This work was supported by the BLUERPINT EU grant (BLUEPRINT &#8211; A BLUEPRINT of Haematopoietic Epigenomes). We also thank the Walloon Region (DG06) for its financial support.

1. Standard ChIP Experiments
<ol>
	<li>Cell collection and DNA-protein crosslinking.
	<ol>
		<li>Grow HeLa-S3 cells to a confluence of 80%-90%. Remove culture medium, wash the dish twice with 10 ml of 1x phosphate buffered saline (PBS), and add Trypsin-EDTA (1x) to the cultured plate. Incubate for a maximum of 2 min to detach the cells from the dish. Collect cells and wash twice with 10 ml PBS. 
		NOTE: Longer incubation times will lead to cell damage.</li>
		<li>Centrifuge the cells for 5 min at 500 x g and resuspend the cells in 20 ml of PBS. Proceed to count the cells.</li>
		<li>Centrifuge the cells for 5 min at 500 x g, discard the supernatant and add 500 &#956;l of PBS. The optimal number of cells for the fixation step is 10 million cells per 500 &#956;l of PBS.</li>
		<li>Add 13.5 &#956;l of fresh 37% formaldehyde into each aliquot of 500 &#956;l of cell suspension. Fixate the cells for 8 min at RT.</li>
		<li>Add 57 &#956;l of 1.25 M glycine solution to stop the fixation. Incubate for 5 min at RT with constant mixing by gentle vortex. Work on ice from this point onwards.</li>
		<li>Centrifuge the cells at 500 x g for 5 min at 4 &#176;C and discard the supernatant without disturbing the cell pellet.</li>
		<li>Wash the cells twice with 1 ml PBS. Discard gently the supernatant and keep the cell pellet on ice.</li>
	</ol>
	</li>
	<li>Cell lysis and chromatin shearing
	<ol>
		<li>Add 10 ml of ice cold lysis buffer iL1 to the cell pellet (1 ml of lysis buffer per 1 million cells is the optimal ratio). Pipette up and down several times and incubate for 10 min at 4 &#176;C with gentle mixing.</li>
		<li>Centrifuge the lysate for 5 min at 500 x g and 4 &#176;C. Discard the supernatant.</li>
		<li>Add 10 ml of ice cold lysis buffer iL2 to the lysates and mix gently by pipetting up and down. Incubate the lysates for 10 min at 4 &#176;C.</li>
		<li>Centrifuge for 5 min at 500 x g and 4 &#176;C and discard the supernatant.</li>
		<li>Prepare the complete shearing buffer adding the 200x protease inhibitor cocktail (PIC) to the iS1 shearing buffer. Keep the buffer on ice for 5 min and work on ice afterwards. Add 1 ml of the complete iS1 shearing buffer to each 10 million cells pellet and gently mix by pipetting up and down. Prior to sonication incubate the samples on ice for 10 min to reduce viscosity of the sample.</li>
		<li>Shear 300 &#181;l aliquots of chromatin by sonication using a water bath sonicator for 2 to 3 sets of 10 cycles each. A cycle consists of 30 sec &#8220;ON&#8221; and 30 sec &#8220;OFF&#8221; on a high power setting. Alternatively, use a pico-sonication device with a shorter sonication time of 5 to 10 cycles of 30 sec &#8220;ON&#8221;, 30 sec &#8220;OFF&#8221;. Briefly vortex and spin the tubes between the runs. When using other types of sonicators, follow corresponding manufacturer&#8217;s instructions for chromatin shearing.</li>
		<li>Centrifuge the sheared chromatin at 16,000 x g for 10 min and collect the supernatant to be used immediately in the IP step. Alternatively, store the chromatin at -80 &#176;C for up to 2 months for future use.</li>
		<li>Analyze the chromatin shearing efficiency prior to immunoprecipitation step using 1-1.5% TAE agarose gels or bionalyzer. Optimal chromatin fragment sizes range between 100-600 bp.</li>
	</ol>
	</li>
</ol>
2. Low Cell ChIP Experiments
<ol>
	<li>Cell collection and DNA-protein crosslinking
	<ol>
		<li>Grow HeLa-S3 cells to a confluence of 80%-90%. Remove culture medium, wash the dish twice with 10 ml of 1x phosphate buffered saline (PBS), and add 1x Trypsin-EDTA to the cultured plate. Incubate for a maximum of 2 min to detach the cells from the dish. 
		NOTE: Longer incubation times will lead to cell damage.</li>
		<li>Collect cells by adding 1 ml culture medium containing serum into a 1 ml centrifugation tube. Count the cells.</li>
		<li>Centrifuge the cells for 5 min at 500 x g. Bring the cell number to 10,000 cells per ml of culture medium for the fixation.</li>
		<li>Add 27 &#956;l of 36.5% fresh prepared formaldehyde into each tube for the fixation. Invert the tube two or three times and incubate 10 min at RT.</li>
		<li>Add 115 &#956;l of 1.25 M glycine solution to the sample, invert the tube two or three times and incubate 5 min at RT. Work on ice from this point onwards.</li>
		<li>Centrifuge the cells at 300 x g for 10 min at 4 &#176;C. Discard the supernatant slowly.</li>
		<li>Wash cells with 1 ml ice cold HBSS with PIC (200x, final concentration 1x). Invert the tube two or three times to resuspend the cells and centrifuge at 300 x g for 10 min at 4 &#176;C. Discard gently the supernatant and keep the cell pellet on ice.</li>
	</ol>
	</li>
	<li>Cell lysis and chromatin shearing
	<ol>
		<li>Add 25 &#956;l of complete Lysis Buffer tL1 (Lysis Buffer tL1 + PIC) per 10,000 cells and agitate manually the bottom of the tube to resuspend the cells. Incubate on ice for 5 min.</li>
		<li>Add 75 &#956;l of complete HBSS (HBSS + PIC) buffer into each aliquot containing 10,000 cells.</li>
		<li>Shear 100 &#956;l aliquots of 10,000 cells by sonication for 5 sets of 5 cycle each. A cycle consists of 30 sec &#8220;ON&#8221; and 30 sec &#8220;OFF&#8221; on the high power setting. Alternatively, use a pico-sonication device used with a shorter sonication time of 5 cycles of 30 sec &#8220;ON&#8221;, 30 sec &#8220;OFF&#8221;. Optimal chromatin fragment sizes range between 100-600 bp. Note that chromatin preparations, cell types and different sonicators require separate shearing optimization experiments.</li>
		<li>Centrifuge the sheared chromatin at 14,000 x g for 10 min to discard the insoluble material and collect the supernatant to be used immediately in the IP step. Alternatively, store the chromatin at -80 &#176;C for up to 2 months for future use.</li>
		<li>Analyze the chromatin shearing efficiency prior to immunoprecipitation step using 1-1.5% TAE agarose gels or the bionalyzer. Treat samples with RNase prior to agarose gel analysis in order to improve the visual assessment of shearing. Optimal chromatin fragment sizes range between 100-600 bp.</li>
	</ol>
	</li>
</ol>
3. Chromatin Immunoprecipitation and Library Prep
<ol>
	<li>For standard automated ChIP experiments
	<ol>
		<li>Add 120 &#956;l of ChIP Buffer H (ChIP Buffer H + PIC) to 100 &#956;l sheared chromatin. Use 200 &#956;l for the IP and keep 2 &#956;l to 20 &#956;l as input sample.</li>
		<li>Select the automated ChIP 200 &#956;l protocol in the automation instrument. The throughput of the protocol is 1 to 16 samples per run.</li>
		<li>Run an automated ChIP experiment using, chromatin corresponding to 1-2 million cells, 1-2 &#956;g of anti-H3K79me3, -H3K27me3, -H3K4me3, -H3K4me2, -H3K9ac, -H3K9/14ac, -H3K36me3 and H3K9me3 ChIP-seq grade rabbit polyclonal antibodies. Optimal antibody amounts vary depending on the histone modification and the affinity and specificity of the corresponding antibody.
		<ol>
