extfieldsofstudy: Chemistry Medicine

s2fieldsofstudy: Biology Medicine

text:
Arginase attenuates inhibitory nonadrenergic noncholinergic nerve-induced nitric oxide generation and airway smooth muscle relaxation

Background Recent evidence suggests that endogenous arginase activity potentiates airway responsiveness to methacholine by attenuation of agonist-induced nitric oxide (NO) production, presumably by competition with epithelial constitutive NO synthase for the common substrate, L-arginine. Using guinea pig tracheal open-ring preparations, we now investigated the involvement of arginase in the modulation of neuronal nitric oxide synthase (nNOS)-mediated relaxation induced by inhibitory nonadrenergic noncholinergic (iNANC) nerve stimulation. Methods Electrical field stimulation (EFS; 150 mA, 4 ms, 4 s, 0.5 – 16 Hz)-induced relaxation was measured in tracheal preparations precontracted to 30% with histamine, in the presence of 1 μM atropine and 3 μM indomethacin. The contribution of NO to the EFS-induced relaxation was assessed by the nonselective NOS inhibitor L-NNA (0.1 mM), while the involvement of arginase activity in the regulation of EFS-induced NO production and relaxation was investigated by the effect of the specific arginase inhibitor nor-NOHA (10 μM). Furthermore, the role of substrate availability to nNOS in EFS-induced relaxation was measured in the presence of various concentrations of exogenous L-arginine. Results EFS induced a frequency-dependent relaxation, ranging from 6.6 ± 0.8% at 0.5 Hz to 74.6 ± 1.2% at 16 Hz, which was inhibited with the NOS inhibitor L-NNA by 78.0 ± 10.5% at 0.5 Hz to 26.7 ± 7.7% at 8 Hz (P < 0.01 all). In contrast, the arginase inhibitor nor-NOHA increased EFS-induced relaxation by 3.3 ± 1.2-fold at 0.5 Hz to 1.2 ± 0.1-fold at 4 Hz (P < 0.05 all), which was reversed by L-NNA to the level of control airways in the presence of L-NNA (P < 0.01 all). Similar to nor-NOHA, exogenous L-arginine increased EFS-induced airway relaxation (P < 0.05 all). Conclusion The results indicate that endogenous arginase activity attenuates iNANC nerve-mediated airway relaxation by inhibition of NO generation, presumably by limiting L-arginine availability to nNOS.

Background
The inhibitory nonadrenergic noncholinergic (iNANC) nervous system is the most effective bronchodilating neural pathway of the airways. Inhibition of nitric oxide synthase (NOS) markedly reduces the iNANC relaxation of both guinea pigs [1-3] and human airways [4,5], indicating that nitric oxide (NO) is a major neurotransmitter of the iNANC system. In addition, vasoactive intestinal polypeptide (VIP) has been implicated in iNANC relaxation [6,7], and colocalization of NOS and VIP has been demonstrated both in guinea pig [8] and in human airway nerves [9].
NO is generated by a family of NOS isoforms that utilize the semi-essential amino acid L-arginine, oxygen and NADPH as substrates to produce NO and L-citrulline [10]. Three isoforms of NOS have been identified: neuronal NOS (nNOS), endothelial NOS (eNOS) and inducible NOS (iNOS). In the airways, the constitutive NOS (cNOS) isoforms are mainly expressed in the iNANC neurons (nNOS), the endothelium (eNOS) and the epithelium (nNOS and eNOS), whereas iNOS, which is induced by proinflammatory cytokines during airway inflammation, is mainly expressed in macrophages and epithelial cells [11].
Another L-arginine metabolizing enzyme is arginase, which hydrolyzes L-arginine to L-ornithine and urea. Arginase is classically considered to be an enzyme of the urea cycle in the liver, but also occurs in extrahepatic tissues, including the lung [12,13]. Two distinct isoforms of arginase have been identified in mammals: arginase I, a cytosolic enzyme, mainly expressed in the liver, and arginase II, a mitochondrial enzyme, which is mainly expressed in extrahepatic tissues [13]. Extrahepatic arginase has been implicated in the regulation of NO synthesis by limiting the availability of intracellular L-arginine for NOS [12][13][14][15]. In addition, arginase might be involved in cell growth and tissue repair via the production of L-ornithine, a precursor of polyamines and proline [13]. Both arginase isoforms are constitutively expressed in the airways, particularly in the bronchial epithelium and in fibroblasts from peribronchial connective tissue [12]. Using a perfused guinea pig tracheal tube preparation, we have previously demonstrated that endogenous arginase activity is functionally involved in the regulation of airway smooth muscle tone [16]. Endogenous arginase potentiates methacholine-induced airway constriction by diminishing agonist-induced NO production, by competition with epithelial cNOS for the common substrate, Larginine [16]. Previous studies had demonstrated that Larginine availability is indeed a limiting factor for agonistinduced NO-production and airway relaxation [17].
A role for arginase in the iNANC system has been found in internal anal sphincter [18] and penile corpus cavernosum [19,20]. Thus, arginase inhibition increased electrical field stimulation (EFS)-induced relaxation of these preparations, indicating that endogenous arginase activity attenuates nNOS-mediated NANC relaxation.
The role of endogenous arginase in the regulation of iNANC-derived NO generation in the airways has not yet been investigated. In the present study, we demonstrated that endogenous arginase activity and L-arginine availability are importantly involved in the modulation of iNANC nerve-mediated NO-production and relaxation of guinea pig tracheal smooth muscle.

Animals
Male specific pathogen free HsdPoc:Dunkin Hartley guinea pigs (Harlan Heathfield, UK), weighing 500 -800 g, were used in this study. The animals were group-housed in individual cages in climate-controlled animal quarters and given water and food ad libitum, while a 12-h on/12h off light cycle was maintained.
All protocols described in this study were approved by the University of Groningen Committee for Animal Experimentation.

Tissue preparation
The guinea pigs were sacrificed by a sharp blow on the head. After exsanguination, the trachea was removed from the larynx to the bronchi and rapidly placed in a Krebs-Henseleit (KH) buffer solution of 37°C, gassed with 95% O 2 and 5% CO 2 . The composition of the KH-solution in mM was: NaCl 117.50; KCl 5.60; MgSO 4 1.18; CaCl 2 2.50; NaH 2 PO 4 1.28; NaHCO 3 25.0 and D-glucose 5.50; pH 7.4. The trachea was prepared free of serosal connective tissue. Twelve single proximal tracheal open-ring preparations were mounted for isotonic recording (0.3 g preload) between two parallel platinum point-electrodes in waterjacketed (37°C) organ baths containing 20.0 ml of gassed KH-solution and indomethacin (3 µM), which remained present during the whole experiment to eliminate any influence of prostanoids.

Electrical field stimulation-induced relaxation experiments
After a 30 min equilibration period, tracheal preparations were relaxed with isoprenaline (0.1 µM) to establish basal tone. After a washout period of 30 min with three washes with fresh KH solution, maximal contraction of the tracheal preparations to histamine was determined with cumulative additions of the agonist (0.1, 1, 10 and 100 µM). After washout (30 min), the tracheal preparations were precontracted with histamine to 30% of the maximal histamine-induced tone in the presence of atropine (1 µM) to prevent EFS-induced cholinergic airway contraction. On the plateau, biphasic EFS (150 mA, 4 ms, 4 s, 0.5 -16 Hz) was applied and frequency response curves (0.5 -16 Hz in doubling steps) were recorded. Per preparation, one frequency response curve was performed. When used, the nonselective NOS inhibitor N ω -nitro-L-arginine (L-NNA; 100 µM), the specific arginase inhibitor N ωhydroxy-nor-L-arginine (nor-NOHA; 10 µM), a combination of both inhibitors, or L-arginine (0.3, 1.0 or 5.0 mM) were applied 30 min prior to histamine-addition. In line with previous observations [21], neither the NOS inhibitor, nor the arginase inhibitor and L-arginine affected agonist-induced tone in the open-ring preparations. All measurements were performed in triplicate. After the final EFS-induced relaxation, followed by washout, isoprenaline (10 µM) was added to establish basal tone.

Data analysis
All individual relaxations elicited by EFS were estimated as peak height of the EFS-induced response, and were expressed as a percentage of maximal relaxation as established in the presence of isoprenaline. The contribution of NO to the EFS-induced relaxation was determined by the effect of the NOS inhibitor L-NNA. Similarly, the role of arginase activity in the modulation of EFS-induced airway relaxation was determined by the effect of the arginase inhibitor nor-NOHA. The role of substrate availability in EFS-induced airway relaxation was assessed by measuring the responses in the presence of various concentrations of exogenous L-arginine.
All data are expressed as means ± s.e.m. Statistical significance of differences was evaluated using a paired or unpaired two-tailed Student's t-test as appropriate, and significance was accepted when P < 0.05.

