2D Difference Gel Electrophoresis of Prepubertal and Pubertal Rat Mammary Gland Proteomes Helen Kim,*,†,‡,§ Mark B. Cope,†,§ Richie Herring,†,§ Gloria Robinson,§ Landon Wilson,§ Grier P. Page,‡,| and Stephen Barnes†,‡,§ Departments of Pharmacology & Toxicology and Biostatistics, the UAB Center for Nutrient-Gene Interaction, and the UAB Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, Alabama 35294 Received February 14, 2008
Rat mammary gland proteomes at day 21 (prepubertal) and day 50 (late puberty) were compared by 2D difference gel electrophoresis. Two-hundred fifty-one spots were significantly different (p < 0.05) in abundance. Peptide mass fingerprint analysis of a subset of these proteins identified two significantly over-represented classes including structural and blood proteins (increased), and metabolism-relevant proteins (reduced) in day 50 relative to day 21 glands. This is a first report of mammary gland proteome differences at these important breast cancer-relevant time-points. Keywords: DIGE • mammary • puberty • false discovery rate • 2D gel • Cydye • breast cancer • chemoprevention • peptide mass fingerprinting
Introduction Breast cancer remains the most common form of cancer in women.1 In the U.S.A., 178 480 new breast cancer cases in women were estimated for 2007 as well as 40 460 deaths.1 Breast cancer incidence rates vary from country to country, with the highest in the U.S.A. and Europe.2 Although the rates in Southeast Asia have traditionally been much lower, they have risen in conjunction with westernization of the Asian diet.3,4
period prior to vaginal opening (30-34 days of age), an early stage in pubertal development in these animals.12 It was, therefore, expected that the proteomes in the mammary gland prior to puberty (day 21) and after 4 weeks of increasing promotion of expression of steroid-sensitive genes by gonadal steroids (day 50) would have significant differences that would be manifested in distinct changes in protein abundances.
In rodent models of breast cancer, a similar time periodrelated sensitivity to carcinogenic agents has been demonstrated. The incidence and number of mammary tumors induced by the carcinogens 7,12-dimethylbenz[a]anthracene (DMBA) and N-methyl-N-nitrosourea (MNU) are maximal when single doses are administered to rats at 50 days of age, that is, in mid- to late-puberty.10,11 Under normal circumstances, rats are weaned from their dams at 21 days of age, a
The Center for Nutrient-Gene Interaction (CNGI) at the University of Alabama at Birmingham is investigating the changes that occur in the Sprague-Dawley rat mammary gland at the transcriptional, translational, and metabolite levels as the rat progresses through puberty, and at which level dietary polyphenols that are chemopreventive in rodent models of breast cancer have impact on the mammary gland. The present study is an initial assessment of the differences in the mammary gland proteome between day 21 and day 50 in untreated female Sprague-Dawley rats. This was accomplished by the twodimensional difference gel electrophoresis (2D-DIGE) proteomic approach,13 where pairs of protein mixtures labeled with fluorescent dyes, either Cy3 or Cy5, were resolved on twodimensional isoelectric focusing/sodium dodecyl sulfate electrophoresis gels (IEF/SDS-PAGE) (2DE); the information in the resultant 2D gel images was analyzed with DeCyder image analysis software. A pooled mixture of all samples labeled with a third dye, Cy2, was resolved on every gel, which generated a 2D spot pattern against which each spot volume was normalized. Finally, careful attention was paid to reducing bias in the overall experimental design.14
* To whom correspondence should be addressed. Helen Kim, PhD, Department of Pharmacology and Toxicology, MCLM 452, University of Alabama at Birmingham, 1918 University Boulevard, Birmingham, AL 35294, Tel: (205) 934-3880. Fax: (205) 934-6944. E-mail:
[email protected]. † Departments of Pharmacology and Toxicology. ‡ UAB Center for Nutrient-Gene Interaction. § UAB Comprehensive Cancer Center. | Department of Biostatistics.