			<li>Use equal amounts of non-immune rabbit IgG as an isotype control antibody. Alternatively, use uncoated beads or specific blocked antibody as ChIP controls. Add 20 &#956;l of Protein-A coated magnetic beads for each reaction.</li>
		</ol>
		</li>
		<li>Use the automated histone ChIP-seq kit reagents to perform automated ChIP experiments with anti-H3K79me3 and -H3K4me2 polyclonal antibodies. Use the ideal ChIP-seq kit reagents to perform ChIP experiments with anti-H3K27me3, -H3K4me3, -H3K9ac, -H3K9/14ac, -H3K36me3 and -H3K9me3.</li>
		<li>Select the automated ChIP protocol following the software instructions implemented in the automation device. Set the ChIP experimental parameters to 4 hr for the antibody coating step and 15 hr for the immunoprecipitation step. The reverse crosslinking step takes place in the automated instrument at 65 &#176;C for 4 hr.</li>
		<li>Purify the reverse cross-linked DNA on the automated system. Select automated protocols for DNA purification with a protocol or kit using magnetic bead based DNA purification. Elute the DNA in 25 &#956;l of water.</li>
		<li>Quantify the immunoprecipitated DNA by extracting 10% of the immunoprecipitated DNA. The immunoprecipitated DNA yield depends on the quality of the chromatin and antibody, cell type and the target histone modification. Quantify the DNA using an assay kit according to manufacturer&#8217;s instructions.</li>
		<li>Analyze the quality of the immunoprecipitated DNA by quantitative PCR using primers for at least 1 positive and 1 negative control genomic regions. Do not use more than 10% of the total immunoprecipitated DNA for assessing ChIP enrichments.
		<ol>
			<li>Prepare the qPCR reactions. Add 10 &#956;l of a 2x SyberGreen qPCR master mix, 1 &#956;l of primer mix, 1-5 &#956;l of immunoprecipitated or input DNA and sterile water up to 20 &#181;l final reaction volume. The qPCR program includes an initial denaturation step at 95 &#176;C for 5-10 min depending on the provider of the Taq polymerase and the annealing temperatures should be set according to the primers selected.</li>
		</ol>
		</li>
		<li>Use automated library prep protocols compatible with the commercially available Illumina ChIP-seq library preparation reagents to build the libraries using both ChIP DNA as well as the saved input DNA from the same chromatin preparation. Use 10-20 ng of immunoprecipitated DNA from each antibody for library preparation. Prepare up to 16 automated libraries per run.</li>
		<li>Sequence the libraries and generate clusters according to Illumina manufacturer&#8217;s instructions. Perform primary bioinformatics analysis (cluster filtering, base calling, etc.) following the standard Illumina pipeline, filter and align the reads to the latest human genome assembly (current version is GRCh38) with the ELAND aligner. Use SICER7 or MACS8 for peak calling and perform the downstream analyses of peaks with Homer9, BEDTools10 or preferred software.</li>
	</ol>
	</li>
	<li>For low cell number automated ChIP experiments
	<ol>
		<li>Add 120 &#956;l of complete ChIP buffer tC1 (ChIP Buffer tC1 + PIC) to 100 &#956;l sheared chromatin. Use 200 &#956;l for the IP and keep 20 &#956;l as input.</li>
		<li>Select automated ChIP 200 &#956;l protocol in the automation system. The throughput of the protocol is 1 to 16 samples per run.</li>
		<li>Run an automated ChIP-seq experiment using automated ChIP reagents and ChIP grade antibodies optimized to work on low chromatin quantities. Use chromatin corresponding to 10,000 cells and 100,000 cells, 0.5 &#956;g of anti-H3K27me3, 0.25 &#956;g -H3K4me3, 0.1 &#956;g -H3K27ac, 0.25 &#956;g -H3K9me3 rabbit Premium ChIP-seq grade rabbit polyclonal antibodies. Optimal antibody amounts vary depending on the histone modification and the affinity and specificity of the corresponding antibody.
		<ol>
			<li>Use equal amount of non-immune rabbit IgG as an isotype control antibody. Alternatively, use uncoated beads or specific blocked antibody as ChIP controls. Add 10 &#956;l of Protein-A coated magnetic beads for each reaction.</li>
		</ol>
		</li>
		<li>Select the automated ChIP protocol following the software instructions implemented in the automation device. Set the ChIP experimental parameters to 4 hr for the antibody coating step and 15 hr for the immunoprecipitation step. The reverse crosslinking step takes place in the automated instrument at 65 &#176;C for 4 hr.</li>
		<li>Purify reverse cross-linked DNA using spin columns following manufacturer&#8217;s instructions and elute in volumes from 6 &#956;l to 25 &#956;l of water.</li>
		<li>Quantify the DNA using a commercial assay kit. Analyze the results by qPCR using primers for positive and negative control regions to evaluate the ChIP quality.</li>
		<li>Use a library preparation kit with optimized library preparation reagents to prepare libraries with low DNA quantities. Use 30 pg and 300 pg of ChIP DNA (corresponding to 10,000 and 100,000 cells experiments respectively) for library preparation. Prepare libraries using the automated protocol compatible with library preparation reagents. The automated library prep throughput is 1 to 48 libraries per run.</li>
		<li>Following the end repair of the double-stranded DNA templates, ligate the cleavable stem-loop adaptors containing the sequencing primer sites. Following the DNA extension step, amplify the sample with the high fidelity amplification method described in the library preparation kit protocol.</li>
		<li>After library amplification, quantify and purify the libraries following the library preparation kit guidelines. Note that size selection after purification is not necessary.</li>
		<li>Sequence the libraries and generate clusters according to the manufacturer&#8217;s instructions. Perform primary bioinformatics analysis (cluster filtering, base calling, etc.) following the standard manufacturer pipeline, filter, and align the reads to the latest human genome assembly (current version is GRCh38) with the ELAND7 aligner. Use SICER8 or MACS9 for peak calling and perform the downstream analyses of peaks with Homer, BEDTools10, or any preferred software.</li>
	</ol>
	</li>
</ol>
<img alt="Figure 1" src="/files/ftp_upload/52150/52150fig1highres.jpg" /> 
Figure 1. Screenshots of the software showing how to set up automated ChIP experiments in the IP-Star Compact. The software provides the flexibility to select the amount of samples per run as well as to change key experimental parameters (Antibody Coating, IP and washes) according to the researcher needs. The automated procedure allows testing different conditions in parallel (i.e., different types and amounts of antibodies, different types and amounts of cells and even different types and amounts of magnetic beads in the same run. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/52150/52150fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" src="/files/ftp_upload/52150/52150fig2highres.jpg" /> 
Figure 2. Screenshots of the software showing how to set up automated library preparation for next generation sequencing using the library kit in the automation system. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/52150/52150fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