Results
In guinea pig tracheal open-ring preparations, EFS induced a frequency-dependent relaxation of histamineinduced tone ranging from 6.6 ± 0.8% at 0.5 Hz to 74.6 ± 1.2% at 16 Hz. Incubation with the NOS inhibitor L-NNA caused a significant inhibition of the EFS-induced relaxation at 0.5 to 8 Hz, particularly at the lower frequencies.
In contrast, incubation with the arginase inhibitor nor-NOHA significantly enhanced EFS-induced relaxation by 3.3 ± 1.2-fold at 0.5 Hz to 1.2 ± 0.1-fold at 4 Hz (P < 0.05 all; Fig. 1), that is, at the frequencies most sensitive to L-NNA. The increased relaxation in the presence of nor-NOHA was fully reverted by L-NNA (P < 0.05 all), to the level of control preparations in the presence of L-NNA alone (Fig. 1).
Incubation with L-arginine caused a dose-dependent increase of total EFS-induced relaxation, which was maximal at 5.0 mM L-arginine (data not shown). In the presence of 5.0 mM L-arginine, a significant increase in EFSinduced relaxation was observed at all frequencies compared to untreated preparations (P < 0.05 all, Fig. 2). At the lower frequencies, this increase was similar to the increase in EFS-induced relaxation observed after incubation with nor-NOHA (Fig. 2).

Discussion
Using perfused tracheal preparations, we have previously demonstrated that endogenous arginase activity is involved in the regulation of agonist-induced airway constriction by inhibition of NO production, presumably by competition with cNOS for L-arginine [16]. In the present study, we demonstrated that endogenous arginase activity is also involved in the regulation of iNANC nerve-mediated airway smooth muscle relaxation.
In line with previous observations [1], it was demonstrated that the NOS inhibitor L-NNA inhibited EFSinduced iNANC relaxation of guinea pig tracheal preparations. This inhibition was most pronounced at the lower frequencies, indicating a prominent role of nNOS-derived NO at these frequencies. By contrast, inhibition of arginase activity by nor-NOHA caused a considerable (up to 3.3-fold) increase in EFS-induced relaxation at low frequencies, indicating that endogenous arginase activity restricts iNANC nerve-mediated airway smooth muscle relaxation. The increased relaxation after arginase inhibition was completely reverted by L-NNA, clearly indicating that arginase activity attenuates iNANC nerve-mediated airway smooth muscle relaxation by limiting NO production, presumably by competition with nNOS for their common substrate, L-arginine.
The observation that exogenous L-arginine significantly enhanced the EFS-induced airway smooth muscle relaxation confirms that L-arginine is indeed a limiting factor in EFS-induced, NO-mediated airway smooth muscle relaxation under basal conditions. Remarkably, the effect of nor-NOHA was similar to that observed in the presence of the maximally effective L-arginine concentration, indicating that endogenous arginase activity is a major factor in regulating the neural NO-mediated airway smooth muscle relaxation.
Recently, we discovered that increased arginase activity is importantly involved in the pathophysiology of asthma by contributing to the allergen-induced NO-deficiency and subsequent airway hyperresponsiveness to methacholine after the early asthmatic reaction, by limiting the availability of L-arginine for cNOS to produce bronchodilating NO [22]. Arginase activity as well as expression was also considerably increased in two mouse models of aller-gic asthma, irrespective whether the animals were challenged with ovalbumin or with Aspergillus fumigatus [23]. Moreover, enhanced mRNA or protein expression of arginase I was observed in human asthmatic lung tissue, particularly in inflammatory cells and in the airway epithelium [23], while increased arginase activity was measured in asthmatic serum [24]. In guinea pig tracheal strips, it has previously been demonstrated that EFSinduced iNANC relaxation is reduced after ovalbuminchallenge, due to a deficiency of iNANC nerve-derived NO [25]. Thus, it is tempting to speculate that increased Role of NO and arginase in iNANC nerve-induced relaxation of guinea pig tracheal smooth muscle Figure 1 Role of NO and arginase in iNANC nerve-induced relaxation of guinea pig tracheal smooth muscle. Electrical field stimulation-induced relaxation of precontracted guinea pig tracheal open-ring preparations in the absence and presence of the NOS inhibitor L-NNA (100 µM), the arginase inhibitor nor-NOHA (10 µM) or a combination of both inhibitors. Results are means ± s.e.m. of 8 experiments. *P < 0.05 and **P < 0.01 compared to control, † P < 0.05 and ‡ P < 0.01 compared to nor-NOHA-treated.
arginase activity could similarly be involved in allergeninduced reduced iNANC activity.
A role for arginase by restricting the L-arginine availability for nNOS in iNANC nerves has also been proposed in the pathophysiology of erectile dysfunction [19]. In support, increased expression and activity of arginase II contributing to reduced NO production has been demonstrated in diabetic cavernosal tissue [26]. Neuronal arginase may also be involved in gastrointestinal motility disorders, by reducing nNOS-mediated iNANC relaxation in the internal anal sphincter [18].

Conclusion
This is the first demonstration that endogenous arginase activity is functionally involved in iNANC nerve activity in the airways, by attenuating the generation of nNOSderived NO. Disturbance of this novel regulation mechanism of airway responsiveness might be involved in the pathophysiology of allergic asthma.

Abbreviations
cNOS, constitutive nitric oxide synthase; EFS, electrical field stimulation; eNOS, endothelial nitric oxide synthase; iNANC, inhibitory nonadrenergic noncholinergic; Role of L-arginine availability and arginase in iNANC nerve-induced relaxation of guinea pig tracheal smooth muscle Figure 2 Role of L-arginine availability and arginase in iNANC nerve-induced relaxation of guinea pig tracheal smooth muscle. Electrical field stimulation-induced relaxation of precontracted guinea pig tracheal open-ring preparations in the absence and presence of exogenous L-arginine (5.0 mM) or the arginase inhibitor nor-NOHA (10 µM). Results are means ± s.e.m. of 5-13 experiments. *P < 0.05 and **P < 0.01 compared to control.


extfieldsofstudy: Biology Medicine

text:
CPD Photolyase Gene from Spinacia oleracea : Repair of UV-Damaged DNA and Expression in Plant Organs

DNA repair/Cyclobutyl pyrimidine dimers/Photolyase/ Spinacia oleracea. The UV-B radiation contained in solar radiation has deleterious effects on plant growth, development and physiology. Specific damage to DNA caused by UV radiation involves the cyclobutyl pyrimidine dimers (CPD) and the pyrimidine (6-4) pyrimidone photoproducts. CPDs are repaired by CPD photolyase via a UV-A/blue light-dependent mechanism. The gene for the class II CPD photolyase has been cloned from higher plants such as Arabidopsis , cucumbers and rice. We isolated and characterized the cDNA and a genomic clone encoding the spinach class II CPD photolyase. The gene consisted of 3777 bases and 9 exons. The sequence of amino acids predicted from the nucleotide sequence of the cDNA of the gene was highly homologous to that of the higher plants listed above. When a photolyase-deficient Escherichia coli strain was transformed with the cDNA, photoreactivation activity was partially restored, by the illumination with photoreactivating light, resulting in an increased survival and decreased content of CPDs in the Escherichia coli genome. In both the male and female plants, the gene was highly expressed in leaves and flowers under the condition of 14-h light and 10-h dark cycle. The expression in the roots was quite low compared with the other organs.