Statistical analysis of the data included determination of false discovery rates for all fold differences, analysis of coefficient of variation as a function of normalized spot volume, and comparison of predicted molecular weights (Mrs) and isoelectric points (pIs) with observed Mrs and pIs. These approaches enabled a reduction in the number of protein differences that distinguished day 50 from day 21 mammary glands. Putative
Analysis of cancers in the survivors of the Hiroshima and Nagasaki nuclear explosions revealed that the largest increase in the risk of later life breast cancer occurred for girls who were in their midteens at the time of the explosion.5–7 This coincides with the period of most rapid growth in the mammary gland, which is driven by the surge in the levels of estrogens and progestins that occur with the onset of puberty.8 The mammary gland undergoes a substantial expansion of its epithelial cell population during this time.9 Eventually, the elevated steroid levels cause differentiation of the epithelial cells, a process that also occurs to an even greater extent during pregnancy.
4638 Journal of Proteome Research 2008, 7, 4638–4650 Published on Web 09/04/2008
10.1021/pr800121b CCC: $40.75
2008 American Chemical Society
2D-DIGE of Prepubertal and Pubertal Rat Mammary Gland Proteomes identifications were obtained for a subset of the significantly different spots that were detected by postanalysis Sypro Ruby staining, by excising the spots and processing them through peptide mass fingerprint analysis (PMF) using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). The results described here comprise an initial phase of a larger study ultimately examining the molecular basis of the chemopreventive actions of dietary polyphenols. This is to our knowledge a first analysis of proteomic differences that distinguish two time points in rat mammary gland development, day 21 and day 50, that are important with regard to chemoprevention.
Materials and Methods Animals. Impregnated female Sprague-Dawley rats (Charles River, Wilmington, MA) were maintained on AIN-76A diet (Harlan Teklad, Madison, WI) through pregnancy and throughout the postnatal and weaning period. For day 21 samples, litters were euthanized at weaning on day 21. For day 50 samples, litters were maintained on AIN-76A diet until day 50, at which time they were euthanized. Animal protocols were approved by the UAB Institutional Animal Care and Use Committee (IACUC). Rat tissues were processed as described by Lamartiniere and co-workers (42, 44). Mammary Gland Collection and Processing for 2D Gel Analysis. Rats were euthanized with carbon dioxide as per IACUC guidelines. The fourth right abdominal mammary gland was excised, manually scraped of fatty tissue on ice, then weighed, snap-frozen in liquid nitrogen, and finally stored at -80 °C. To generate homogenates, mammary gland samples were thawed from -80 °C, minced, and homogenized in 5 mL of isoelectric focusing (IEF) sample buffer (7 M urea/2 M thiourea/4% CHAPS/40 mM Tris-HCl, pH 8.8) using a PT 1200 Polytron Tissue Homogenizer (Glen Mills, Inc., Clifton, NJ), at speed setting 3 for 15 s, then sonicated with a Sonic Dismembrator (Fisher Scientific, Pittsburgh, PA) with three 1-s bursts on ice. Clarification of the samples was accomplished by ultracentrifugation for 30 min at 100 000× g at 4 °C using a SW40.1 rotor (Beckman Coulter, Fullerton, CA). The resultant supernates were frozen at -80 °C in 1 mL aliquots. Protein concentrations were determined for 10 µL aliquots from each sample using a modified Bradford assay.15 Preparation of Mammary Gland Homogenates for 2DElectrophoresis. Mammary gland homogenates from day 21 samples (n ) 5) and day 50 samples (n ) 5) were thawed from -80 °C, and volumes containing a total of 25 µg protein were processed through established methanol/chlorofom extraction prior to labeling with Cy3 or Cy5 (Amersham CyDye DIGE Fluor-minimal dyes, GE Healthcare, Piscataway, NJ). Briefly, all samples were adjusted with IEF buffer to the same volume, 75 µL, then mixed sequentially with 4× volumes of methanol, 3× volumes of water, and 1× volume of chloroform. Samples were centrifuged at 12 000× g for 5 min at 4 °C to separate the phases. After aspirating and discarding the upper phase, an additional 225 µL of methanol was added, and the samples were vortexed and centrifuged under the same conditions. The supernate was discarded, and the pelleted protein was allowed to air-dry for 10 min prior to labeling with the CyDyes. Equal amounts of protein (12.5 µg) of each of the samples were mixed in a separate tube for labeling with Cy2 (to generate a pooled standard).