<ol><li>Dahl, J. A., Collas, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((A+rapid+micro+chromatin+immunoprecipitation+assay+%28microChIP%29%5BTitle%5D)+AND+%22Nature+Protocols%22%5BJournal%5D)">A rapid micro chromatin immunoprecipitation assay (microChIP).</a> Nature Protocols. 3, 1032-1045 (2008).</li>
<li>Adli, M., Bernstein, B. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Whole-genome+chromatin+profiling+from+limited+numbers+of+cells+using+nano-ChIP-seq%5BTitle%5D)+AND+%22Nature+Protocols%22%5BJournal%5D)">Whole-genome chromatin profiling from limited numbers of cells using nano-ChIP-seq.</a> Nature Protocols. 6, 1656-1668 (2011).</li>
<li>Blecher-Gonen, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((High-throughput+chromatin+immunoprecipitation+for+genome-wide+mapping+of+in+vivo+protein-DNA+interactions+and+epigenomic+states%5BTitle%5D)+AND+%22Nature+Protocols%22%5BJournal%5D)">High-throughput chromatin immunoprecipitation for genome-wide mapping of in vivo protein-DNA interactions and epigenomic states.</a> Nature Protocols. 8, 539-554 (2013).</li>
<li>Aldridge, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((AHT-ChIP-seq%3A+a+completely+automated+robotic+protocol+for+high-throughput+chromatin+immunoprecipitation%5BTitle%5D)+AND+%22Genome+Biology%22%5BJournal%5D)">AHT-ChIP-seq: a completely automated robotic protocol for high-throughput chromatin immunoprecipitation.</a> Genome Biology. 14, 124(2013).</li>
<li>Farias-Hesson, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Semi-automated+library+preparation+for+high-throughput+DNA+sequencing+platforms%5BTitle%5D)+AND+%22Journal+of+Biomedicin.%2C+%26+Biotechnology%22%5BJournal%5D)">Semi-automated library preparation for high-throughput DNA sequencing platforms.</a> Journal of Biomedicin., & Biotechnology. 2010, (2010).</li>
<li>Callejas, S., Alvarez, R., Benguria, A., Dopazo, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((AG-NGS%3A+a+powerful+and+user-friendly+computing+application+for+the+semi-automated+preparation+of+next-generation+sequencing+libraries+using+open+liquid+handling+platforms%5BTitle%5D)+AND+%22BioTechniques%22%5BJournal%5D)">AG-NGS: a powerful and user-friendly computing application for the semi-automated preparation of next-generation sequencing libraries using open liquid handling platforms.</a> BioTechniques. 56, 28-35 (2014).</li>
<li>Zang, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((A+clustering+approach+for+identification+of+enriched+domains+from+histone+modification+ChIP-Seq+data%5BTitle%5D)+AND+%22Bioinformatics%22%5BJournal%5D)">A clustering approach for identification of enriched domains from histone modification ChIP-Seq data.</a> Bioinformatics. 25, Oxford, England. 1952-1958 (2009).</li>
<li>Zhang, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Model-based+analysis+of+ChIP-Seq+%28MACS%29%5BTitle%5D)+AND+%22Genome+Biology%22%5BJournal%5D)">Model-based analysis of ChIP-Seq (MACS).</a> Genome Biology. 9, 137(2008).</li>
<li>Heinz, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Simple+combinations+of+lineage-determining+transcription+factors+prime+cis-regulatory+elements+required+for+macrophage+and+B+cell+identities%5BTitle%5D)+AND+%22Molecular+Cell%22%5BJournal%5D)">Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities.</a> Molecular Cell. 38, 576-589 (2010).</li>
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</ol>

The authors of this article, at the time of its writing, are employed by Diagenode S.A. and Diagenode, Inc., the manufacturer of the automated system described.

Chromatin immunoprecipitation followed by sequencing is now a standard procedure. Here an automated ChIP-seq protocol that can generate chromatin epigenetic profiles with as few as 10,000 cells of starting material is presented.
Automating ChIP and library preparation assays allows standardizing the ChIP optimization procedure and reducing experimental variability. The liquid handling system presented here eliminates many of the manual procedures associated with ChIP reducing the hands on time to just 30 min, minimizes sample loss, and enables accurate ChIP-seq with just a few picograms of library input. In order to achieve successful automated ChIP-seq experiments, it is also crucial to use high quality sheared chromatin preparations and ChIP-seq grade antibodies in each experiment The system uses magnetic bead-based technology and offers flexibility to change main experimental parameters such as incubation time for the antibody coating and immunoprecipitation steps or modification of the washing conditions allowing the researcher to conduct all necessary experiments for ChIP-seq optimization. The automated system is an &#8220;open&#8221; platform that also allows comparison of multiple reagents in parallel for optimization of experimental conditions for each individual cell line and antibody and enables direct comparison of various types and concentrations of chromatin, different antibodies and even different types of magnetic beads.
One of the limitations of the automated system is the need of automating all protocols in volumes that range from 5 &#956;l to 200 &#956;l. However, the miniaturization of the experiments in this automated platform also enables saving costs in reagents.
In addition to the protocols described in this study, the system is adaptable and also automates a variety of other magnetic bead based applications such as immunoprecipitation and capture of methylated DNA (MeDIP and MethylCap technologies), immunoprecipitation of hydroxylmethylated DNA (hMEDIP), sequential chromatin immunoprecipitation (ReChIP), RNA immunoprecipitation (RNA-IP), bisulfite conversion, and DNA purification assays.

As Next-Generation Sequencing (NGS) technologies have become widespread and more accessible, the primary method for genome-wide mapping of protein-DNA interactions is now chromatin immunoprecipitation followed by NGS detection (ChIP-seq), which enables the discovery of transcription factor binding sites or patterns of histone modifications. ChIP-seq is advantageous in providing high-throughput data of the whole genome that can be used for quantitative and qualitative analysis of the protein-DNA interactions by the measurement of the enriched DNA fragments. However, there are some disadvantages in standard ChIP-seq experiments such as the difficulty in obtaining enough material to create a sequencing library.
ChIP experiments are divided into six basic steps including 1) crosslinking protein-DNA binding regions 2) sample preparation which includes cell lysis and shearing the chromatin by sonication, 3) formation of the immunocomplexes, 4) precipitation of the immunocomplexes, 5) washing of the immunocomplexes, and 6) elution of the enriched material and analysis by qPCR and NGS.
The success of a ChIP assay is dependent on three main factors: a good chromatin preparation, the amount of antigen in the original sample, and the specificity and affinity of the antibody for its cognate antigen. A major limitation is the requirement for high amounts of starting cell numbers in order to obtain enough enriched DNA to create a sequencing library. For scientists who work with limited sample amounts, such as biopsy samples or cell sub-populations, ChIP-seq experiments are very challenging. Recent studies have shown that ChIP-seq assays can be performed when working with a low amount of cells1, 2. Diagenode has developed a robotic liquid handling system that can fully automate ChIP-seq experiments when starting with a limited number of cells.
Automation provides many advantages over manual preparation of ChIP-seq samples as it diminishes human error, reduces variability, and reduces experimental cost. Semi-automated protocols for chromatin immunoprecipitation and library preparation have been reported but none of these studies has shown data when using low cell numbers3, 4, 5, 6.
In this paper a complete automated workflow is described for both chromatin immunoprecipitation and library preparation assays in a robotic liquid-handling system that uses magnetic bead-based technology and that can address multiple parameters in the protocol optimization. Here, automated ChIP-seq experiments were successfully performed on a limited number of cells with the goal of simplifying, standardizing, and providing a reliable solution to study epigenetic profiles in small cell populations. The automated ChIP protocol described in this paper has been optimized on HeLa cells using specific histone antibodies and reagents but the workflow can be adapted to other cell lines and antibodies with corresponding experimental optimization.