INTRODUCTION
Ultraviolet (UV) radiation is cytotoxic and mutagenic for living organisms. Ozone absorbs UV-C (wavelengths shorter than 290 nm) radiation in solar radiation and controls the amount of UV-B (between 290 and 320 nm) radiation reaching the earth. Chlorofluorocarbons and other gases emitted in the process of human industrial activity deplete the stratospheric ozone layer, resulting in increased UV-B radiation reaching the surface of the earth. 1,2) Increases in UV-B radiation affect ecosystems and cause a reduction in phytoplankton photosynthesis 3) and an increase in UV-induced DNA damage in pelagic icefish eggs. 4) UV-B radiation affects plant growth and productivity. 5,6) Some species of plants and cultivars of a given species exhibit relatively high sensitivity to UV-B radiation, while others are apparently not affected by enhanced UV-B radiation. 6,7) Supplemental UV-B levels corresponding to 16 to 25 percent ozone depletion were reported to affect soybean seed yields. 8) Several UV-B-sensitive cultivars of higher plants, including rice 9,10,11) and maize, 12) have been reported, and removal of the UV-B wavelengths from the light increased plant growth. 13,14) UV-B radiation induces the formation of DNA lesions such as cyclobutyl pyrimidine dimers (CPDs), pyrimidine pyrimidone (6-4) photoproducts ((6-4) photoproducts) and Dewar isomers. Among them, the CPD is a major UVinduced photoproduct. 15) These lesions block DNA synthesis during replication and interfere with mRNA synthesis during transcription, resulting in cell death if not removed. 16) Mutation may occur when the lesion bypass DNA synthesis proceeds beyond the lesion by a translesion DNA polymerase such as the Escherichia coli DNA polymerase IV. 16) Living organisms have developed a variety of DNA repair mechanisms during evolution, such as photoreactivation, nucleotide excision repair and recombinational repair, 17) of which photoreactivation is a light-dependent process and the others are light-independent processes. Photoreactivation is mediated by damage-specific photolyases, i.e., CPD photolyase and (6-4) photolyase. CPD photolyases are categorized into class I or class II according to their amino acid sequences. 18) Photolyases over prokaryotes to eukaryotes carry FAD as a chromophore, 19,20) which is excited by light energy and then monomerizes the CPDs in an electron transfer reaction. 21) Plants must overcome the injurious effects of UV radiation (principally UV-B) in solar radiation, because they are completely dependent on solar radiation for photosynthesis and cannot escape from UV radiation. The mutation frequency of maize endosperm of pollen grains treated with visible light after UV irradiation was significantly lower than that in an untreated control, suggesting the presence of light-dependent repair mechanisms in plants. 22) Photoreactivation might be an effective repair of UV-induced DNA damage in plants. 23,24) The activity of photolyase-removing CPDs was found in Arabidopsis. 25) Ahmad et al . (1997) first isolated the gene encoding the class II CPD photolyase in Arabidopsis ecotype Columbia. 26) A mutant of Arabidopsis ecotype Lansberg ( uvr2-1 ) defective in the light-dependent repair of CPDs was more hypersensitive to UV-B radiation than the wild-type plants. 27) Recently, the genes for photolyase were isolated from cucumbers 28) and rice 29) and classified into the class II CPD photolyase from the predicted amino acid sequences.
A reduced yield of crop plants because of UV-B radiation affects the global food supply. Hidema et al . (1996) demonstrated that two rice cultivars, Sasanishiki and Norin 1, showed different UV sensitivity, 9) and that the differences were due to varying levels of CPD photolyase activity. 30) Norin 1, carrying defective activity of the CPD photolyase, exhibited a lower growth rate under UVB irradiation than Sasanishiki with wild-type photolyase activity. 31) These results suggest the importance of photoreactivation for the growth of higher plants irradiated with UV-B.  characterized the cDNA encoding the cucumber CPD photolyase, and demonstrated that the photoreactivation activity in the first leaves of cucumber plants changed during the diurnal cycle. 28) The photoreactivation activity of CPDs in spinach seedlings and the localization of CPD photolyase activity in spinach cells have previously been investigated. 32,33) Spinach is a diecious plant, in which male and female flowers are generated on different roots, unlike Arabidopsis and cucumbers, which are monoclinous and monoecious plants, respectively. A detailed investigation of photoreactivation, including the isolation and characterization of the gene in plants, has been limited to Arabidopsis , 26) cucumbers 28) and rice. 29) Like cucumbers, spinach is relatively sensitive to UV-B radiation 34) ; both plants are essential foods for many people worldwide. It is necessary to determine the nucleotide sequence of the gene and predict the amino acid sequence in order to characterize the spinach CPD photolyase and to compare it with that of other organisms.
In this study, we isolated the cDNA encoding the spinach CPD photolyase and examined its photoreactivation ability following the complementation of Escherichia coli deficient in photoreactivation and by enzyme-linked immunosorbent assay (ELISA). The expression of the gene for CPD photolyase in the leaf, flower, stem and root was examined separately in male and female plants.

Plant materials and growth conditions
The plant growth room was kept at 23-25 ° C. Spinach seeds of ( Spinacia oleracea L., cv Orai) were sown on vermiculite in a plastic tray and germinated in the dark. The seedlings were illuminated by 4 fluorescent lamps (40 w) at a 50 cm height under 14-h light and 10-h dark cycle. Hyponex (N:P:K= 10:5:10) diluted 1000-fold was used as a fertilizer.

Escherichia coli strain and media
Escherichia coli NKJ3002 ( recA uvrA phr ) 35) was used for the complementation assay of the CPD photolyase gene of spinach. Luria broth (L broth) and buffer were used as described previously. 36,37)

UV irradiation
A germicidal lamp (15 w, Toshiba) was used to irradiate the DNA and Escherichia coli cells with UV-C radiation.

Extraction of genome DNA from spinach leaves
Spinach genome DNA was prepared from approximately 5 g of one-month-old young leaves according to the cetyltrimethylammonium bromide (CTBA) procedures 38) with slight modifications. The leaves were ground in liquid nitrogen and mixed with 5 ml of 2 x CTAB extraction buffer (2% CTAB, 0.1 M Tris-HCl, pH 8.0, 20 mM EDTA, 1.4 M NaCl and 1% polyvinyl pyrrolidone) heated to 70 ° C, and then the mixture was incubated at 55 ° C for 10 min with gentle mixing. The precipitates were dissolved at 55 ° C in 5 ml of 1 M NaCl-TE (10 mM Tris-HCl, pH 8.0, 1 M NaCl, 1 mM EDTA) after extraction with chloroform/isoamyl alcohol. The DNA was stored at -20 ° C after treatment with RNase, phenol extraction and ethanol precipitation.

Partial cloning of a gene for the class II CPD photolyase from spinach by PCR
A partial region of a gene for the CPD photolyase in spinach was amplified by PCR using degenerate PCR primers designed from highly conserved amino acid sequences in Arabidopsis and Chlamidomonus CPD photolyase. The primer sequences were AC2 (5'-GTIGAYGCICAYAAYGT-IGTICC-3') and AC4R (5'-CATRAAICCRTGCATYTTICC-3'). 29

Isolation of cDNA encoding spinach CPD photolyase and determination of its nucleotide sequence
Total RNA was prepared from 2g of spinach leaves using TRIZOL reagent (Invitrogen). Poly(A) + RNA was purified from total RNA using a QuickPrep Micro mRNA purification kit (Pharmacia Biotech). cDNA was synthesized from poly(A) + RNA by 5'-RACE and 3'-RACE. Double-stranded cDNA was synthesized from poly(A) + RNA using the cDNA Synthesis Kit (Stratagene) and inserted into pGEM-T Easy Vector (Promega). After the cDNA was sequenced, it was excised at an Eco RI site and cloned into the Eco RI site of pBluescript II SK+, named pSpCPDPR1-7.

Determination of the genome sequence of the CPD photolyase gene of spinach
Five DNA fragments, including a part of the spinach CPD photolyase gene, were amplified using five pairs of PCR primers and cloned on pGEM-T Easy Vectors. These primers were designed on the basis of the sequence of cDNA for the spinach CPD photolyase. Each PCR product consisted of 1077 bp, 867bp, 713 bp, 708bp and 542 bp.

Complementation of Escherichia coli mutant deficient in photoreactivation with the gene for spinach CPD photolyase
We introduced pSpCPDPR1-7 into Escherichia coli strain NKJ3002. The transformants were grown to the medium log phase in LB medium containing ampicillin and 5 mM IPTG at 37 ° C. The cultures were diluted and spread on LB agar medium. The Escherichia coli on the agar plates were exposed to UV-C radiation from a germicidal lamp at a dose rate of 0.003 Jm -2 s -1 and thereafter illuminated with white light from a fluorescent daylight lamp for 60 min to allow photoreactivation.

Repair of CPD from genomic DNA of Escherichia coli carrying the spinach photolyase gene
Escherichia coli NKJ3002 transformed with pSpCPDPR1-7 was grown in L broth with ampicillin and 1 mM IPTG to the late log phase. The cells re-suspended in phosphatebuffered saline (PBS) were irradiated with 0.1 Jm -2 of UV-C in a plastic dish with gentle agitation. The irradiated cells were illuminated with a fluorescent daylight lamp for 18 hrs. The UV region included in the fluorescent light was cut off with an acrylic plastic plate. After the extraction of Escherichia coli DNA, the relative amount of CPDs was determined by ELISA. 39) The CPD-specific antibody used was MX-thymine dimer-HRP (Kyowa Medex Co., Japan).