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CyDye Labeling. Each methanol/chloroform-extracted pellet was resuspended in 20 µL IEF buffer and incubated in the dark on ice with 200 pmoles Cy3 or Cy5 according to manufacturer’s directions as follows: the stock CyDye (1 mM, made in dimethylformamide [DMF] and kept at -20 °C) was diluted 1/10 just prior to use with DMF. For labeling with Cy3 or Cy5, 2 µL of dye was mixed gently into each resuspended protein sample, and the mixture allowed to sit on ice for 30 min. The pooled mixture of all samples was mixed with 5 µL of Cy2. The reactions were quenched by addition of 2 µL (to Cy3 or Cy5 reactions) or 5 µL (to Cy2 reactions) of 10 mM lysine for 10 min on ice. 2D Difference Gel Electrophoresis (DIGE). For each 2D DIGE gel, a pair of Cy3 and Cy5-labeled samples (50 µg each) and a 10 µL aliquot of the pooled standard (50 µg) were combined, brought up to 110 µL with IEF buffer, then diluted 1:1 with rehydration buffer (7 M urea/2 M thiourea/4% CHAPS/ 40 mM Tris-HCl, pH 8.8) containing 1% IPGphor ampholytes (pI range 4-7) (GE Healthcare) and freshly added DTT (30 mM). Every strip contained a day 21 and a day 50 pair of samples. Eleven centimeter immobilized pH gradient (IPG) DryStrips (GE Healthcare) (pH gradient 4-7) were thawed from -20 °C, laid gel side down on top of each 220 µL sample, and rehydrated overnight for 16 h at room temperature under mineral oil in individual troughs in the IPG strip rehydrating chamber (GE Healthcare). The next day, the IPG strips were laid gel-side up under mineral oil on the Ettan IPGphor II (GE Healthcare) and focused at 20 °C using the manufacturer’s recommended protocol for 11 cm strips: 1 h at 500 V, 1 h at 1000 V, 2 h at 6000 V, for a total of 80 000 Vh. After IEF, the IPG strips were lightly blotted of excess oil by touching the ends onto Whatman filter paper, then each were equilibrated for SDS-PAGE in 5 mL SDS-sample buffer (6 M urea, 75 mM Tris-HCl, pH 8.8, 20% glycerol, 2% SDS) containing freshly added DTT (65 mM) twice for 15 min with gentle agitation, and then once for 15 min in 5 mL SDS-sample buffer containing freshly added iodoacetamide (135 mM) and a trace of bromophenol blue. Strips were lightly drained onto Whatman filter paper; then each was placed on top of a Criterion (Bio-Rad Laboratories, Hercules, CA) precast gel (12.5% acrylamide, 1 mm thick) so that the acidic end of the pI gradient was closest to the well where 6 µL of molecular weight markers (Precision Plus Unstained Standards, BioRad Laboratories) were loaded. SDS-PAGE was carried out in a Dodeca Cell (Bio-Rad Laboratories), at 100 V for 4 h at room temperature, until the bromophenol blue had reached the bottom of the gel. Chilled water maintained at 4 °C was circulated in coils in the bottom of the gel tank, beginning at the start of the run. Gel Image Acquisition. Once the second dimension SDSPAGE was completed, images of the gels were acquired immediately on a Typhoon Trio+ Variable Mode Imaging System (GE Healthcare), using the specific laser band-pass filters for each dye’s excitation and emission wavelengths. The excitation/emission wavelength combinations were (480 ( 35 nm)/(530 ( 30 nm) for Cy2, (540 ( 25 nm)/(590 ( 35 nm) for Cy3, and (620 ( 30 nm)/(680 ( 30 nm) for Cy5. Gels were scanned individually and Photo Multiplier Tube (PMT) voltages were adjusted for maximum image quality with minimal signal saturation and clipping. Images were checked for saturation during the acquisition process using ImageQuant TL software (GE Healthcare). Images were exported as 16-bit GEL files, cropped using ImageQuant TL software and exported into DeCyder (GE Healthcare) image analysis software. Journal of Proteome Research • Vol. 7, No. 11, 2008 4639
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Figure 1. Representative DIGE images of rat mammary gland proteome. Ten homogenates of rat mammary glands, five of day 21 and five of day 50, were each labeled with Cy3 or Cy5 as described in Methods. A mixture of equal amounts of all ten was labeled with Cy2. 2D electrophoresis was accomplished as described in Methods. Like samples (i.e., day 21) were labeled with Cy3 on some gels and with Cy5 on others, to minimize differences in dye-affinity. Gels A and B are two of the five gels in this data set. In Gel A, a day 21 sample was labeled with Cy3, and the day 50 sample labeled with Cy5. In Gel B, a different day 21 sample was labeled with Cy5, and a day 50 sample (different from gel A) was labeled with Cy3. The white rectangles indicate a pattern of red and green spots that was largely reversed between gels A and B, indicating that there was no major difference in dye-specificity within biological replicates of a sample. pH 4 and pH 7 indicate the pH range of the first dimension IEF, and 250 and 10 indicate the mass range (in kDa) of the second dimension SDS-PAGE.