<table><tbody><tr><td>PBS&amp;nbsp;</td><td>Life technologies</td><td>14190-094</td><td></td></tr><tr><td>Trypsin-EDTA</td><td>Sigma</td><td>T3924-100ML</td><td></td></tr><tr><td>Formaldehyde 37%</td><td>Sigma</td><td>F8775-25</td><td></td></tr><tr><td>1.25 M Glycine Solution</td><td>Diagenode</td><td>C01020010</td><td>Component of the ideal ChIP-seq kit</td></tr><tr><td>Lysis Buffer iL1</td><td>Diagenode</td><td>C01020010</td><td>Component of the ideal ChIP-seq kit</td></tr><tr><td>Lysis Buffer iL2</td><td>Diagenode</td><td>C01020010</td><td>Component of the ideal ChIP-seq kit</td></tr><tr><td>Shearing Buffer iS1</td><td>Diagenode</td><td>C01020010</td><td>Component of the ideal ChIP-seq kit</td></tr><tr><td>Protease Inhibitors Mix (200x)</td><td>Diagenode</td><td>C01010130</td><td>Component of the Auto True Micro ChIP kit</td></tr><tr><td>HBSS (no calcium, no magnesium, no phenol red)</td><td>Life technologies</td><td>14175-053</td><td></td></tr><tr><td>Lysis Buffer tL1</td><td>Diagenode</td><td>C01010130</td><td>Component of the Auto True Micro ChIP kit</td></tr><tr><td>ChIP Buffer tC1</td><td>Diagenode</td><td>C01010130</td><td>Component of the Auto True Micro ChIP kit</td></tr><tr><td>ideal ChIP-seq kit</td><td>Diagneode</td><td>C01010051</td><td></td></tr><tr><td>ChIP-Buffer H</td><td>Diagenode</td><td>C01010020</td><td>Component of the Auto Histone ChIP-seq kit</td></tr><tr><td>Auto Histone ChIP-seq kit</td><td>Diagenode</td><td>C01010020</td><td></td></tr><tr><td>Auto True Micro ChIP kit</td><td>Diagenode</td><td>C01010130</td><td></td></tr><tr><td>H3K79me3 polyclonal antibody-Classic</td><td>Diagenode</td><td>C15310068</td><td></td></tr><tr><td>H3K27me3 polyclonal antibody-Classic</td><td>Diagenode</td><td>C15410069</td><td></td></tr><tr><td>H3K4me3 polyclonal antibody-Classic</td><td>Diagenode</td><td>C15410030</td><td></td></tr><tr><td>H3K4me2 polyclonal antibody-Classic</td><td>Diagenode</td><td>C15410035</td><td></td></tr><tr><td>H3K9ac polyclonal antibody-Premium</td><td>Diagenode</td><td>C15410004</td><td></td></tr><tr><td>H3K9/14ac polyclonal antibody-Premium</td><td>Diagenode</td><td>C15410200</td><td></td></tr><tr><td>H3K36me3 polyclonal antibody-Premium</td><td>Diagenode</td><td>C15410058</td><td></td></tr><tr><td>H3K9me3 polyclonal antibody-Premium</td><td>Diagenode</td><td>C15410193</td><td></td></tr><tr><td>Rabbit IgG</td><td>Diagenode</td><td>C15410206</td><td></td></tr><tr><td>Protein-A coated paramagnetic beads</td><td>Diagenode</td><td>C01010020</td><td></td></tr><tr><td>Auto IPure</td><td>Diagenode</td><td>C03010010</td><td></td></tr><tr><td>MicroChIP DiaPure columns</td><td>Diagenode</td><td>C03040001</td><td></td></tr><tr><td>Universal SyberGreenMaster Mix 1.25 ml</td><td>Diagenode</td><td>DMMLD2D100&amp;nbsp;</td><td></td></tr><tr><td>Quant-IT dsDNA</td><td>Invitrogen</td><td>Q32854</td><td></td></tr><tr><td>Illumina Sample Preparation kit fro Genomic DNA</td><td>Illumina</td><td>FC-121-3001</td><td></td></tr><tr><td>Illumina True-seq kit ChIP library Prep kit</td><td>Illumina</td><td>IP-202-1012</td><td></td></tr><tr><td>MicroPlex Library Preparation Kit</td><td>Diagenode</td><td>C05010010</td><td></td></tr><tr><td>Agencourt AMPure XP beads</td><td>Beckman Coulter</td><td>A63881</td><td></td></tr><tr><td>Illumina Library prep Quantification kit</td><td>Kapa Biosystems</td><td>KK4844</td><td></td></tr><tr><td>IP-Star Compact&amp;nbsp; Automated System</td><td>Diagenode</td><td>B03000002</td><td></td></tr><tr><td>Bioruptor Plus</td><td>Diagenode</td><td>B01020001</td><td></td></tr><tr><td>Bioruptor Pico</td><td>Diagenode</td><td>B01060001</td><td></td></tr><tr><td>Qubit system</td><td>Invitrogen</td><td>Q32857</td><td></td></tr><tr><td>Illumina Hiseq systems</td><td>Illumina</td><td></td><td></td></tr></tbody></table>

automating chip-seq experiments to generate epigenetic profiles on 10,000 hela cells

Chromatin immunoprecipitation followed by next generation sequencing (ChIP-seq) is a technique of choice for studying protein-DNA interactions. ChIP-seq has been used for mapping protein-DNA interactions and allocating histones modifications. The procedure is tedious and time consuming, and one of the major limitations is the requirement for high amounts of starting material, usually millions of cells. Automation of chromatin immunoprecipitation assays is possible when the procedure is based on the use of magnetic beads. Successful automated protocols of chromatin immunoprecipitation and library preparation have been specifically designed on a commercially available robotic liquid handling system dedicated mainly to automate epigenetic assays. First, validation of automated ChIP-seq assays using antibodies directed against various histone modifications was shown, followed by optimization of the automated protocols to perform chromatin immunoprecipitation and library preparation starting with low cell numbers. The goal of these experiments is to provide a valuable tool for future epigenetic analysis of specific cell types, sub-populations, and biopsy samples.