Determination of the expression of the gene for CPD photolyase in organs of spinach by real-time PCR
All leaves, flowers, stems and roots were harvested during flowering from one plant body of spinach grown under the conditions mentioned above. The stems were the part of the plant that did not have any leaves, flowers or roots. The total RNA was isolated separately from these organs using TRI-ZOL Reagent (Invitrogen). Template cDNA for real-time PCR was synthesized using the Thermoscript TM RT-PCR System (Invtrogen). The primers for CPD photolyase were SpCPD-34R (5'-CTTCATCAACGGCGTGGATTAAG-3'). The reference standard was spinach cytosolic ribosomal protein L23 mRNA. The relative quantity of spinach CPD photolyase mRNA was determined by real-time PCR (Gene-Amp 5700 Sequence Detection System, PE Biosystems) following RT-PCR. The primers were SpCPD-34R and 5'-ATGACCTCCAAACCGGTACC-3'. Double-strand DNAspecific dye SYBR Green was used to detect and quantitate the PCR products as fluorescent molecular probes (SYBR Green PCR Core Reagents, PE Biosystems). The relative extent of the gene expression for the spinach CPD photolyase was expressed as the ratio of the initial amount of mRNA for the CPD photolyase to that for the cytosolic ribosomal protein L23.

Cloning of the CPD photolyase gene of spinach
Amino acid sequences of the CPD photolyase in Arabidopsis 26) and Chlamydomonas 40) were applied to design PCR primers for isolation of the CPD photolyase gene from spinach. A 1.4-kbp DNA fragment was successfully amplified from spinach genome DNA by using two degenerate primers, AC2 and AC4R. 29) The amplified DNA fragment contained a sequence similar to the class II CPD photolyase of Arabidopsis . Sequences of the fragment were employed to design primers for cloning cDNA by RT-PCR. Unknown regions of the 5' side and 3' side of cDNA were determined by 5'-RACE and 3'-RACE using the primers listed above. The entire cDNA was obtained by joining three parts of cDNA, i.e., the 5' region, the 3' region and the region cloned by the AC2 and AC4R primers. The fulllength cDNA consisted of 1476 bases containing a single ORF of 491 amino acids. The cDNA sequence has been registered in the GenBank database, under accession number AY267198.
Fourteen primers including forward and reverse directions were designed from the cDNA sequences. Genome DNA was subjected to PCR using these primers, resulting in the amplification of seven DNA fragments. The nucleotide sequence of each fragment was determined and aligned according to its cDNA sequence. The nucleotide sequence from the initiation codon, ATG, to the termination codon, TGA, consisted of 3776 bases. The spinach photolyase gene was defined to include nine exons. Furthermore, a ca. 400bp region upstream from the initiation codon was determined by Thermal Asymmetrical Interlaced PCR, 41) although the regulatory region of the gene has not been analyzed. The genome sequence has also been registered in the GenBank database, under accession number AY267199. Table 1 shows the sequence of exon-intron boundaries. All eight introns contain a 5'-GT and 3'-AG sequence. There was a pyrimidine-rich sequence upstream of the AG in many organisms. 42)

Similarity of amino acid sequences predicted from cDNA to CPD photolyase of other organisms
The cDNA encoded 491 amino acid residues, which is quite similar to the number of residues of CPD photolyase in Arabidopsis , cucumbers and rice, 496, 489 and 506, res- 1) base number of exons and introns, 2) sequences of 5' side and 3' side of intron, Uppercase and lowercase indicate exon and intron sequences, respectively. Bold face indicates conserved sequence in splice junction. pectively. 28,29) Spinach photolyase shows a high degree of homology to other class II CPD photolyases from Arabidopsis (71%), 26) cucumbers (71%), 27) rice (64%) 29) (Fig. 1), Drosophilla (48%), 18) Chlamydomonas (58%) 40) and Monodelphis (53%) 43) (data not shown). The spinach photolyase in this study was therefore shown to be a class II CPD photolyase (Fig. 2). At the C-terminus of the photolyase, we predicted a nuclear localization signal by using the Prediction of Protein Sorting Signals and Localization Sites in Amino Acid Sequences Program (Fig. 1), which suggests targeting the spinach photolyase in the nucleus.

Complementation of mutant Escherichia coli deficient in photoreactivation by the cloned cDNA
Escherichia coli NKJ3002 (recA, uvrA, phr) was transformed with pSpCPDPR1-7 so we could investigate whether the cloned cDNA contained photoreactivation activity. The survival of NKJ3002 and NKJ3002/pBluescript II SK+ cells irradiated with 0.15 Jm -2 of UV-C light was about 10 -4 with or without photoirradiation. The survival of NKJ3002/ pSpCPDPR1-7 irradiated with 0.15 Jm -2 of UV-C light was 5 × 10 -3 when they were illuminated with white light (Fig.  2). These results demonstrate that the cDNA isolated from spinach encodes protein with photoreactivation activity.

Light-dependent removal of CPDs from genome DNA in UV-irradiated NKJ3002/pSpCPDPR1-7 cells
We investigated the repair of CPD on the genome DNA of Escherichia coli NKJ3002 carrying pSpCPDPR1-7. The remaining CPDs in NKJ3002/pSpCPDPR1-7 cells illuminated with white light for 18 h after 0.1 Jm -2 of UV-C irradiation was approximately 50% of the unilluminated control (Fig. 3). The repair of CPDs was not enhanced in NKJ3002/ pBluescript II SK+ by white light illumination (Fig. 3). The number of living cells in phosphate-buffered saline did not decrease during the 18-h white light illumination. Therefore, it was demonstrated that NKJ3002/pSpCPDPR1-7 showed an enhanced repair activity of CPDs by white light illumination. We concluded that the cDNA isolated from spinach was the gene for the class II CPD photolyase.

Expression of the gene for CPD photolyase in the leaves, flowers, stems and roots of spinach
The amount of expression of the CPD photolyase gene   was determined in the leaves, flowers, stems and roots of spinach grown under 14-h light and 10-h dark conditions. As shown in Table 2, in both males and females, the level of expression of the CPD photolyase gene in spinach was higher in the leaves and flowers than in the roots in each quarterly independent experiment, although the expression level varied widely in the leaves and flowers among the experiments (Table 2).