Image and Statistical Analysis. GEL files were analyzed using the Batch Processor, Difference In-gel Analysis (DIA) and Biological Variation Analysis (BVA) modules within DeCyder (GE Healthcare). Batch Processing was accomplished setting 1500 spots as the upper limit. DIA was performed within individual gels comparing the Cy3 or Cy5 gel spot pattern to that for a Cy2 gel spot pattern. Ratios of Cy3/Cy5 spot volumes on each gel in the 5 gel data set were normalized in the BVA module against a common Cy2 spot pattern. Results were obtained as abundance ratios for each protein spot (day 50/ day 21). The statistical significance of each ratio was calculated using Student’s t-test on the logs of the ratios. False Discovery Rate (FDR) was calculated using the Benjamini and Hochberg method.16 Spot volume ratios that showed a statistically significant (p < 0.05) difference were processed for further analysis. Once significantly different spots were determined, 2D gels of the same parameters as the originals were loaded with unlabeled 500 µg protein (50 µg from each of the 10 samples) and run under identical conditions as the DIGE gels, except that they were visualized with Sypro Ruby fluorescent stain after the SDS-PAGE dimension. Of the 251 spots previously determined to be the most significantly different (p > 0.05, FDR > 10%) using the CyDye method, 141 were detected on the Sypro Ruby stained gels (Figure 2). These were excised and processed through peptide mass fingerprint (PMF) analysis using MALDI-TOF MS. Protein Identification by PMF Analysis using MALDI-TOF MS. Protein spots of interest were excised from the preparative gels using the ProPic robotic spot picker (Genomic Solutions, Ann Arbor, MI) following revisualization of the gel. Gel plugs were rinsed three times with 1 mL 50% aqueous acetonitrile in 10 mM ammonium bicarbonate, pH 8, to remove Sypro Ruby stain. After evaporation of the solvent by SpeedVac, each of the gel plugs were rehydrated in 25 µL of 10 mM ammonium bicarbonate, pH 8. Ten microliters of trypsin (12.5 µg/mL) (Trypsin Gold, Mass Spectrometry grade, Promega Corp., Madison, WI) was added to each gel plug solution, and the mixture agitated at 37 °C overnight (16 h). The supernate was aspirated; the gel plugs were rinsed with two additional 25 µL washes of 10 mM ammonium bicarbonate. These rinses were 4640
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combined, evaporated to dryness by SpeedVac, then reconsitituted in 10 µL 0.1% formic acid. These were desalted using C18 zip-tips (Millipore, Billerica, MA). The tryptic peptides were analyzed on a DE-Pro MALDI-TOF mass spectrometer (Applied Biosystems, Inc., Foster City, CA) as follows: 1 µL of the peptide mixture was mixed with 3 µL of a saturated solution of R-cyano4-hydroxycinnamic acid in 0.1% TFA/acetonitrile 1:1. One µL of this mixture was spotted on the MALDI target plate and allowed to dry. A total of 200 shots from the nitrogen laser operating at 337 nm were accumulated for each spot. The spectra were internally calibrated using trypsin autolysis peaks followed by baseline-correction, noise-filtration and deisotoping. The list of peptide masses was exported, and searched for matches within the nonredundant NCBI database (9/27/ 07) using the MASCOT search engine at http://www.matrixscience.com. Mass accuracy was set at 50 ppm, missed trypsin cuts at 1, and fixed modifications for alkylation of Cys residues and variable modifications at methionine residues. Determination of Observed Molecular Masses and pIs. The observed Mr and pI for each protein spot was determined by calibrating the master gel image (DIGE gel 1) within DeCyder image analysis software. Briefly, Mrs were determined by selecting ten spots on the master 2D gel image that comigrated with 1 of the 10 protein standards (Bio-Rad Laboratories) that were loaded on the Sypro Ruby-stained gels. A Mr was assigned to each of these gel spots corresponding to the Mr of the standard with which it comigrated. This established a calibration that DeCyder then used to assign observed Mrs for unknown protein spots. The linearity of the pH range in the IPG strips