Table 1 in the online Data Supplement). We selected [DELTA]Ct values >25 as the cutoff for absence of expression. The mean RQs of ABC transporter mRNA in macrophages relative to monocytes and of 9-cis RA/TO901317-treated cells relative to control-treated macrophages of 3 different donors were combined and are listed in Table 1.

The ranges of the RQ values were calculated by use of the equation: RQ = [2.sup.-[DELTA][DELTA]Ct], with [DELTA][DELTA]Ct + SD and [DELTA][DELTA]Ct - SDs. The Micro Fluidic Cards detect a 2-fold difference in gene expression at the 99.7% confidence level. The efficiencies of all target and reference amplifications were nearly identical as analyzed by serial dilutions using 2, 1, 0.5, 0.25, and 0.125 ng of calibrator cDNA. When we plotted the log input amount of cDNA vs the [DELTA]Ct values, the slope was <0.1. The correlation coefficients were always >0.95, which is comparable to our previously established method (5). We assessed the within-run and day-to-day imprecision of our assay by measuring 4 identical samples in duplicate; the CVs were <1.6% and <2.9%, respectively.

As can be seen in Table 1, 30 ABC transporters displayed detectable mRNA expression in human primary monocytes, based on [DELTA]Ct values >25. Twenty-six genes were induced more than 2-fold during macrophage differentiation, and 12 genes were sensitive to LXR/RXR agonist incubation, with 10 up-regulated ABC transporters and only 2 down-regulated genes. Although the differentiation-dependent and sterol-regulated induction of ABCA1 and ABCG1 is well established (7), parallel transcript profiling, using our Human ABC Transporter TaqMan Low-Density Array, revealed several additional differentiation-dependent ABC transporters and novel LXR/RXR-regulated ABC transporters, including ABCB1 (MDR1), ABCB9, ABCB11 (BSEP), ABCC2 (MRP2), ABCC5 (MRP5), ABCD1 (ALD), ABCD4, and ABCG2. Despite the large dynamic range of gene regulation (e.g., a 24.5-fold induction of ABCA1 by 9-cis RA/T0901317), the range of differential transcript expression between 3 different donors was quite narrow (21.9-27.4). This implies that the interindividual differences in response are much smaller than the differentiation-dependent and lipid-regulated effects, allowing screening processes with a limited number of probands.

These findings are particularly relevant for lipidomics and cardiovascular research, as these ABC transporters are novel candidates for lipid disorders and pharmacologic targets for lipid-modulating drugs.

In summary, we have developed a Human ABC Transporter TaqMan Low-Density Array based on the TaqMan chemistry, the Micro Fluidic Card, and the 7900HT Sequence Detection System. Compared with standard Taq-Man reverse transcription-PCR methods, the Micro Fluidic Card requires less sample material (2 ng instead of 50 ng of total RNA-equivalents per gene), only one-tenth the volume of TaqMan Universal Master Mix, and much less hands-on time. This assay could be a useful tool for monitoring dysregulated ABC transporter mRNA profiles in human lipid disorders and cancer-related multidrug resistance. Furthermore, the pharmacologic and metabolic regulation of ABC transporter gene expression important for drug development could be analyzed in large screening approaches using this Human ABC Transporter Taq-Man Low-Density Array.

We thank Ernst Arnoldi, Astrid Potratz, and Andrea Geiger for support and discussions, and Manfred Haas for excellent technical assistance. This study was funded by grants from the Deutsche Forschungsgemeinschaft (SFB585-02/A1) and was supported by Applied Biosystems.

References

(1.) Dean M, Hamon Y, Chimini G. The human ATP-binding cassette (ABC) transporter superfamily. J Lipid Res 2001;42:1007-17.

(2.) Borst P, Zelcer N, van Helvoort A. ABC transporters in lipid transport. Biochim Biophys Acta 2000;1486:128-44.

(3.) Litman T, Druley TE, Stein WD, Bates SE. From MDR to MXR: new understanding of multidrug resistance systems, their properties and clinical significance. Cell Mol Life Sci 2001;58:931-59.

(4.) Schuierer M, Langmann T. Molecular diagnosis of ABC-transporter related diseases. Expert Rev Mol Diagn 2005;5:755-67.