DISCUSSION
We isolated and characterized the gene for class II CPD photolyase from spinach, which consisted of 3776 bases. The cDNA consisting of 1476 bases encoded the protein of 491 amino acid residues, which was quite similar to the class II CPD photolyase of higher plants, including Arabidopsis, cucumbers and rice. The genome sequence of the gene consisted of 9 exons, which was the same as the class II CPD photolyase gene of Arabidopsis 44) and cucumbers (GenBank AB084265).
The cDNA was introduced into Escherichia coli strain NKJ3002, which was defective in photoreactivation. When NKJ3002 carrying the gene was illuminated with white light after irradiation with UV-C light, the survival significantly increased compared with that of NKJ3002 transformed with an empty vector and an unilluminated NKJ3002 (Fig. 2). Therefore, we demonstrated that the cDNA conferred the photoreactivation activity to Escherichia coli.
We examined the extent of the repair of CPDs in genome DNA in NKJ3002 carrying the cDNA. The amount of CPDs decreased in white light-illuminated cells by less than 50% of the amount in the unilluminated NKJ3002 (Fig. 3). These results indicate that the cDNA complemented the deficiency of photoreactivation in NKJ3002. Therefore, we concluded that the cDNA cloned in the present study encodes the class II CPD photolyase.
The level of photoreactivation of Escherichia coli NKJ3002 transformed with the spinach photolyase gene was lower than that observed in Escherichia coli with the gene for cucumbers 28) and rice 29) (Fig. 2). The vector pBluescript II SK+ used for cloning contains bacteriophage T3 and T7 promoters in opposite orientations. The direction of the gene inserted in the vector may affect the expression of the photolyase gene on pSpCPDPR1-7. In the examination of the light-dependent removal of CPDs from the Escherichia coli genome DNA, white light was illuminated for a long time, 18 h, to allow the full, light-dependent repair of CPDs ( Table  2).
The CPD photolyase protein has been reported to be the most abundant in floral tissues and at a very low level in the roots of Arabidopsis. 45) The amount of photolyase in Arabidopsis leaves varied according to the development stage. The levels of the protein in 7-to 14-d leaves in Arabidopsis were higher than those of younger leaves. In spinach, a high level of expression was observed in the leaves and flowers harvested at flowering, although the relative content of the mRNA varied widely from experiment to experiment ( Table  2). The white light induced CPD photolyase gene expression in Arabidopsis. 45) The low level of CPD photolyase expression in spinach roots observed in the present study may be due to the decreased intensity of fluorescent white light and solar radiation under the soil.
The transcript level in the leaves and flowers varied widely among the experiments (Table 2). Hidema and Kumagai 30) reported that rice exhibited a remarkable change of CPD photoreactivation activity during the leaf developmental stage. Takahashi 28) also found that the activity in cucumbers fluctuates throughout a single day. The large fluctuation in the level of expression observed might reflect the mRNA content in leaves harvested at various developmental stages and times of day.
A rapid decrease in the CPDs and (6-4) photoproducts was observed when Arabidopsis cells were exposed to UV-A and white light after UV-B-irradiation, although these photoproducts were slightly reduced in the dark. 46) CPD photolyases repair CPDs much more rapidly than the lightindependent repair process in plant tissues. 47) Seedlings of the UV-B-resistant mutant uvi1 of Arabidopsis grown under white light exhibited a more rapid removal of CPDs than that in wild-type seedlings, indicating an increased photoreactivation activity in uvi1 Arabidopsis. The CPD photolyase gene expression in the uvi1 mutant was higher than in the wild-type plants. 48) UV-B radiation is known to induce the expression of the gene for the CPD photolyase, 45) which suggests that a defense system against UV is induced by UV itself. Plant leaves efficiently receive solar energy for photosynthesis and are simultaneously exposed to a massive dose of solar UV radiation. Flowers, the sexual organs which produce seeds, should be protected from UV damage.
Since plants cannot flee from the UV radiation found in solar radiation, photoreactivation facilitated by the white light in solar radiation is assumed to be the most efficient repair system of UV-induced DNA lesions. Rice cultivar Norin 1 is quite a bit more sensitive to UV-B radiation than Sasanishiki, resulting in a lower growth rate for Norin 1 under UV-B irradiation than for Sasanishiki. 9) The hypersensitivity of Norin 1 was ascribed to a defect in the lightdependent repair of CPDs caused by functionally altered CPD photolyase. 31) These results strongly suggest the importance of photoreactivation for the growth of higher plants irradiated with solar UV-B radiation under natural conditions. Cultivated vegetables such as soybeans, tomatoes, spinach and cucumbers are sensitive to UV-B radiation. 34) Alleviation of the reduced yield of crop plants caused by solar UV-B radiation is required to ensure the future global food supply. If the resistance of agricultural plants to UV radiation increases, the yield will likely increase. Introducing the gene for photolyase into plants to enhance their


extfieldsofstudy:
Computer Science
Biology
Medicine

text:
Construction and validation of the APOCHIP, a spotted oligo-microarray for the study of beta-cell apoptosis

Background Type 1 diabetes mellitus (T1DM) is a autoimmune disease caused by a long-term negative balance between immune-mediated beta-cell damage and beta-cell repair/regeneration. Following immune-mediated damage the beta-cell fate depends on several genes up- or down-regulated in parallel and/or sequentially. Based on the information obtained by the analysis of several microarray experiments of beta-cells exposed to pro-apoptotic conditions (e.g. double stranded RNA (dsRNA) and cytokines), we have developed a spotted rat oligonucleotide microarray, the APOCHIP, containing 60-mer probes for 574 genes selected for the study of beta-cell apoptosis. Results The APOCHIP was validated by a combination of approaches. First we performed an internal validation of the spotted probes based on a weighted linear regression model using dilution series experiments. Second we profiled expression measurements in ten dissimilar rat RNA samples for 515 genes that were represented on both the spotted oligonucleotide collection and on the in situ-synthesized 25-mer arrays (Affymetrix GeneChips). Internal validation showed that most of the spotted probes displayed a pattern of reaction close to that predicted by the model. By using simple rules for comparison of data between platforms we found strong correlations (rmedian= 0.84) between relative gene expression measurements made with spotted probes and in situ-synthesized 25-mer probe sets. Conclusion In conclusion our data suggest that there is a high reproducibility of the APOCHIP in terms of technical replication and that relative gene expression measurements obtained with the APOCHIP compare well to the Affymetrix GeneChip. The APOCHIP is available to the scientific community and is a useful tool to study the molecular mechanisms regulating beta-cell apoptosis.

Background
Type 1 diabetes mellitus (T1DM) is an autoimmune disease caused by the selective destruction of the pancreatic beta-cells causing impaired insulin secretion. Beta-cell dysfunction and death in T1DM is the result of direct contact with activated macrophages and T-lymphocytes, and/ or exposure to soluble mediators secreted by these cells, such as cytokines, oxygen free radicals and nitric oxide (NO) [1]. There is increasing evidence that apoptosis is the main cause of beta-cell death at the onset of T1DM [1][2][3][4] and after islet transplantation [1,5,6] Apoptosis is a regulated process, affected by expression of diverse pro-and anti-apoptotic genes [1,7,8] Cytokines play a role in the inflammatory destruction of islet grafts immediately after transplantation [9][10][11] a process that hampers the success of islet transplantation in patients with T1DM. In vitro beta-cell exposure to the cytokine interleukin (IL)-1β induces functional impairment, whereas exposure to IL-1β in combination with interferon (IFN)-γ and/or tumor necrosis factor (TNF)-α, induces beta-cell death by apoptosis in rodent and human islet cells after a period of 3-9 days [1][2][3] These cytokines modify the expression of several hundreds of genes in beta-cells, including stress response genes that are either protective or deleterious for beta-cell survival, whereas genes related to differentiated beta-cell functions are mostly down-regulated [12,13] DNA microarrays have become a standard tool for several applications in molecular biology and provide a way to monitor the expression of thousands of genes in a single assay. The two major microarray platforms presently in use are the high density microarrays produced by in situ synthesis and the arrays produced by deposition of presynthesized DNA onto a solid surface. One widely used implementation is the Affymetrix GeneChip which uses photolithography and solid-phase chemistry to produce high density arrays of 25-mer oligonucleotides [14]. Spotted long oligonucleotides arrays were recently introduced as an alternative to cDNA arrays and in situ synthesized oligonucleotide arrays [15]. Utilizing this technology we have prepared a custom oligonucleotide array representing 574 genes chosen for their putative involvement in beta cell death, the APOCHIP. Gene selection was based on the analysis of a large number of array determinations of cytokine-and double stranded RNA-treated primary beta cells or insulin-producing INS-1 cells using Affymetrix chips [5,[16][17][18]. This targeted and low cost array to be made freely available to the research community will allow the performance of detailed time-course studies and thus contribute to the understanding of the molecular events leading to beta cell dysfunction and death in diabetes mellitus.
To evaluate the performance of the spotted oligonucleotide array, we presently used two approaches. First we investigated the ability of the individual probes to respond to changes in target concentration. We expected that the M-value (log 2 fold-change of test versus reference) Figure 1 Representation of the APOCHIP and GeneChip microarrays. Representation of genes on the two array types illustrating the number of genes represented by at least one probe or probe set on each array type and the total number of genes present on the arrays. A total of 515 genes were represented on both array types. The first column σω m is the average measurement error, the second σ s is the spot variation, and the third σ c is the channel variation. The fourth column is the median fold-change, exp [(ζ 1j -ζ 2j ) ln (2)], between the two channels. The last column is the ratio of median fold-change to median fold-change for concentration 1.

Representation of the APOCHIP and GeneChip microarrays
would be proportional to the target concentration on a logarithmic scale and that slopes ideally would be close to one. We performed a weighted regression of M on concentration (log 2 scale) using data from hybridisations at five different target concentrations. Next we used ten dissimilar RNA samples to compare the gene expression between the spotted array and Affymetrix platforms. We expected that this would yield a sufficient number of differentially expressed genes to allow for meaningful conclusions to be drawn about the concordance between the two platforms.
Our data suggest a good reproducibility for technical replications both within and between chips. High concordance to the Affymetrix GeneChip in terms of relative gene expression indicates that the APOCHIP is a reliable tool for studying the molecular mechanisms involved in beta cell apoptosis.