was confirmed to be linear by isoelectric focusing of proteins of known pIs (GE Healthcare) on the same pH range IPG strips on which the samples were focused (GE Healthcare and Sigma Corporation, St. Louis, MO) (data not shown). Initially, the predicted Mrs and pIs were obtained through the database search at MASCOT (Table 2). This information was for the amino acid sequence obtained from translating the nucleotide sequence from the open reading frame of the gene. However, for certain proteins, the N-terminal amino acid or a leader sequence is removed in the mature form of the protein. For these proteins, their corresponding protein record was
2D-DIGE of Prepubertal and Pubertal Rat Mammary Gland Proteomes
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Figure 2. Three-dimensional correlates of protein spots that were among the most significantly different between day 21 and day 50 rat mammary tissue. The three-dimensional images shown were exported directly out of DeCyder image analysis software. In each pair of peaks from the same spot, the left circled peak corresponds to day 21 mammary gland, and the right circled peak corresponds to day 50 mammary gland. The fold differences for the spots shown all had p < 0.005 and FDR less than 0.06 (see Table 2). Table 1. Randomization and CyDye-Labeling of Two Groups of Five Rat Mammary Gland Samples for 2D Gel Analysis gel #
1
2
3
4
5
Cy 2 internal internal internal internal internal standard standard standard standard standard Cy 3 day 21 day 50 day 21 day 50 day 21 Cy 5 day 50 day 21 day 50 day 21 day 50 Each of five 2D gels was loaded with 25 µg of a day 21 sample pre-labeled with either Cy3 (gels 1, 3, 5) or Cy5 (gels 2, 4), 25 µg of a day 50 sample prelabeled with either Cy3 (gels 2, 4) or Cy5 (gels 1, 3, 5), and 25 µg of the Internal Standard (mixture of all samples), pre-labeled with Cy2 (all gels). The isoelectric focusing was carried out for all five IPG strips at the same time, and the second dimension SDS-PAGE gels were run in the same tank. The labeling, rehydration and 2D electrophoretic steps were carried out as described in Methods.
located at http://www.expasy.org, (Table 3), and their predicted Mrs and pIs were recalculated (Table 2) using the tools available at this site. Annotation and Gene Class Testing. The “gi” accession numbers obtained from MASCOT were linked via Entrez17 to the corresponding Entrez Gene, which were then used to connect the Gene Ontology18 and KEGG19 information for these genes to the polypeptides. The identified polypeptides/genes were analyzed with Onto-Express20 using a hypergeometric statistical test to identify the GO and KEGG classes that indicated the significantly changed peptides compared to the
proteome. A class was considered significant if its p values were 0.3-1.5 pH units) than the predicted pI, indicating that the majority probably had undergone an acidic post-translational modification such as phosphorylation of Ser, Thr, and Tyr residues or sulfonation of Tyr residues. The largest acidic displacement was for the isoforms of hemopexin; this protein has five putative N-glycosylation sites. Glycosylation is known to cause considerable reductions in isoelectric point of both hemopexin30 and other proteins.31 Proteomic Approaches to Study of Mammary Gland Proteins. To our knowledge, a proteomic analysis of the mammary gland in the rat as it undergoes pubertal development has not Journal of Proteome Research • Vol. 7, No. 11, 2008 4647
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Figure 7. Distribution of proteins significantly different in abundance in the mammary gland at day 50 versus day 21 according to function. Several functionally related proteins were grouped for this figure; structural proteins included cytoskeletal and extracellular matrix proteins; chaperones and protein-folding formed another group; those associated with glucose-sensing and regulation, glucose transport and glycogen metabolism were grouped; the final group included those falling under various aspects of metabolism. The numbers are the numbers of proteins in each category, not a proportion of the total.