(5.) Langmann T, Mauerer R, Zahn A, Moehle C, Probst M, Stremmel W, et al. Real-time reverse transcription-PCR expression profiling of the complete human ATP-binding cassette transporter superfamily in various tissues. Clin Chem 2003;49:230-8.

(6.) Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods 2001;25:402-8.

(7.) Schmitz G, Langmann T. Transcriptional regulatory networks in lipid metabolism control ABCA1 expression. Biochim Biophys Acta 2005;1735:1-19.

DOI: 10.1373/clinchem.2005.059774

Thomas Langmann, * Richard Mauerer, and Gerd Schmitz (Institute of Clinical Chemistry, University of Regensburg, Regensburg, Germany; * address correspondence to this author at: Institute of Clinical Chemistry and Laboratory Medicine, University Hospital Regensburg, Franz-Josef-Strauss-Allee 11, D-93053 Regensburg, Germany; fax 49-941-944-6202, e-mail thomas.langmann@klinik.uni-regensburg.de)
Table 1. Expression and regulation of ABC transporters in monocytes,
macrophages, and 9-cis RA/T0901317-stimulated macrophages. (a)

Gene Assay ID Monocyte
 [DELTA]Ct (SD) (b)

ABCA1 Hs00194095_ml 13.51 (0.38)
ABCA2 Hs00292232_m1 14.59 (0.52}
ABCA3 Hs00184593_ml 22.36 (0.23)
ABCA4 Hs00184367_ml n.e.
ABCAS HsOD363322_m1 17.9D (D.45)
ABCA6 Hs00365329_ml 19.06 (0.19)
ABCA7 Hs00185303_m1 16.48 (0.14)
ABCAB HsOD200350_m1 n.e.
ABCA9 Hs00329320_ml 19.56 (0.31)
ABCA10 Hs00365268_ml n.e.
ABCA12 Hs00292421_ml n.e.
ABCA13 Hs00541599_ml n.e.
ABCB1 Hs00184491_ml n.e.
ABCB2 Hs00184465_m1 15.61 (0.17)
ABCB3 Hs00241060_m1 15.93 (0.21)
ABCB4 Hs0024D956_m1 20.82 (0.11)
ABCBS Hs00698751_ml n.e.
ABCB6 Hs00180568_ml 19.55 (0.11)
ABCB7 Hs00188776_ml 14.75 (0.17)
ABCB8 Hs00185159_ml 18.56 (0.30)
ABCB9 Hs00608690_m1 22.29 (0.68)
ABCB10 Hs00429290_ml 14.66 (0.29)
ABCB11 Hs00184824_m1 n.e.
ABCC1 HsOD219905_ml 16.75 (0.13)
ABCC2 Hs00166123_ml 19.57 (0.81)
ABCC3 Hs0035B656_ml 16.72 (0.47)
ABCC4 Hs00195260_ml 16.80 (0.24)
ABCC5 Hs00194701_m1 19.72 (0.16)
ABCC6 Hs00184566_m1 19.90 (0.52)
ABCC7 Hs00357011_ml n.e.
ABCCB Hs00165861_ml n.e.
ABCC9 Hs00245832_ml n.e.
ABCC10 Hs00375716_ml 17.39 (0.51)
ABCC11 Hs00261567_ml n.e.
ABCD1 Hs00163610_ml 17.35 (0.65)
ABCD2 Hs00193054_m1 n.e.
ABCD3 Hs00161065_m1 15.79 (0.28)
ABCD4 Hs00245390_ml 16.16 (0.25)
ABCE1 Hs00759267_sl 13.29 (0.23)
ABCF1 Hs001537D3_ml 15.81 (0.11)
ABCF2 Hs00606493_ml 16.79 (0.12)
ABCF3 HsOD217977_m1 15.31 (0.21)
ABCG1 Hs00245154_ml 16.91 (0.19)
ABCG2 Hs00184979_m1 n.e.
ABCG4 Hs00223996_m1 n.e.
ABCG5 Hs00223686_ml n.e.
ABCGB Hs00223690 m1 n.e.