The Model based approach Internal replication
The results of the internal replicates are shown in Table 1. The spot variation was roughly 1.5 fold as large as the measurement variation. This shows that there are moderate variations in the replicated spots within a chip. The channel variation was of the same order of magnitude as the spot variation except for the lowest target concentration, where it was much larger (~3 fold). The origin of the channel variation remains to be clarified, but it may be due to intensity dependent properties between the two channels. By normalising the two channels against one another, block wise, we obtained only a small reduction in the channel variance (data not shown). The two chips with the lowest concentration generally showed higher variance values than at the higher concentrations, and may reflect that the target concentration for the test sample (1/3 µg/20 µL) is close to the lower detection limit of this system, a hypothesis supported by the substantial increase in "bad" and "not found" calls around this concentration (data not shown). Table 2 shows the estimated additional variance as compared to that predicted by the model when calculating log 2 fold-changes from technical replications. Most of the estimates are negative, showing that there is no additional variance and indicating a good reproducibility for technical replication ( Figure 2).

External replication
The spot variance provides information on the difference between using a one-colour system as opposed to a twocolour system. In a two-colour system the spot variance terms for each channel within a chip cancel when using ratios. Thus a log2 fold-change obtained from two chips in a one colour system will have a variance of at least 2σs2 + 2σ2ω2 compared to a two colour system where it is 2σs2 (Table 3 and Additional file 2). As depicted in Table 3 the estimated one-colour variance was comparable to the spot variance when print-tip differences were accounted for in the normalisation.
Comparison of gene expression measurements illustrating the technical reproducibility of the spotted long oligonucle-otide array Figure 2 Comparison of gene expression measurements illustrating the technical reproducibility of the spotted long oligonucleotide array. The upper left subplot shows technical replication between spotted arrays within print batches. The upper right subplot shows technical replication between replicated spots within arrays. The lower left subplot shows a self-self hybridisation (the sample is labelled to both Cy3 and Cy5 separately and hybridised together) illustrating the reproducibility between Cy3 and Cy5 fluorofores. Data was normalised using a lowess transformation implemented in the MIDAS software. Pearson correlation coefficients (r) are shown for each comparison and are representative (mean) of at least four independent experiments. Lines are lines of equality.

Fold-change regression
The result of the regression is illustrated in Figure 3. If the fold-change is proportional to the concentration the slope β in the regression of log 2 fold-changes is 1. As can be seen in Figure 3 most slopes are in the range 0.8-1.2 (78%). Interestingly, there seems to be a spread around 1 suggesting that each gene has its own sensitivity to changes in the concentration. A formal test at level 5% for the slope being equal to one gives acceptance in only 25% of the genes. Furthermore, as the lower left subplot of Figure 3 shows, when the signal intensity is very high all slopes are either larger than 1 or very small. Also, a small value of the slope does not imply that the probe does not respond at all, rather the sensitivity to changes in the concentration is limited. The physical origin of these phenomena is unclear. Using the linear relation between the measured log 2 fold-changes and the log 2 concentration we may ask for which probes are we able to detect a true fold-change of a certain size. Using average properties and considering only internal replication we found in our experiments that for a true log 2 fold-change λ the measured log 2 fold-change is roughly normally distributed with mean βλ and standard deviation 0.09. If we want the measured log 2 foldchange to be larger than αλ, for some chosen value of α, the probability of this event is the probability that a standard normal variate is bigger than (α-β) λ/0.09. As an example, if we require this latter probability to be bigger than 0.5, we find that we can use the probes with β > α.
Elaborating on this example, if we take α = 0.5, there are in our experiment 97 % of the probes satisfying β > 0.5, with 34 probes only left out.
As depicted in Table 1 we observed a discrepancy between the log 2 concentration and the median log 2 fold-change. This may partly be accounted for by the scanner settings which were set to fixed but arbitrary values. Considering the self-self hybridisations (concentration 1, Table 1) it is evident that the settings for the test channel were too high compared to the settings for the reference channel. This effect may be minimized by using automated settings generated by the scanning software (data not shown). However, the ratios between two consecutive concentrations are close to the expected values except for the highest concentration where it is lower than expected (Table 1).

Cross platform comparison
We compared the relative expression of 515 genes present on both the APOCHIP and Affymetrix GeneChip 230A arrays. These genes, corresponding to 949 probes on the APOCHIP, were used to compare the relative gene expression profiles in ten rat RNA samples. On average, 93 % of the spots were called "good" by the Scanarray Express software and 7 % was called either "bad" or "not found". The samples and the pooled reference was analysed separately on GeneChip 230A arrays, since this system utilizes single colour hybridisations. Normalised M-values (sample vs. reference) were calculated for each probe set on the array using RMA [19] and Affymetrix MAS 5.0 algorithm that compares signal intensity from perfect-match and mismatch 25-mers [14]. On average, 65 % of the genes surveyed on these arrays were called "present" and 34 % were called "absent" and the remainder "marginal" using MAS 5.0. This software also reports calls for "increased" (I), "decreased" (D) and "no change" (NC) for the relative gene expression. To take into account possible differences due to normalisation methods we compared the results obtained by our approach (MAS 5.0/median centering) to those obtained using RMA and a LOWESS (LOcally WEighted Scatterplot Smoothing) procedure implemented in MIDAS [20]. We found similar results particularly when low intensity data was excluded, as described below (data not shown).
As low intensity data are prone to increased variation [21] and therefore less reliable we set the following criteria for the comparison: a. Affymetrix array: 1. For "NC" calls both test and reference pool signal should be called "present", 2. For "I" calls the test signal value should be called "present", 3. For "D" calls the reference pool signal should be called "present"; b. APOCHIP: Measurements associated with "not found" or "bad" were excluded. We then focused on the remaining 496 probes that fulfilled the above criteria in all ten measurements on both platforms. The results are listed in Table 4 and illustrated in Figure 4 and Figure 5.
Without this quality filtering of the probes the median of the weighted Pearson correlation was 0.39, whereas the filtering increased this value to 0.64 (first two lines of Table 4). A further filtering of the probes may be relevant. If a gene has no differential expression between the ten samples there is no possibility of estimating the correlation. Similarly, if the probe does not respond at all in one of the two platforms, the estimated correlation is unreliable.
In an attempt to avoid this we removed probes that had a low variation over the ten samples in either one or both of the two platforms. The Affymetrix GeneChips showed the largest range of the log2 ratios. To compare a large number of probes and include only the most varying we set an arbitrary cut-off of 0.25 for the Affymetrix platform. To include a similar number of probes for the APO-CHIP we set an arbitrary cut-off of 0.0625 for the variance of this platform. This reduced the number of probes to 267 (164 genes) ( Figure 4). For this reduced set of probes the median correlation was 0.84 (Table 4), indicating a tight concordance between the two array types.
The distribution of the genes excluded from the analyses is illustrated in Figure 6. Of the 164 most varying genes, 9 gave discordant results exhibiting a negative correlation (Table 5). Further analysis of these genes revealed that in most instances the signal intensities were below the mean signal intensity on either one or both platforms. Moreover, two of these genes displayed variations close to the lower limits for one or both platforms as described above, indicating that the correlations obtained for these genes may be less reliable (Table 5). To further address this issue we performed a BLAST [22] search based on the long oligonucleotide sequences. We then mapped these probes and corresponding Affymetrix probe-sets to the mRNA sequence on which the APOCHIP probe was based. Second, we checked for sequence overlap between the probes of the corresponding platforms. As depicted in Table 5 we found that six of the Affymetrix probe-sets mapped to the APOCHIP mRNA but only one probe-set (Affymetrix ID: 1367713_at) showed overlap with the APOCHIP oligonucleotide probe sequence. For two of the remaining probes the Affymetrix probes did not properly match the APO-CHIP mRNA, suggesting that these sequences interrogate different sequences for these genes. For the last APOCHIP probe (GenBank ID: XM_213699) the mRNA annotation was changed and the 60-mer did not match the transcript perfectly. In cases where both platform sequences align perfectly to the APOCHIP mRNA other factors such as differences in specificity and sensitivity, RNA splice variants, and RNA structure of the probes may be important.