been described. Previous proteomic studies on the rat mammary gland focused on the effect of prepubertal treatment of injected genistein32 and in utero treatment with 2,3,7,8tetrachlorodibenzo-p-dioxin,33 the proteome of mammary gland tumors in rats34 and in transgenic mice,35 and cultured rat mammary epithelial cells.36,37 Similar studies have been reported for human mammary epithelial cells.38–40 In the present study, the proteome of the rat mammary gland was examined prior to the onset of puberty (21 days of age) and at the peak of sensitivity to applied carcinogens (50 days of age). The proteins with significantly different abundance were classified into those from the blood proteome (albumin, R1-antitrypsin) and those that were derived from the mammary gland tissue. To ensure as rapid processing as possible for proteomic as well as microarray studies, animals were not perfused prior to biochemical analysis; thus, blood proteins were expected to be present among those proteins resolved on the 2D gels. Future proteomic studies of the mammary gland cells should involve perfusion of the sedated animal to eliminate blood proteins. However, it is worth noting that certain of the albumin and hemopexin isoforms were highly significantly different between day 21 and day 50 gland samples (see Table 2), suggesting that while not components of mammary glandular epithelial cells per se, differences in blood protein components such as specific albumin or hemopexin isoforms could be markers of differences between day 21 and day 50 developmental time points. The proteins in the mammary gland exhibiting significant change in abundance between days 21 and 50 can be divided into several classes (Figure 7). The predominant protein differences between day 21 and day 50 mammary glands included structural and extracellular matrix proteins (β and γ Actin, β-tubulin isoforms and vimentin), chaperone proteins (Hsp 90 and Hsp 4), those involved in glucose-sensing, transport and storage, and proteins that are part of metabolic pathways (enolase-1, mitochondrial aldehyde 4648
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Kim et al. dehydrogenase, cytoplasmic malate dehydrogenase and guanine deaminase) (Figure 7). While β tubulin isoforms 2 and 5 and vimentin were lower, two Actin isoforms, coronin and dynein-like proteins, were higher at day 50. Extracellular matrix protein annexin A4 was lower in abundance, whereas procollagen type XIV R1 and collagen R1 type VI were higher. The heat shock proteins (Hsp 90 1 beta and Hsp 4) were higher in abundance. Many of the metabolic enzymes were lower in abundance (aldehyde dehydrogenase, malate dehydrogenase, lactate dehydrogenase and guanine deaminase). A recent study of protein markers of mouse mammary gland involution after lactation employed a similar 2D gel approach, but using singlestained gels;25 protein differences in this physiologically important process involved several functional categories as those detected here, namely metabolic enzymes, cytoskeletal proteins, chaperones, signaling proteins, as well as albumin. This documentation of differences in known proteins at distinct developmental time points lays the groundwork for further studies to examine the physiological significance of such changes in the mammary gland, during development, and whether any of these has a role in determining vulnerability to carcinogens/environmental stimuli that cause breast cancer. Although this is an initial report of protein differences that distinguish normal rat mammary gland at different physiological ages, some protein differences are worth noting; coronin, an Actin binding protein, and Actin itself were in general increased at day 50 relative to day 21 in normal rat mammary gland. The fact that lower levels of profilin, an Actin-assembly promoter, were found in more aggressive mouse mammary tumors by tissue MALDI-TOF MS suggested that stabilization of Actin might be a point of vulnerability for carcinogens in mammary glands at day 50 where increased levels of Actin are normally found.35 Similarly, the reduced amount of peroxiredoxin 4 in day 50 versus day 21 mammary gland might reflect reduced ability of the tissue to deal with oxidative stress, such as might be induced by carcinogens; this is consistent with the finding of increased levels of thioredoxin by tissue MALDI-TOF MS in mouse mammary tumors.35 It is appreciated that the 511 proteins detected so far in this study represent a small proportion of the total mammary gland proteome. The 2D-gel approach selects for proteins that are