Optimizing automated ChIP-seq experiments for eight different histone markers
In order to successfully develop and validate the automated ChIP protocols, ChIP-seq grade antibodies that were previously validated in manual ChIP-Seq experiments (data not shown) were selected. The following ChIP-seq grade antibodies were chosen for this study: anti-H3K79me3, -H3K27me3, -H3K4me3, -H3K4me2, -H3K9ac, -H3K9/14ac, -H3K36me3 and -H3K9me3. The specificity of all ChIP-seq grade antibodies was previously confirmed by dot blot, peptide arrays and Western Blot experiments (data not shown). Pilot ChIP-qPCR experiments with increasing antibody amounts were performed to determine the sensitivity of the antibodies (Figure 3). qPCR with at least two positive and two negative control targets were analyzed and profiles with enrichments of positive over negative target higher than fivefold are qualified for sequencing experiments. It is important to perform ChIP and ChIP-seq experiments with a high quality of sheared chromatin. All ChIP experiments shown in this publication were performed using fresh chromatin. It is also possible to freeze the fixed cells at -80 &#176;C and proceed with the chromatin preparation and shearing on a different day. However, chromatin prepared from frozen fixed cells may behave differently from chromatin freshly prepared and therefore sonication conditions may need to be optimized for each chromatin preparation. When working with different cell types, shearing buffers with different detergent compositions (SDS) can be used. Cell types such as primary cell lines or cell grown in suspension are difficult cells to shear and will require of high SDS concentrations (1%) whereas cell lines that are easy to shear such as HeLa will require low SDS concentrations (0.1%) in the shearing buffers.
<img alt="Figure 3" src="/files/ftp_upload/52150/52150fig3highres.jpg" /> 
Figure 3. Validation of ChIP-grade antibodies using the automation system. ChIP was performed with anti-H3K79me3, -H3K27me3, -H3K4me3, -H3K4me2, -H3K9ac, H3K9/14ac, -H3K36me3 and -H3K9me3 rabbit polyclonal antibodies on sheared chromatin from 1 million HeLa-S3 cells depending on the histone modifications. Automated ChIP protocols with 200 &#181;l working volumes were used in the automation instrument for antibody titration experiments. Antibody quantities of 1, 2, 5 and 10 &#956;g were tested per ChIP experiment and 2 &#956;g IgG were used as negative control in each experiment. Enrichments were assessed by qPCR. Results are shown as a % of input (the relative amount of immunoprecipitated DNA compared to input DNA after qPCR analysis). <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/52150/52150fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
After validating and determining optimal amounts of ChIP-grade antibodies to be used in the automation system, automated ChIP-seq experiments were performed in order to generate sequencing profiles for each histone modification (Figure 4).
<img alt="Figure 4" src="/files/ftp_upload/52150/52150fig4highres.jpg" /> 
Figure 4. Histone ChIP-seq profiles generated by automated ChIP-seq experiments. The figure shows the ChIP-seq profiles in different genomic regions for H3K4me3, H3K9ac and H3K9/14acH3K4me2 H3K79me3, and H3K36me3. 4A shows the peak distribution along the complete X-chromosome and 4B the distribution in a 75 kb region surrounding the GAPDH gene. 4C shows the profiles of H3K27me3, H3K36me3 and H3K4me3 in a 500 kb region surrounding the MYT1 gene and 4D shows the distribution of H3K9me3 in a 200 kb region surrounding ZNF12. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/52150/52150fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Histone epigenetic profiles for six different histone modifications associated with gene expression were generated (H3K4me3, H3K9ac, H3K9/14ac, H3K4me2, H3K79me3 and H3K36me3). Figure 4A shows ChIP-seq profiles along the chromosome X for the different histone markers. The highly peak correlation observed between the 6 different histone profiles indicates the capabilities of automated system to generate accurate and reliable data. Figure 4B, 4C and 4D show the distribution of peaks for different histone modifications at specific genomic regions.
Automated chromatin immunoprecipitation experiments down to 200 cells
The minimum amount of cells that can be used in ChIP experiments depends on the quality of the chromatin, the specificity and sensitivity of the antibody and the abundance of the histone modification or protein studied. Selecting good ChIP-seq grade antibodies is important when working with limited amounts of sample and the selection of optimal reagents and different carriers improves the efficiency of the DNA recovery and contribute to the success of the ChIP experiment. To determine the minimum amount of cells that the automated ChIP protocol can process, different quantities of chromatin, antibody, and magnetic beads were tested in the IP-Star automated system using ChIP reagents specifically optimized to work with low quantities of chromatin.
First, chromatin from 10,000 cells was sonicated as described in the protocol. The ChIP results were confirmed by qPCR (Figure 5A) which shows significant enrichments with H3K4me3 antibody in positive control regions and negligible signal in negative control regions. For comparison and proof of consistency, additional data obtained with H3K27ac, H3K9me3, and H3K27me3 antibodies, using 10,000 cells is provided.
Automated ChIP experiments were performed then to demonstrate the capabilities of the automated system to work with low quantities of cells using the same H3K4me3 antibody. The automated ChIP performed well, demonstrated by a series of ten IP reactions that were reproducible and highly comparable with the manual ChIP results (Figure 5B). Manual and automated experiments were performed and benefits of the automated protocols were seen in reducing experiment to experiment variability (Figure 5C).
<img alt="Figure 5" src="/files/ftp_upload/52150/52150fig5highres.jpg" /> 
Figure 5. Optimization of ChIP and Auto ChIP experiments on 10,000 cells Manual ChIP experiments were performed on 10,000 cells and using 0.25 &#956;g of H3K4me3, 0.1 &#956;g of H3K27ac, 0.5 &#956;g of H3K9me3 and 0.25 &#956;g of H3K27me3 antibodies. Identical quantities of rabbit IgG were used as a control. The qPCR was performed with primers for two positive loci and two negative loci for each ChIP assay. Figure 5A shows the recovery, expressed as a percentage of input (the relative amount of immunoprecipitated DNA compared to input DNA after qPCR analysis). Figure 5B shows 10 ChIP reactions run on the IP-Star Compact using 0.25 &#956;g H3K4me3 polyclonal antibody and 0.25 &#956;g of rabbit IgG as negative control antibody. Then qPCR analysis was performed with primers for the positive loci EIF4A2 promoter and GAPDH TSS and the negative loci Myoglobin exon2 and Sat2. The figure shows the recovery, expressed as a percent of input (relative amount of immunoprecipitated DNA compared to input DNA after qPCR analysis). Figure 5C shows H3K4me3 ChIP data of 10 manual ChIP experiments in comparison to 10 automated ChIP experiments. Error bars represent standard deviations of each of the ten replicates. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/52150/52150fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
In order to understand the sensitivity of the automated ChIP protocols, experiments were performed using an amount of cells that ranged from 100,000 down to 200 cells per IP. The anti-H3K27me3 antibody was used as it is a very common histone modification. The use of other histone or non-histone antibodies may require more or less cells, depending on the abundance of the epitope and the quality of the antibody. The experiments were validated by quantitative PCR and it was observed that by reducing amounts of beads and antibody background in the experiments is reduced allowing successful ChIP-qPCR results with as little as 200 cells antibody (Figure 6).
<img alt="Figure 6" src="/files/ftp_upload/52150/52150fig6highres.jpg" /> 
Figure 6. Automated ChIP assays on 200 cells. Hela-S3 cells and antibody directed against H3K27me3. Chromatin was sheared from 1 million cells and serial dilutions of this chromatin (from 100,000 to 200 cell equivalent) were used per ChIP reaction. 1 &#181;g of H3K27me3 and 10 &#956;l of protein A-coated magnetic beads were used on 100,000 cells experiment, 0.5 &#181;g of H3K27me3 and 10 &#181;l of beads on 10,000 and 1,000 cells, and 0.25 &#181;g of H3K27me3 and 5 &#181;l of beads with 500 and 200 cells. 1 &#181;g and 0.5 of &#956;g of rabbit IgG were used as negative control antibody when performing experiments with 100,000 cells and 1,000 cells respectively. 6A shows the occupancy of TSH2B and GAPDH genes in % over input. 6B shows relative occupancy of TSH2B versus negative GAPDH control genomic region.
Downstream analysis of ChIP-seq results on 10,000 cells 
In order to assess the global quality of the automated ChIP-seq experiments with low starting numbers of cells, automated ChIP-seq assays were performed with 0.25 &#181;g of the H3K4me3 antibody on 10,000 HeLa cells and ChIP experiments on 100,000 HeLa-S3 cells were used as positive control for the experiment. The automated libraries were prepared using the MicroPlex library preparation kit reagents adapted to prepared libraries with low DNA amounts. Note that even though it is possible to perform successful automated ChIP-experiments with less than 10,000 cells, the amounts of pulled down DNA will not be enough to prepare libraries using the kit reagents. Cluster generation and sequencing were performed according to the manufacturer&#8217;s instructions. The bioinformatics analyses after the sequencing show outstanding results from the low cell number ChIP samples. The 30 pg dataset (corresponding to 10,000 cells of starting material) contain low background noise and highly reliable enrichment peaks which are confirmed by both the 300 pg dataset (corresponding to 100,000 cells of starting material) and the H3K4me3 dataset generated by the Broad Institute for the ENCODE project which was used as an external reference. It is important to note the Top 40 overlap ratio data, which refers to a standard method used in the ENCODE11 project in which the ChIP-seq is considered reproducible if comparing two datasets there is at least an 80% overlap of the best 40% of the peaks ranked by significance score. The 30 pg dataset fulfills these criteria when compared to both the 300 pg dataset (considering all of its peaks, not just the best 40%) and the Broad Institute data (Table 1). The 300 pg dataset shows almost identical peaks to Broad Institute data with a 98% Top 40 overlap ratio (Figure 7).
<img alt="Figure 7" src="/files/ftp_upload/52150/52150fig7highres.jpg" /> 
Figure 7. ChIP assays and library generation on 10,000 cells ChIP-seq experiments were generated on 10,000 and 100,000 HeLa-S3 cells using H3K4me3 antibody (0.25 &#181;g/&#181;l). The 35 bp tags were mapped to the human genome with the ELAND aligner. During the subsequent peak calling SICER could reliably identify the enrichments from low cell numbers as well as from millions of cells. The datasets were analyzed and compared with each other and to the reference data generated by the Broad Institute. The low cell samples are consistent and have very high similarity. The 30 pg sample fulfills the ENCODE criteria11 (min. 80% of the top 40% of the peaks should overlap). <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/52150/52150fig7large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Table 1" src="/files/ftp_upload/52150/52150table1.jpg" /> 
Table 1.

