automation of chromatin immunoprecipitation

A central element of genome function is the expression of the individual genome elements and the factors that regulate those events. Transcription factors, histone proteins, and covalent modifications of various proteins that interact with DNA are critical players within the regulation of gene expression events. Due to their far-reaching functional implications, there are currently many efforts to study these protein-DNA interactions and their associated covalent modifications in a detailed and comprehensive manner 1,2. To study these events many investigators perform chromatin immunoprecipitation (ChIP) analyses directed to specific genomic loci, whereby locus-specific primer sets are used for detection of the sequence of interest by PCR3,4, which has recently been adapted to provide quantitative results by real-time PCR5,6. In addition, DNA microarray technology is applied for genome-wide identification of those genomic loci that interact with specific interaction partners7or interaction partners that possess specific covalent modifications 8. It is clear from the current breadth and scope of efforts such as these that functional events governing gene regulation will continue to be the subject of intense study for many years to come.

An essential component to successful ChIP analyses is the ability to conduct high-performance immunoaffinity separations of crosslinked protein-DNA complexes, and key to that success is the quality of antibodies applied. For example, the antibodies must possess high affinity to achieve maximum sensitivity for the targeted protein-DNA complex and thus minimize false negatives, but must also possess very high specificity so as to minimize false positives due to background “noise” contributed by non-specific binding events. The optimization process for ChIP antibodies must insure that rigorous wash procedures are applied so that non-specific binding does not occur with the antibody or the antibody-support resin, yet at the same time this washing must generate minimal losses of the target complex. With proper optimization, it has been shown in genome-wide ChIP studies that false positive error rates can range from 4%7 to 27%9, with more typically quoted false positive rates ranging between 6-10%10,11. False negative error rates – though obviously not directly measurable – are often quoted on the basis of retrospective statistical analyses as being ~33%10. In addition, bioinformatics-based approaches have been described for reducing the false positive error rate by identifying those regulatory sequence motifs most likely to be valid12. These models have also been “boosted” with training data of validated positive and negative sequences13. While this boosting was shown to provide 40% improvement over the non-boosted models, there were still invariably unaccounted-for false positives.

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Introduction

Technical Note

Performance Enhancement and Automation of Chromatin Immunoprecipitation (ChIP) Procedures with PhyTip® Column Technology


While thorough ChIP antibody optimization combined with rigorous bioinformatics can lead to reductions in false positives, there will always be questions as to which positive interactions are true and which are false, thus requiring validation and confirmation of reported protein-DNA interactions. This situation is eloquently summarized by authors9 that have performed extensive work in the area of ChIP analyses:

“…However, despite ever increasingly sophisticated statistical analysis of the genome-wide ChIP-chip data currently being performed in yeast10, independent and stringent empirical examination of…error rates will continue to be required to validate the global conclusions presented of genome-wide DNA-binding factor targets due to experimental error. These issues will become more pronounced as genome-wide analysis moves increasingly toward human studies where there are three orders of magnitude more DNA than in yeast.”

In view of the current state of ChIP analyses, one area that has not been rigorously optimized is the ChIP separation format. An optimized separation format for ChIP analyses would insure that:

• The antibody-protein-DNA complex is extracted to the Protein A or Protein G resin with maximum efficiency so that the highest possible target signal can be obtained. This insures the lowest possible rate of false negatives.

• The trapped complex is washed in a manner that allows for efficient and complete removal of any non-specific binders. This should be achieved without excessive washing, transfer steps or the need for repeated ChIP rounds. This insures the lowest possible rate of false positives.

• The trapped complex is eluted from the resin with extremely high yields and is eluted into a small volume that maximizes final target complex concentration. This insures maximum analytical rigor and sensitivity in determining enrichment factors.

• Once the complex is eluted from the resin and is released from its crosslinking, the sample is in a form that lends itself to simple and quantitative DNA cleanup procedures. This further insures the lowest possible rate of false negatives.

All of the above steps are easily automated and each sample is subjected to a fresh separation column. This insures maximum precision and zero carryover from sample-to-sample.

PhyNexus’ PhyTip column technology provides an optimized ChIP separation format that meets the specifications described above. As shown in the photo below at left, the PhyNexus PhyTip 1000+ (top) and 200+ (bottom) column products each possess a microcolumn of agarose-based resin at the opening of a pipet tip. As shown in the drawing below at right, the design of the PhyTip column is such that highly efficient capture of the target protein is achieved by maximizing transport to the agarose beads, which is enhanced through repeated back-and-forth sample exposure cycles. This design also insures exceptional purity for the target protein by reducing the amount of unwashed volume to virtually zero, thus minimizing any opportunities for non-specific binding events. Lastly, this same design provides for high-yield elutions to occur into exceptionally small volumes. All of these features work together to provide dramatically increased target protein concentrations at high levels of purity, all from starting samples as small as a few hundred microliters.