generally water-soluble, whereas membrane proteins are poorly represented. In addition, without depletion of major proteins such as albumin, many of the mid to lower abundance proteins in any proteome are not present in sufficient quantity on 2D gels for quantitative analysis, because only so much protein can be resolved on a given 2D gel. For this first analysis, however, we felt that depletion of any components from multiple samples would introduce variables that would counter any potential gain. Now that the image and statistical analysis has identified spots with known 2D gel positions that were statistically significantly different between day 50 and day 21 that were not analyzed in this report, 2D gels of samples that have been depleted of albumin can now be re-run, at higher protein loadings, to study proteins of lower abundance, including those that were significantly different, but not analyzed in this report. It is important to use complementary approaches to fully describe the proteome of an organ such as the mammary gland. Future reports will thus describe results of studies initiated using MALDI-TOF/TOF MS analysis of the protein spots isolated from the 2D-gels to confirm the identities of the proteins derived from the PMF analysis as well as to provide
2D-DIGE of Prepubertal and Pubertal Rat Mammary Gland Proteomes clues to the identities of the peptides that were present in the MALDI-TOF mass spectra but did not match to known proteins. In addition, nanoLC multiple reaction ion monitoring mass spectrometry will be explored to provide accurate quantitative analysis of specific proteins.41
Conclusions This is the first proteomic analysis of the normal rat mammary gland, and of the gland at developmental ages important with regard to mammary tumor chemoprevention. Rats can be significantly protected against mammary tumors induced by carcinogens if given chemopreventive agents during the prepubertal period (up to day 21), but not if given at the time of administration of carcinogen (day 50).44 Thus, defining the proteomic differences of the mammary gland between these two time points begins to define a database that will contribute to understanding the susceptibility of the rat at day 50 to carcinogens and the timing of efficacy of chemopreventive agents in rat models of breast cancer. The statistical analyses implemented in this DIGE study enabled identifying the most significantly different spots, with low FDRs. The fact that both spot populations, those that were significantly different and those that were not, between the two ages had similar distributions of CV meant that the differences in abundance for the spots between the two ages were due to actual differences in the mean spot volumes, not to differences in their variances. It will be important to validate with orthogonal methods the proteins identified in this study as well as to extend the database of differences between days 21 and 50 in the rat mammary gland. Ultimately, proteomic studies such as this will complement other types of approaches to understand agerelated susceptibility of rat mammary gland to carcinogens, and the mechanisms by which chemopreventive agents have efficacy in rat models of breast cancer.42–44
Acknowledgment. This study was supported by a U54 grant (CA100949) to the UAB Center for Nutrient-Gene Interaction (SB, PI). The instrumentation for running, imaging and processing 2D-gels was provided by a NCRR Shared Instrumentation grant (S10 RR16849, HK, PI). The mass spectrometers were purchased from funds provided by NCRR grants (S10 RR11329, RR13795, RR19231, SB, PI). Operation of the Comprehensive Cancer Center Proteomics-Mass Spectrometry Shared Facility was partially supported by funds from a P30 Core support grant (CA13148-35, E. Partridge, PI) to the UAB Comprehensive Cancer Center. We would like to acknowledge Drs. Coral Lamartiniere and Tim Whitsett and their colleagues for providing animal tissues, and for general assistance with animal-related issues in this study. Supporting Information Available: MALDI-TOF MS peptide mass fingerprints for all proteins identified in this study. This material is available free of charge via the Internet at http://pubs.acs.org. References (1) Cancer Facts and Figures - 2007 (http://www.cancer.org/downloads/ STT/CAFF2007PWSecured.pdf). (2) Shibuya, K.; Mathers, C. D.; Boschi-Pinto, C.; Lopez, A. D.; Murray, C. J. BMC Cancer 2000, 26, 2–37. (3) Nagata, C.; Kawakami, N.; Shimizu, H. Breast Cancer Res. Treat. 1997, 44, 75–82.
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