Watch this Scientific Journal Video about Automating ChIP-seq Experiments to Generate Epigenetic Profiles on 10,000 HeLa Cells at JoVE.com

Automating ChIP-seq Experiments to Generate Epigenetic Profiles on 10,000 HeLa Cells

Methods for mapping in vivo protein-DNA interactions are becoming crucial for every aspect of genomic research but they are laborious, costly, and time consuming. Here a commercially available robotic liquid handling system that automates chromatin immunoprecipitation for mapping in vivo protein-DNA interactions with limited amounts of cells is presented.

Chromatin immunoprecipitation followed by next generation sequencing (ChIP-seq) is a technique of choice for studying protein-DNA interactions. ChIP-seq ...

automating-chip-seq-experiments-to-generate-epigenetic-profiles-on

Nanyang Technological University

Research

JoVE Journal

Biology

18.7K Views.  Diagenode S.A.. Methods for mapping in vivo protein-DNA interactions are becoming crucial for every aspect of genomic research but they are laborious, costly, and time consuming. Here a commercially available robotic liquid handling system that automates chromatin immunoprecipitation for mapping in vivo protein-DNA interactions with limited amounts of cells is presented.

Video: Automating ChIP-seq Experiments to Generate Epigenetic Profiles on 10,000 HeLa Cells

An Integrated Platform for Genome-wide Mapping of Chromatin States Using High-throughput ChIP-sequencing in Tumor Tissues

Histone modifications constitute a major component of the epigenome and play important regulatory roles in determining the transcriptional status of associated loci. In addition, the presence of specific modifications has been used to determine the position and identity non-coding functional elements such as enhancers. In recent years, chromatin immunoprecipitation followed by next generation sequencing (ChIP-seq) has become a powerful tool in determining the genome-wide profiles of individual histone modifications. However, it has become increasingly clear that the combinatorial patterns of chromatin modifications, referred to as Chromatin States, determine the identity and nature of the associated genomic locus. Therefore, workflows consisting of robust high-throughput (HT) methodologies for profiling a number of histone modification marks, as well as computational analyses pipelines capable of handling myriads of ChIP-Seq profiling datasets, are needed for comprehensive determination of epigenomic states in large number of samples. The HT-ChIP-Seq workflow presented here consists of two modules: 1) an experimental protocol for profiling several histone modifications from small amounts of tumor samples and cell lines in a 96-well format; and 2) a computational data analysis pipeline that combines existing tools to compute both individual mark occupancy and combinatorial chromatin state patterns. Together, these two modules facilitate easy processing of hundreds of ChIP-Seq samples in a fast and efficient manner. The workflow presented here is used to derive chromatin state patterns from 6 histone mark profiles in melanoma tumors and cell lines. Overall, we present a comprehensive ChIP-seq workflow that can be applied to dozens of human tumor samples and cancer cell lines to determine epigenomic aberrations in various malignancies.

Here, we describe an optimized high-throughput ChIP-sequencing protocol and computational analyses pipeline for the determination of genome-wide chromatin state patterns from frozen tumor tissues and cell lines.

Histone modifications constitute a major component of the epigenome and play important regulatory roles in determining the transcriptional status of ...