PhyTip Column Technology

PhyTip column technology is a simple and straightforward means of performing fully optimized ChIP separations prior to conventional ChIP, ChIP-chip or validation of individual ChIP-chip interactions – all of which can also be easily automated for high-throughput procedures. The benefits described above as being provided by the PhyTip column technology are illustrated below for different colon cancer cell lines and different histone modifications associated with the hMLH1 gene.

Materials and Methods

Antibodies and cell lines

Histone H3 antibodies, SDS Lysis Buffer, ChIP Dilution Buffer, and salmon-sperm DNA/Protein A and Protein G agarose were obtained from Upstate Biotechnology (Lake Placid, NY). RKO and SW480 cell lines were obtained from the American Type Culture Collection. Dulbecco’s modified growth medium, L-15 medium and fetal bovine serum were obtained from Invitrogen (Carlsbad, CA). Protein G PhyTip® Columns were from PhyNexus, Inc. (San Jose, CA).

Cell growth, crosslinking and chromatin preparation

RKO and SW480 colorectal cancer cell lines were obtained from American Type Culture Collection. RKO cells were grown in high-glucose Dulbecco’s modified Eagle’s medium supplemented with 10% fetal bovine serum and 1% penicillin/streptomycin. SW480 cells were grown in L-15 medium supplemented with 10% fetal bovine serum and 1% penicillin/streptomycin in a humidified atmosphere containing 5% CO2 at 37°C.

EZChIP Assay Kit from Upstate Biotechnology was used for chromatin preparation with some modifications. 1x106 cells were harvested from each cell line. Proteins were cross-linked to DNA by addition of formaldehyde directly to the culture medium to a final concentration of 1% for 10 min at room temperature. The cross-linking reaction was quenched by adding 0.125 M glycine for 5 min at room temperature. The medium was then removed and cells were washed with 1X PBS containing a combination of protease inhibitors. The PBS was removed and 0.2X trypsin was added to the cells. After a 5-min incubation at 37°C, ice-cold 1X PBS containing 10% FBS was added to stop trypsinization. The cells were pelleted, and washed twice with 1X PBS plus protease inhibitors as above and resuspended in 200 µl 1% SDS, 10mM EDTA, 50mM Tris, pH 8.1. The lysate from each cell line was diluted to a final volume of 2 mL in 0.01% SDS, 1.1% TritonX-100, 1.2mM EDTA, 16.7mM Tris-HCl, pH 8.1, 167mM NaCl.

DNA was sheared by sonication on ice using a Sonifier 250 ultrasonic cell disruptor (Branson Ultrasonics), 40% duty cycle for 2 minutes at low power. Insoluble material was removed by centrifugation at 12,000 x g for 10 minutes at 4°. 20 µl of each sample was retained as DNA input control for PCR analysis. The sonicated samples were pre-cleared with 80 µl of salmon sperm DNA/Protein A and Protein G agarose beads (3:1 ratio of Protein A to Protein G) for 1 h at 4°C with agitation followed by centrifugation at 4000 x g for 1 minute to pellet agarose beads.

The resulting supernatant from each cell line was divided equally into five 400 µl fractions. 2.5 µl of each antibody was added to separate fractions and incubated overnight at 4ºC. Control samples containing no antibody were also prepared for the two cell lines. Following the overnight incubation, each sample was divided into two 200 µl fractions for analysis using conventional immunoprecipitation and PhyTip column enrichment.

Standard Chromatin Immunoprecipitation

Ten microliters of the 3:1 Protein A and Protein G agarose were added to each sample for one hour at 4ºC with agitation followed by centrifugation at 4000 x g for 1 minute to pellet agarose beads. The beads were washed by resuspending in 1ml ice-cold Low-Salt Wash Buffer (0.1% SDS, 1% Triton X-100, 2mM EDTA, 20mM Tris-HCl, pH 8.1, 150mM NaCl) followed by centrifugation at 4000 x g for 1 minute. The wash was repeated once with High Salt Wash Buffer (0.1% SDS, 1% Triton X-100, 2mM EDTA, 20mM Tris-HCl, pH 8.1, 500mM NaCl), once with LiCl Wash Buffer (0.25M LiCl, 1% IGEPAL-CA630, 1% deoxycholic acid (sodium salt), 1mM EDTA, 10mM Tris, pH 8.1) and two washes with TE Wash Buffer (10mM Tris-HCl, 1mM EDTA, pH 8.0). Following the final wash step, the immune complex was extracted from the beads by adding 120 µl Elution Buffer (1% SDS. 0.1M NaHCO3) at room temperature for 15 minutes.