Discussion
Microarrays have been widely used for expression profiling [14,23], discovery of gene function [24,25], pathway dissection [26], classification of clinical samples [27,28] as well as investigation of RNA splice variants [29]. Several studies have been conducted comparing gene expression across platforms with varying results [30][31][32][33][34][35][36][37][38][39]. Whereas quantitative RT-PCR are usually found to agree well with corresponding array data concerns have been raised in some studies comparing different array formats [29,32,33,37]. Thus, Kuo et al. [32] compared cDNA and Affymetrix 25-mer arrays and reported little concordance. The data in this study, however, was originated from two different laboratories and it is not clear whether the poor agreement was due to differences in the array types. Moreover, these results were based on absolute measurements which may be misleading [40]. Li et al. [29] and Kothapalli et al. [33] also used cDNA and Affymetrix arrays and in both cases found substantial discrepancies; based on these findings, it was inferred that cDNA arrays often fail to identify differentially expressed genes. On the other hand, strong support for the use of long oligonucleotide microarrays comes from two independent studies [30,34], and several recent studies suggest a robust concordance between the different microarray platforms [40][41][42].
Hughes et al. [30] reported high concordance utilizing data from 60-mer oligonucleotide arrays synthesized by an ink-jet oligonucleotide synthesizer, cDNA arrays and Affymetrix GeneChip arrays. Barczak et al. [34] compared relative gene expression measurements of a large collection of spotted 70-mers against Affymetrix GeneChips and found good agreement.
Although, the majority of the most differentially expressed probes yielded high correlations, there were exceptions (Table 5). There was also a group of genes exhibiting relatively large log 2 fold-change variation in one, but not the other, platform ( Figure 6). These findings may partly be explained by differences in sensitivity and specificity and other probe specific effects. Of note, in some cases differences in transcript annotation and/or In the first column a global median centering is used, and in the second a median centering for each of the 8 blocks is used. The last column gives 2σ s 2 for comparison. RNA splicing may be more important than discrepancies in array performance. Several factors may influence the reproducibility when comparing data across platforms.
Proper gene identification is essential as genes can only be compared if they are accurately identified on both platforms [43]. This can be difficult as transcript information often comes from different sources and are continuously being improved. The starting material must be consistent and procedures for RNA handling standardized. There are several labelling procedures in use, amplification versus no amplification, direct versus indirect dye incorporation which may contribute to downstream biases [43]. In this study the samples were treated identically prior to RNA amplification and similar amplification and labelling protocols were used for both array types. Pre-processing and methods for data handling may also influence the final results [44]. As stated in the Results section, there were differences using different spot identification software and beta log residual variance normalisation algorithms, but these differences were substantially reduced by removing low intensity data and by comparing only the most varying genes (data not shown). Moreover, when comparing gene expression data across platforms it is essential to do so using relative measurements, since absolute measurements are affected by probe and platform specific properties that may cause misleading interpretations [40]. As discussed above, low signal intensities are prone to increased variation [21] a phenomenon that is well established for most array formats, including spotted 30 mer arrays [45], in situ synthesized 24 mer arrays [46] and GeneChips [47,48]. Thus, it was not surprising to find that the correlation between differential measurements improved significantly when lowintensity measurements were excluded. Although intensities between two identical samples labelled to different dyes are rarely equal across all spots, we find that much of this variation is removed after proper normalisation (Figure 4 subplot 3). Two-colour hybridisations are generally used for spotted arrays, and many study designs involve comparison of the test sample to a common reference sample. Accurate quantification of a particular gene requires that the reference sample contains sufficient RNA to produce a clear signal for the corresponding probe. Reference samples may be generated from a pool of several cell lines, or as here, by pooling of all samples obtained from different tissues. The rationale for pooling the samples is that differentially expressed transcripts will also be present in the reference. Reference pools may not always produce sufficient signal intensity to allow for accurate quantification of some of the probes. When using Affymetrix MAS 5.0 software to analyse the pool reference for the subset of genes associated to both platforms, 76 % of the probe sets were called "present", as compared to 65 % "present" calls on average in the present data. Different designs such as a reference-free setup where pairs of test samples are compared directly may be preferable depending on the application [49].

Representation of the APOCHIP linear regression for the dilution series
Oligonucleotide probe design may also be important for signal intensity and for measuring differential gene expression. Oligonucleotide probes are designed on the basis of sequence. Several criteria, such as GC content and melting point, are used in the design but it is not possible to accurately account for differences in structure which may lead to unwanted steric effects. We observed that there were sometimes large numerical differences in the signal intensity of different spotted probes corresponding to the same gene (data not shown) a phenomenon that has been noted by others [14,34]. In a few cases long oligonucleotides representing the same gene gave discordant results. Such differences between probes may depend on several factors, including low sensitivity of some probes, alternative splicing, nucleic acid structure, distance from the 3' end of the RNA transcripts, GC content, and crosshybridisation to unknown or poorly characterized mRNAs including pseudo genes and non-coding RNAs. Hence, the use of standardised sets of probes and protocols is an important issue when data from different laboratories and array platforms are compared [40][41][42]50,51]. Selection of a suitable microarray platform is influenced by several considerations. The Affymetrix system has been widely used for several applications and holds the advantage of standardisation in terms of probes and hybridisation protocols and, to some extent, data quantification [40]. However, this technology has been limited by cost considerations for projects involving a large number of samples. Spotted arrays are labour intensive, but they can be made in large quantities by individual laboratories at a lower cost. Moreover, sequences with high homology to other genes can be avoided and probes for novel genes and gene variants may readily be designed.
In conclusion, we have constructed and validated the APOCHIP, a spotted microarray designed for the study of beta cell death in diabetes mellitus that may be of use to the scientific community. Designing and printing in-Distribution of probes according to log 2 fold-change variation house arrays offers a flexible mean to carry out combinations of extensive multipoint and detailed time course gene expression analysis, following exposure of pancreatic beta-cells to different pro-apoptotic stimuli. We expect that this array will help research in the field enabling the performance of more detailed and complete experiments.

Conclusion
We have validated a rat oligonucleotide microarray constructed for the study of beta cell death in diabetes mellitus. We evaluated the technical reproducibility of the array by estimating the variance associated with the internal and external replication. We then used a fold-change regression model to estimate the ability of the probes to respond to changes in target concentration. Finally, we used ten dissimilar RNA samples to compare the relative gene expression between the spotted array and Affymetrix platforms. We found a high reproducibility for technical replications both within arrays and between arrays, with most oligonucleotide probes responding to target concentration in a manner close to that predicted by the model. There was a clear relation between successive data filtering and concordance between the two array types; by comparing only the most variable genes on both platforms we found that there was a high concordance between the APOCHIP and the GeneChip platform, supporting the validity of this approach.

Isolation of total RNA
Total RNA was isolated from snap frozen cells and tissue using Trizol. Each sample was dissolved in 1 mL Trizol ® reagent (Invitrogen) on ice and homogenised using a Fastprep homogeniser (Bio 101 Savant Instruments Inc.) according to the manufacturer's instructions. Trizol was removed by addition of chloroform followed by isopropanol precipitation. The precipitates were washed using 75 % ethanol. The amount and purity of RNA was quantified photo-spectrometrically by measuring the optical density at 260 and 280 nm and the integrity was checked by agarose gel electrophoresis.

cRNA preparation Affymetrix arrays
For each hybridisation reverse transcription was performed on 5 µg total RNA for 1 hour at 42°C using a T7 oligo(dT) 24 -primer and reverse transcriptase (SuperScript II; Life Technologies Inc.). Second-strand cDNA synthesis was performed for 2 hours at 16°C using Escherichia coli DNA polymerase I, DNA ligase, and RNase H (Life Technologies Inc.) followed by incubation in 50 mM NaOH and 0.1 mM EDTA for 10 minutes at 65°C to degrade the RNA. After phenol-chloroform extraction and ethanol precipitation, in vitro transcription was performed for 6 hours at 37°C using biotin-16-UTP and biotin-11-CTP with an RNA transcript labelling kit (BioArray; Enzo Diagnostics). cRNA was purified on RNeasy spin columns (Qiagen), followed by fragmentation for 30 minutes at 95°C.

Spotted oligonucleotide chip
Total RNA extraction, reverse transcription on 5 µg total RNA and second strand cDNA synthesis were performed as described above. In vitro transcription was performed for 6 h at 37°C using amino-allyl-UTP and T7 Megascript Kit (Ambion). The produced cRNA was purified using Rneasy spin columns (Quiagen) followed by coupling of Cross-platform comparison illustrating the correlations between the APOCHIP and the Affymetrix array Figure 5 Cross-platform comparison illustrating the correlations between the APOCHIP and the Affymetrix array. The upper left subplot illustrates the raw data. The upper right subplot corresponds to data were low intensity data was removed. The lower left subplot corresponds to the most varying genes in the comparison.

Spotted oligonucleotide microarray procedures Oligonucleotide probe design
The genes on the spotted array were selected based on our large data set obtained with GeneChip (Affymetrix) analyses of two different treatments that induce beta cell apoptosis, namely cytokines and double stranded RNA [13,[16][17][18]. We used three criteria to select genes to grid in our custom microarray: First, largest numerical alterations in gene expression; Second, representing informative gene clusters (e.g. genes involved in NO production, signal transduction/transcription factors, bcl-2 family, ER stress, etc); Third, genes showing distinct expression patterns over a time course (identified by self organizing maps). The complete list of genes present in the APOCHIP is provided in Additional file 1. Moreover a number of genes were selected for normalisation purposes. These genes were chosen to cover a range of signal intensities from low, medium to high. For each gene on the array one to three 60-mer oligonucleotides were designed using the Array Designer software (Premier Biosoft International).