Cancer Research

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

Immunophenotypic characterization and molecular analysis have long been used to delineate heterogeneity and define distinct cell populations. FACS is inherently a single-cell assay, however prior to molecular analysis, the target cells are often prospectively isolated in bulk, thereby losing single-cell resolution. Single-cell gene expression analysis provides a means to understand molecular differences between individual cells in heterogeneous cell populations. In bulk cell analysis an overrepresentation of a distinct cell type results in biases and occlusions of signals from rare cells with biological importance. By utilizing FACS index sorting coupled to single-cell gene expression analysis, populations can be investigated without the loss of single-cell resolution while cells with intermediate cell surface marker expression are also captured, enabling evaluation of the relevance of continuous surface marker expression. Here, we describe an approach that combines single-cell reverse transcription quantitative PCR (RT-qPCR) and FACS index sorting to simultaneously characterize the molecular and immunophenotypic heterogeneity within cell populations.
In contrast to single-cell RNA sequencing methods, the use of qPCR with specific target amplification allows for robust measurements of low-abundance transcripts with fewer dropouts, while it is not confounded by issues related to cell-to-cell variations in read depth. Moreover, by directly index-sorting single-cells into lysis buffer this method, allows for cDNA synthesis and specific target pre-amplification to be performed in one step as well as for correlation of subsequently derived molecular signatures with cell surface marker expression. The described approach has been developed to investigate hematopoietic single-cells, but have also been used successfully on other cell types.
In conclusion, the approach described herein allows for sensitive measurement of mRNA expression for a panel of pre-selected genes with the possibility to develop protocols for subsequent prospective isolation of molecularly distinct subpopulations.

Bulk gene expression measurements cloud individual cell differences in heterogeneous cell populations. Here, we describe a protocol for how single-cell gene expression analysis and index sorting by Florescence Activated Cell Sorting (FACS) can be combined to delineate heterogeneity and immunophenotypically characterize molecularly distinct cell populations.

Immunophenotypic characterization and molecular analysis have long been used to delineate heterogeneity and define distinct cell populations. FACS is ...

Genetics

Reusable Single Cell for Iterative Epigenomic Analyses

Current single-cell epigenome analyses are designed for single use. The cell is discarded after a single use, preventing analysis of multiple epigenetic marks in a single cell and requiring data from other cells to distinguish signal from experimental background noise in a single cell. This paper describes a method to reuse the same single cell for iterative epigenomic analyses. 
In this experimental method, cellular proteins are first anchored to a polyacrylamide polymer instead of crosslinking them to protein and DNA, alleviating structural bias. This critical step allows repeated experiments with the same single cell. Next, a random primer with a scaffold sequence for proximity ligation is annealed to the genomic DNA, and the genomic sequence is added to the primer by extension using a DNA polymerase. Subsequently, an antibody against an epigenetic marker and control IgG, each labeled with different DNA probes, are bound to the respective targets in the same single cell. 
Proximity ligation is induced between the random primer and the antibody by adding a connector DNA with complementary sequences to the scaffold sequence of the random primer and the antibody-DNA probe. This approach integrates antibody information and nearby genome sequences in a single DNA product of proximity ligation. By enabling repeated experiments with the same single cell, this method allows an increase in data density from a rare cell and statistical analysis using only IgG and antibody data from the same cell. The reusable single cells prepared by this method can be stored for at least a few months and reused later to broaden epigenetic characterization and increase data density. This method provides flexibility to researchers and their projects.

The present protocol describes a single-cell method for iterative epigenomic analyses using a reusable single cell. The reusable single cell allows analyses of multiple epigenetic marks in the same single cell and statistical validation of the results.

Current single-cell epigenome analyses are designed for single use. The cell is discarded after a single use, preventing analysis of multiple epigenetic ...

ATAC-Seq Optimization for Cancer Epigenetics Research

The assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) probes deoxyribonucleic acid (DNA) accessibility using the hyperactive Tn5 transposase. Tn5 cuts and ligates adapters for high-throughput sequencing within accessible chromatin regions. In eukaryotic cells, genomic DNA is packaged into chromatin, a complex of DNA, histones, and other proteins, which acts as a physical barrier to the transcriptional machinery. In response to extrinsic signals, transcription factors recruit chromatin remodeling complexes to enable access to the transcriptional machinery for gene activation. Therefore, identifying open chromatin regions is useful when monitoring enhancer and gene promoter activities during biological events such as cancer progression. Since this protocol is easy to use and has a low cell input requirement, ATAC-seq has been widely adopted to define open chromatin regions in various cell types, including cancer cells. For successful data acquisition, several parameters need to be considered when preparing ATAC-seq libraries. Among them, the choice of cell lysis buffer, the titration of the Tn5 enzyme, and the starting volume of cells are crucial for ATAC-seq library preparation in cancer cells. Optimization is essential for generating high-quality data. Here, we provide a detailed description of the ATAC-seq optimization methods for epithelial cell types.

ATAC-seq is a DNA sequencing method that uses the hyperactive mutant transposase, Tn5, to map changes in chromatin accessibility mediated by transcription factors. ATAC-seq enables the discovery of the molecular mechanisms underlying phenotypic alterations in cancer cells. This protocol outlines optimization procedures for ATAC-seq in epithelial cell types, including cancer cells.

The assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) probes deoxyribonucleic acid (DNA) accessibility using the ...

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing

Sequencing technologies have undergone a paradigm shift from bulk to single-cell resolution in response to an evolving understanding of the role of cellular heterogeneity in biological systems. However, single-cell sequencing of large populations has been hampered by limitations in processing genomes for sequencing. In this paper, we describe a method for single-cell genome sequencing (SiC-seq) which uses droplet microfluidics to isolate, amplify, and barcode the genomes of single cells. Cell encapsulation in microgels allows the compartmentalized purification and tagmentation of DNA, while a microfluidic merger efficiently pairs each genome with a unique single-cell oligonucleotide barcode, allowing &gt;50,000 single cells to be sequenced per run. The sequencing data is demultiplexed by barcode, generating groups of reads originating from single cells. As a high-throughput and low-bias method of single-cell sequencing, SiC-seq will enable a broader range of genomic studies targeted at diverse cell populations.

Single-cell sequencing reveals genotypic heterogeneity in biological systems, but current technologies lack the throughput necessary for the deep profiling of community composition and function. Here, we describe a microfluidic workflow for sequencing &gt;50,000 single-cell genomes from diverse cell populations.

Sequencing technologies have undergone a paradigm shift from bulk to single-cell resolution in response to an evolving understanding of the role of ...

Bioengineering

Repressing Gene Transcription by Redirecting Cellular Machinery with Chemical Epigenetic Modifiers

Regulation of chromatin compaction is an important process that governs gene expression in higher eukaryotes. Although chromatin compaction and gene expression regulation are commonly disrupted in many diseases, a locus-specific, endogenous, and reversible method to study and control these mechanisms of action has been lacking. To address this issue, we have developed and characterized novel gene-regulating bifunctional molecules. One component of the bifunctional molecule binds to a DNA-protein anchor so that it will be recruited to an allele-specific locus. The other component engages endogenous cellular chromatin-modifying machinery, recruiting these proteins to a gene of interest. These small molecules, called chemical epigenetic modifiers (CEMs), are capable of controlling gene expression and the chromatin environment in a dose-dependent and reversible manner. Here, we detail a CEM approach and its application to decrease gene expression and histone tail acetylation at a Green Fluorescent Protein (GFP) reporter located at the Oct4 locus in mouse embryonic stem cells (mESCs). We characterize the lead CEM (CEM23) using fluorescent microscopy, flow cytometry, and chromatin immunoprecipitation (ChIP), followed by a quantitative polymerase chain reaction (qPCR). While the power of this system is demonstrated at the Oct4 locus, conceptually, the CEM technology is modular and can be applied in other cell types and at other genomic loci.

Regulation of the chromatin environment is an essential process required for proper gene expression. Here, we describe a method for controlling gene expression through the recruitment of chromatin-modifying machinery in a gene-specific and reversible manner.