Gene RQ Diff. (c) RQ 9-cis
 RA/T0901317 (d)

ABCA1 8.57 (7.77-9.46) 13.86 (12.64-15.15)
ABCA2 2.13 (1.95-2.32) 2.08 (1.58-2.72)
ABCA3 25.63 (24.58-26.96) 1.32 (0.95-1.82)
ABCA4 n.e. n.e.
ABCAS 9.32 [8.54-10.17) 0.99 (0.95-1.05)
ABCA6 6.18 (5.92-6.44) 1.37 (1.29-1.46)
ABCA7 1.15 (0.97-1.36} 2.50 (2.34-2.70)
ABCAB n.e. n.e.
ABCA9 0.93 (0.75-1.15) 1.31 (1.13-1.51)
ABCA10 n.e. n.e.
ABCA12 n.e. n.e.
ABCA13 n.e. n.e.
ABCB1 136.75 (95.14-196.55) 11.67 (9.03-15.07)
ABCB2 2.04 (1.95-2.14) 1.28 (1.11-1.47)
ABCB3 2.20 [2.08-2.33) 1.03 (0.90-1.18)
ABCB4 4.3D [3.69-5.D1) 1.09 (1.07-1.20)
ABCBS n.e. n.e.
ABCB6 4.99 (4.62-5.38) 1.19 (0.97-1.29)
ABCB7 1.72 (1.55-1.9D) 1.64 (1.99-1.81)
ABCB8 8.07 (6.89-9.46) 0.86 (0.82-0.90)
ABCB9 55.27 (45.78-66.72) 0.35 (0.33-0.37)
ABCB10 6.22 (5.82-6.65) 0.59 (0.54-0.65)
ABCB11 217.84 (156.86-302.54) 3.47 (2.71-4.45)
ABCC1 8.11 (6.79-9.75) 1.85 (1.84-1.86)
ABCC2 1.02 (0.73-1.92) 3.54 (3.09-3.94)
ABCC3 4.84 (4.28-5.48) 0.99 (0.92-1.09)
ABCC4 2.89 (2.72-3.D8) 0.88 (0.85-0.91)
ABCC5 34.84 (30.53-39.76) 2.31 (1.96-2.73)
ABCC6 2.31 [1.87-2.85) 1.48 (1.44-1.53)
ABCC7 n.e. n.e.
ABCCB n.e. n.e.
ABCC9 n.e. n.e.
ABCC10 3.34 (3.17-3.51) 1.20 (1.D6-1.22)
ABCC11 n.e. n.e.
ABCD1 12.57 (11.55-13.68) 2.98 (2.71-3.28)
ABCD2 n.e. n.e.
ABCD3 7.94 (7.18-8.77) 1.12 (0.85-1.90)
ABCD4 3.65 (3.42-3.89) 2.15 (1.91-2.42)
ABCE1 1.10 (1.05-1.16} 1.19 (1.09-1.35)
ABCF1 1.38 (1.25-1.53) 1.10 (0.96-1.20)
ABCF2 4.88 (4.66-5.12) 1.12 (0.97-1.29)
ABCF3 1.72 (1.62-1.82) 1.10 (1.00-1.21)
ABCG1 5.83 (5.45-6.24) 24.50 (21.89-27.41)
ABCG2 94.68 (92.79-96.60) 0.49 (0.93-0.56)
ABCG4 n.e. n.e.
ABCG5 n.e. n.e.
ABCGB n.e. n.e.

(a) The mean relative quantities of ABC transporter mRNA and the range
of 3 different donors are depicted. Genes that are regulated more than
2-fold ([greater than or equal to]2.0 or [less than or equal to]0.5)
are considered as significantly regulated. Induced genes are depicted
in red, down-regulated genes are depicted in blue.

(b) Cutoff >25 OCt.

(c) RQ of mRNA comparing gene expression of macrophages and monocytes.
Values are the mean (range).

(d) RQ of mRNA comparing gene expression of 9-cis RA/T0901317-treated
macrophages and control-treated macrophages. Values are the mean
(range).

(e) n.e., not expressed.
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Title Annotation:Technical Briefs
Author:Langmann, Thomas; Mauerer, Richard; Schmitz, Gerd
Publication:Clinical Chemistry
Date:Feb 1, 2006
Words:2789
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