Hybridisation, washing and scanning
The probes were spotted in duplicate on Codelink slides (Amersham Biosciences Inc.) at 30 % relative humidity and 20°C using a VersArray Chipwriter from BioRad. For a standard hybridisation one µg of each Cy3 and Cy5 labelled target sample was applied to the microarray slide in a volume of 20 µL for 16 h at 42°C. Before scanning all slides were washed as previously described [30]. The two replicates were spotted below one another on the chips and all hybridisations were carried out twice on separate arrays. The samples were labelled with Cy3 and a common reference pool was labelled with Cy5. Following scanning of the glass slides the fluorescent intensities were quantified and background adjusted using an "adaptive circle" method implemented in the Scanarray Express software (PerkinElmer). Data was normalised by a blockwise median centering within individual hybridisation pairs and mean log 2 -expression ratios were calculated from the four measurements of each probe. Probes exhibiting expression values higher than 60000 (arbitrary units) in one chip within any comparison were discarded from the analyses. Probes exhibiting negative expression values in more than four chips were discarded from the analyses and remaining negative values were set to 1.

Experimental design A model-based approach for internal validation of spotted oligonucleotide probes Dilution series hybridisations
Total RNA and cRNA from rat kidney, heart, liver, and muscle tissue was prepared as described above. Equal amounts of cRNA from all samples were pooled and divided for fluorescent labelling to the dyes Cy3 and Cy5 as described above. Hybridisations were performed at five concentrations of Cy3 labelled target (0.3 µg/20 µL, 1 µg/ 20 µL, 2 µg/20 µL, 3 µg/20 µL, 4 µg/20 µL). The Cy5 material was used as reference and was kept at constant concentration of 1 µg/20 µL in all hybridisations. Arrays were scanned at identical laser (100 %) and PMT (50 for Cy5 and 65 for Cy3) settings.
In the spotted array the total variation contains contributions from: a. variations in the spots; b. variations in the two channels; c. variations between arrays. To study the variation in the system we modelled the log 2 expression value x gcj for gene g, channel c = 1, 2, and internal replicate j = 1, 2 as a sum of terms representing the different variations. Terms that are used to model the mean value structure are denoted levels and terms that are used to model the variance structure are called random. We wrote the log expression as a gene level (µ g ), plus an overall channel and replication level (ψ cj ), plus a random spot variation (u gj with variance σ 2 s ), plus a random gene specific channel difference (υ gc with variance σ 2 c ), plus, finally, a random measurement error (ε gcj with variance σ 2 ω gcj 2 , where Representation of the excluded genes that did not exhibit high variation of log 2 fold-change (on a log 2 scale) on both platforms Figure 6 Representation of the excluded genes that did not exhibit high variation of log 2 fold-change (on a log 2 scale) on both platforms. A; Genes that showed high variation of fold-change only on the long oligonucleotide array (log 2 fold-change variation: long oligonucleotide array > -4/ GeneChip < -2). B; Genes exhibiting low variation on both platforms (log 2 fold-change variation: long oligo array < -4/ GeneChip < -2) C; Genes exhibiting high variation of foldchange only on the GeneChip array (log 2 fold-change variation: long oligonucleotide array < -4/GeneChip > -2).
ω gcj 2 is a known term). Here σ 2 s (s for spot) reflects the difference in morphology of the spots and is not related to the gene. Similarly, σ 2 c (c for channel) reflects that the two channels react differently depending on the gene, the variation in this gene specific channel difference is then given by σ 2 c .
Mathematically we write the model as x gcj = µ g + ξ cj + u gj + λ gc + ε gcj . As suggested by Churchill et al. [52], we model some of the variation as random components. To take into account the larger variances associated with small expression values [21] we scaled the variances using the standard deviations s gcj for the pixel intensities of each spot supplied by the software. Transforming s gcj to the log 2 scale we used ω gcj = s gcj /[exp(x gcj ln(2))ln (2)]. The overall levels x icj were estimated by median values and we let y gcj = x gcj -x icj be the remainder when the estimated overall level was subtracted.

Internal replication
We first considered the variance of the measurement error. The measurement variance can be evaluated by looking at the difference d g = (y g11 -y g21 ) -(y g12 -y g22 ) between the two log 2 fold-changes corresponding to the internal replication. The variance of this difference is σ 2 s g 2 where s g 2 is the sum of the four terms of ω gcj 2 for gene g. A natural estimate for σ 2 is then the average of the squared scaled differences d g /s g .
Having estimated the measurement variance we could next estimate the spot variance σ s 2 and the channel variance σ c 2 . For the spot variance we considered the sum over the two channels of the difference between the two replicates: (y g11 -y g12 ) + (y g21 -y g22 ). The variance of this term is 8σ s 2 + σ 2 s g 2 , and having found the measurement variance σ 2 above we then used the observed variance of these terms to estimate the spot variance σ s 2 . Similarly, for the channel variance we considered the sum over the two internal replicates of the log 2 fold-changes (y g11 -y g21 ) -(y g12 -y g22 ), which has variance 8σ c 2 + σ 2 s g 2 . As above we estimated σ c 2 from the observed variance of these terms.

External replication
To examine the reproducibility of the external replication we calculated a log 2 fold-change for each of the two chips and considered the difference of these. We compared the variance of these differences with that predicted by the model.

Fold-change regression
For each probe and concentration we calculated a common log 2 fold-change from the two internal and the two external replicates. The variances of these are τ g 2 r gi 2 , where g is gene and i is concentration, and where r gi 2 is given through σ 2 ω 2 above. Next, for each gene we performed a regression of log 2 fold-change against the median of the log 2 fold-changes, where the factor τ g 2 in the variance describes how well the linear relation fits the data.

Cross platform comparison of gene expression
Total RNA and double stranded cDNA from ten dissimilar rat tissues were prepared as described above. To minimise the variation associated with preparation of double stranded cDNA, each sample of double stranded cDNA a. Low signal intensity (signal below mean of all arrays); b. Affymetrix and long oligonucleotide probes mapped to the APOCHIP target mRNA; c. Affymetrix and long oligonucleotide probes mapped partly or not at all to the APOCHIP target mRNA; d. Probes exhibiting variation close to the lower limits shown in Figure 4. *. New annotation obtained by BLAST.
was divided in two equal volumes that were used to prepare cRNA for hybridisation to Affymetrix GeneChips-RAE230A and for hybridisation to the spotted arrays.

Affymetrix arrays
A common reference pool was prepared by pooling equal amounts of cRNA from all samples investigated. We analysed 10 samples and common reference cRNA on Gene-Chips RAE-230A (Affymetrix Inc.). These arrays were hybridised with 15 µg of labelled cRNA for 16 h at 45°C while rotating. The chips were stained in an Affymetrix Fluidics station with streptavidin/phycoerythrin, followed by staining with an antistreptavidin antibody and streptavidin/phycoerythrin. The chips were scanned using a HPlaser scanner and the readings from the quantitative scanning were analyzed by the Affymetrix Gene Expression Analysis microarray Suite Software (MAS) 5.0. Each microarray was scaled to "150" as previously described [53]. Data was also normalised using the Robust Multiarray Analysis (RMA) normalisation approach in the Bioconductor Affymetrix package to the R project for statistical computing [19].

Spotted oligonucleotide chip
A common reference pool was prepared by pooling equal amounts of cRNA from all investigated samples. The reference pool was labelled to Cy5 and the ten samples were labelled to Cy3 as described above. For each sample one µg of each Cy3 and Cy5 labelled target was applied to the microarray slide. Data was normalised as described in the Hybridisation, washing and scanning section.

Comparison of relative gene expression between platforms
To identify genes common to both platforms we used a combination of publicly available databases, DAVID [54] and Affymetrix [55], to identify UniGene clusters (build 99) and GenBank accessions. Based on this information, we were able to compare gene expression measurements for 515 genes represented on both platforms (Figure 1). For each gene we calculated the correlation between the values from the two platforms using a weighted Pearson correlation. The weighted Pearson correlation is obtained from the usual Pearson correlation by replacing all the sums entering this formula by weighted sums, using the same weights as those used in the regression above (see Additional file 2). These weights were obtained from the spotted arrays and are also used for the GeneChip values.