Chromatin Immunoprecipitation with PhyTip Columns

Protein G PhyTip columns (5 µl bed volume) were blocked with 30 µg/mL salmon sperm DNA in PBS using a single intake/expel cycle of 190 µl at a flow rate of 50 µl/min. The samples, wash, and elution buffers were placed in individual wells of a microtiter plate (200 µl per well). Liquid handling steps were performed using the PhyNexus ME-200 computer-controlled multichannel flow controller. All of the actions associated with the ChIP protocol can be completely automated through an MEA Personal Purification System, as shown in Figure 1.

Figure 1. PhyNexus MEA Personal Purification System

Capture of the immune complex was achieved by passing the samples back and forth through the column using an intake/expel volume of 190 µl for nine cycles at a flow rate of 150 µl/min. The columns were washed with the same series of buffers (Low Salt Wash, High Salt Wash, LiCl Wash, TE Wash) as described in the preceding section by passing 190 µl of each wash solution through the columns for three cycles at a flow rate of 200 µl/min. The elution step was performed by passing 120 µl of elution buffer back and forth through the column for five cycles at a flow rate of 50 µl/min. This process is illustrated in Figure 2.

Figure 2. PhyTip ChIP extraction process


PCR Amplification

After elution from the beads and columns, each sample was heated at 65ºC for four hours to reverse the DNA-chromatin crosslinking, followed by Proteinase K digestion, phenol:chloroform extraction and ethanol precipitation to recover the DNA. Alternatively the DNA can undergo high-yield quantitative purifications in an entirely automated and high-throughput manner by applying reverse-phase PhyTip columns. A 266 bp sequence of the 5’ upstream region of the hMLH1 gene (AB017806) was amplified via PCR. The sequence of the primers used were: Forward: 5’ GGCTCCACCAC TAAATAACGCTG, Reverse: 5’ GCCTCTGCTGAGGTGATCTGG. Amplification was performed using Taq DNA Polymerase (Roche) using the following program: 95ºC for 5 min (95ºC for 45 s, 60ºC for 45 s, 72ºC for 45 s for 35 cycles), 72ºC for 10 min, heated lid 105ºC. PCR products were visualized using agarose gel electrophoresis and EtBr staining of amplicons.

Results

Acetylation and methylation patterns of histone H3 surrounding the promoter region of the mismatch repair gene hMLH1 in colorectal cancer cell lines RKO (hMLH1 promoter silenced) and SW480 (hMLH1 promoter active) have been described previously3, and were used for the purpose of comparing results obtained by standard ChIP procedures to those obtained by PhyTip ChIP procedures.

Acetylation of Histone H3

The first histone modification studied was acetylation of Histone H3, with the gel image shown below in Figure 3. The symbols above the individual lanes signify the absence (-) or presence (+) of antibody. Therefore, all lanes without antibody should show no PCR product – any PCR product that does show in these lanes would be the result of inadequate washing of non-specific DNA binding to the resin itself or any other potentially contaminating surfaces. In addition, for those cases where antibody is present for this particular histone modification, there should be a clear PCR product present in the case of SW480 cells and no PCR product in the case of RKO cells. Any PCR product that does show in the RKO cell line-plus-antibody lane would be a false positive.

The PhyTip ChIP column procedure generates a strong PCR product for the SW480 cell line, with no discernible PCR product in any of the other lanes – indicating that the wash procedure was sufficient for both cell lines, and that there was not a false positive for the RKO cell line. The standard ChIP procedure generates a clearly discernible signal for the SW480 cell line, with no discernible signal in the “no antibody” lane for this same cell line. However, there are faint PCR products in both lanes of the RKO cell line, indicating that the wash procedure for this cell line was not sufficient and runs the risk of contributing to false positive signals, as shown in the “with antibody” lane for the RKO cell line.

Figure 3. Anti-acetyl-Histone H3 ChIP results, standard vs PhyTip processing


Dimethylation of Histone H3-K9

The second histone modification studied was dimethylation of Histone H3-K9 with the gel image shown below in Figure 4. Just as with the previous histone modification, all lanes without antibody should show no PCR product. Any PCR product that does show in these lanes would be the result of inadequate washing of non-specific DNA binding to the resin itself or any other potentially contaminating surfaces. In addition, for those cases where antibody is present for this particular histone modification, there should be a clear PCR product present in the case of RKO cell lines and no PCR product in the case of SW480 cell lines. Any PCR product that does show in the SW480 cell line-plus-antibody lane would be a false positive.