Regulation of chromatin compaction is an important process that governs gene expression in higher eukaryotes. Although chromatin compaction and gene ...

Generation of High Quality Chromatin Immunoprecipitation DNA Template for High-throughput Sequencing (ChIP-seq)

ChIP-sequencing (ChIP-seq) methods directly offer whole-genome coverage, where combining chromatin immunoprecipitation (ChIP) and massively parallel sequencing can be utilized to identify the repertoire of mammalian DNA sequences bound by transcription factors in vivo. "Next-generation" genome sequencing technologies provide 1-2 orders of magnitude increase in the amount of sequence that can be cost-effectively generated over older technologies thus allowing for ChIP-seq methods to directly provide whole-genome coverage for effective profiling of mammalian protein-DNA interactions.
For successful ChIP-seq approaches, one must generate high quality ChIP DNA template to obtain the best sequencing outcomes. The description is based around experience with the protein product of the gene most strongly implicated in the pathogenesis of type 2 diabetes, namely the transcription factor transcription factor 7-like 2 (TCF7L2). This factor has also been implicated in various cancers.
Outlined is how to generate high quality ChIP DNA template derived from the colorectal carcinoma cell line, HCT116, in order to build a high-resolution map through sequencing to determine the genes bound by TCF7L2, giving further insight in to its key role in the pathogenesis of complex traits.

Generation of High Quality Chromatin Immunoprecipitation DNA Template for High-throughput Sequencing ChIP-seq

The combination of chromatin immunoprecipitation and ultra-high-throughput sequencing (ChIP-seq) can identify and map protein-DNA interactions in a given tissue or cell line. Outlined is how to generate a high quality ChIP template for subsequent sequencing, using experience with the transcription factor TCF7L2 as an example.

ChIP-sequencing (ChIP-seq) methods directly  offer whole-genome coverage, where combining chromatin immunoprecipitation  (ChIP) and massively parallel ...

In Vitro Selection of Engineered Transcriptional Repressors for Targeted Epigenetic Silencing

Gene inactivation is instrumental to study gene function and represents a promising strategy for the treatment of a broad range of diseases. Among traditional technologies, RNA interference suffers from partial target abrogation and the requirement for life-long treatments. In contrast, artificial nucleases can impose stable gene inactivation through induction of a DNA double strand break (DSB), but recent studies are questioning the safety of this approach. Targeted epigenetic editing via engineered transcriptional repressors (ETRs) may represent a solution, as a single administration of specific ETR combinations can lead to durable silencing without inducing DNA breaks.
ETRs are proteins containing a programmable DNA-binding domain (DBD) and effectors from naturally occurring transcriptional repressors. Specifically, a combination of three ETRs equipped with the KRAB domain of human ZNF10, the catalytic domain of human DNMT3A and human DNMT3L, was shown to induce heritable repressive epigenetic states on the ETR-target gene. The hit-and-run nature of this platform, the lack of impact on the DNA sequence of the target, and the possibility to revert to the repressive state by DNA demethylation on demand, make epigenetic silencing a game-changing tool. A critical step is the identification of the proper ETRs&#39; position on the target gene to maximize on-target and minimize off-target silencing. Performing this step in the final ex vivo or in vivo preclinical setting can be cumbersome.
Taking the CRISPR/catalytically dead Cas9 system as a paradigmatic DBD for ETRs, this paper describes a protocol consisting of the in vitro screen of guide RNAs (gRNAs) coupled to the triple-ETR combination for efficient on-target silencing, followed by evaluation of the genome-wide specificity profile of top hits. This allows for reduction of the initial repertoire of candidate gRNAs to a short list of promising ones, whose complexity is suitable for their final&#160;evaluation in the therapeutically relevant setting of interest.

In Vitro Selection of Engineered Transcriptional Repressors for Targeted Epigenetic Silencing

Here, we present a protocol for the in vitro selection of engineered transcriptional repressors (ETRs) with high, long-term, stable, on-target silencing efficiency and low genome-wide, off-target activity. This workflow allows for reducing an initial, complex repertoire of candidate ETRs to a short list, suitable for further evaluation in therapeutically relevant settings.

Gene inactivation is instrumental to study gene function and represents a promising strategy for the treatment of a broad range of diseases. Among ...

TChIP-Seq: Cell-Type-Specific Epigenome Profiling

Epigenetic regulation plays central roles in gene expression. Since histone modification was discovered in the 1960s, its physiological and pathological functions have been extensively studied. Indeed, the advent of next-generation deep sequencing and chromatin immunoprecipitation (ChIP) via specific histone modification antibodies has revolutionized our view of epigenetic regulation across the genome. Conversely, tissues typically consist of diverse cell types, and their complex mixture poses analytic challenges to investigating the epigenome in a particular cell type. To address the cell type-specific chromatin state in a genome-wide manner, we recently developed tandem chromatin immunoprecipitation sequencing (tChIP-Seq), which is based on the selective purification of chromatin by tagged core histone proteins from cell types of interest, followed by ChIP-Seq. The goal of this protocol is the introduction of best practices of tChIP-Seq. This technique provides a versatile tool for tissue-specific epigenome investigation in diverse histone modifications and model organisms.

We describe a step-by-step protocol for tandem chromatin immunoprecipitation sequencing (tChIP-Seq) that enables the analysis of cell-type-specific genome-wide histone modification.

Epigenetic regulation plays central roles in gene expression. Since histone modification was discovered in the 1960s, its physiological and pathological ...

A Semiautomated ChIP-Seq Procedure for Large-scale Epigenetic Studies

Chromatin immunoprecipitation followed by sequencing (ChIP-Seq) is a powerful and widely used approach to profile chromatin DNA associated with specific histone modifications, such as H3K27ac, to help identify cis-regulatory DNA elements. The manual process to complete a ChIP-Seq is labor intensive, technically challenging, and often requires large-cell numbers (&#62;100,000 cells). The method described here helps to overcome those challenges. A complete semiautomated, microscaled H3K27ac ChIP-Seq procedure including cell fixation, chromatin shearing, immunoprecipitation, and sequencing library preparation, for batch of 48 samples for cell number inputs less than 100,000 cells is described in detail. The semiautonomous platform reduces technical variability, improves signal-to-noise ratios, and drastically reduces labor. The system can thereby reduce costs by allowing for reduced reaction volumes, limiting the number of expensive reagents such as enzymes, magnetic beads, antibodies, and hands-on time required. These improvements to the ChIP-Seq method suit perfectly for large-scale epigenetic studies of clinical samples with limited cell numbers in a highly reproducible manner.

This paper describes a semiautomated, microscaled ChIP-Seq protocol of DNA regions associated with a specific histone modification (H3K27ac) using a ChIP liquid-handler platform, followed by library preparation using tagmentation. The procedure includes control assessment for quality and quantity purposes and can be adopted to other histone modifications or transcription factors.

Chromatin immunoprecipitation followed by sequencing (ChIP-Seq) is a powerful and widely used approach to profile chromatin DNA associated with specific ...

Automating ChIP-seq Experiments to Generate Epigenetic Profiles on 10,000 HeLa Cells

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A Semiautomated ChIP-Seq Procedure for Large-scale Epigenetic Studies