The PhyTip ChIP column procedure generates a clearly discernible PCR product for the RKO cell line, with no discernible PCR product in any of the other lanes, indicating that the wash procedure was sufficient for both cell lines, and that there was not a false positive for the SW480 cell line. The standard ChIP procedure generates a very faint PCR product for the RKO cell line (and is close to being undetectable, and hence a false negative), with no discernible signal in the “no antibody” lane for this same cell line. However, there is also a faint PCR product in the “no antibody” lane for the SW480 cell line (and contrary to what is already known about this histone modification, is actually more discernable than the “with antibody” lane for the RKO cell line). This indicates that the wash procedure for this cell line was not sufficient and runs the risk of contributing to false positives.

Figure 4. Anti-H3-K9-Me2 ChIP results, standard vs PhyTip processing

Discussion

As demonstrated for a known gene (hMLH1) oppositely regulated by two different H3 modifications in two different cell lines, PhyTip column technology can provide significant improvements in signal-to-noise for ChIP analyses. This translates to improvements in false positive error rates by providing more specific signals, as well as improvements in false negative error rates by providing stronger signals.

These improvements in performance have implications in a variety of ChIP-related contexts. For one, conventional ChIP analyses whereby a set or sets of loci-specific primers will benefit from having an overall higher degree of reliability and automation. This would be specifically beneficial if a large number of experiments are performed for a particular event, or for validation of individual genome-wide interactions reported – as suggested by previous authors. In addition, the improvements can potentially lead to overall improvements in false negatives and false positives in ChIP-chip experiments.

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Another advantage of the PhyTip column approach to ChIP analyses is that the improvements described above are obtained with significantly reduced starting sample quantities. In many standard ChIP procedures, the starting number of cells is typically 1x106, which are then lysed and commonly brought to a volume of 2 mL for standard ChIP processing. In the case of PhyTip processing for ChIP analyses, 0.2 mL of lysate volume representing the equivalent of 1x105 cells provided the improvements reported over processing this same volume by standard ChIP procedures. The improved results for smaller amounts of starting material mean that PhyTip ChIP approaches are well-suited to those situations where the starting cells are very precious and limited in quantity, such as primary tumor cell lines. In addition, this advantage also means that larger numbers of different experiments can be performed upon the same sample, e.g. examining a range of different histone modifications within a given sample.

In addition to these substantial benefits for ChIP analyses, the PhyTip column approach to ChIP analyses lends itself to very simple automation of the separation process. This creates not only greater precision in ChIP analyses, but also dramatically reduces hands-on time. In addition, the PhyNexus MEA Personal Purification System has accessory items such as on-board heating that can automate the process of reversing protein-DNA crosslinking with 65°C incubations, and the ability to also perform standard pipetting operations on the MEA allows for addition of Proteinase K to these de-crosslinked samples. Furthermore, reverse-phase DNA purification can be performed in a high-yield and automated manner on the MEA Personal Purification System, thus eliminating the need for phenol-chloroform extractions requiring labor-intensive manipulation of the samples resulting in losses of DNA.

Acknowledgments

Drs. Jeffrey Sklar and Hui Li of Yale Medical School are gratefully acknowledged for providing the experimental work and data for this Technical Note.

References

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5. J .C. Wang, M.K. Derynck, D.F. Nonaka, D.B. Khodabakhsh, C. Haqq and K.R. Yamamoto, “Chromatin immunopreciptation (ChIP) scanning identifies primary glucocorticoid receptor target genes”, Proc. Natl. Acad. Sci. USA, 2004, 101, 15603-15608.

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8. B.E. Bernstein, E.L. Humphrey, R.L. Erlich, R. Schneider, P. Bouman, J.S. Liu, T. Kouzarides and S.L. Schreiber, “Methylation of histone H3 Lys 4 in coding regions of active genes”, Proc. Natl. Acad. Sci USA, 2002, 99, 8695-8700.

9. M.J. Oberley, D.R. Inman and P.J. Farnham, “E2F6 negatively regulates BRCA1 in human cancer cells without methylation of histone H3 on lysine 9”, J. Biol. Chem., 2003, 278, 42466-42476.

10. T.I. Lee, et al, “Transcriptional regulatory networks in Saccharomyces cerevisiae”, Science, 2002, 298, 799-804.

11. Z. Li, S. Van Calcar, C. Qu, W.K. Cavenee, M.Q. Zhang and B. Ren, “A global transcriptional regulatory role for c-Myc in Burkitt’s lymphoma cells”, Proc. Natl. Acad. Sci. USA, 2003, 100, 8164-8169.

12. E.M. Conlon, X.S. Liu, J.D. Lieb and J.S. Liu, “Integrating regulatory motif discovery and genome-wide expression analysis”, Proc. Natl. Acad. Sci. USA, 2003, 100, 3339-3344.

13. P. Hong, X.S. Liu, Q. Zhou, X. Lu, J.S. Liu and W.H. Wong, “A boosting approach for motif modeling using ChIP-chip data”, Bioinformatics, 2005, 21, 2636-2643.

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