Name: real-time analysis of transcription factor binding, transcription, translation, and turnover to display global events during cellular activation
Uploaded: 2018-03-07T13:00:00
Duration: 12 min 54 s
Description: Watch this Scientific Journal Video about Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation at JoVE.com

We thank Lars D&#246;lken for advice to establish 4sU labeling for primary T cells; Elisabeth Graf and Thomas Schwarzmayr for critical help in library generations and sequencing; Dirk Eick and Andrew Flatley for providing RNAPII and T cell antibodies; N. Henriette Uhlenhaut and Franziska Greulich for help in library preparation for ChIP-seq; Caroline C. Friedel was supported by grants FR2938/7-1 and CRC 1123 (Z2) from the Deutsche Forschungsgemeinschaft (DFG); Elke Glasmacher was supported by the grant GL 870/1-1 from the Deutsche Forschungsgemeinschaft (DFG) and the German Center for Diabetes Research (DZD), Helmholtz Zentrum M&#252;nchen.

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The authors declare that they have no competing financial interests.

Analyzing the whole process of gene regulation is necessary to fully understand cellular adaptations in response to a specific stimulus or treatment. Combining total RNA-seq, 4sU-seq, ribosome profiling, and ChIP-seq at different time points leads to a comprehensive analysis of the main processes of gene regulation over time. A profound understanding of biological processes is required to define the experimental setup as well as optimal time points.
Since methods to study gene regulation improve rapidly, these protocols can be adapted to rapid changes. Nevertheless, they provide the most important methods for studying basic gene regulatory mechanisms in any type of cell. Here, we discuss some of the pitfalls and facts one has to consider when using these methods.
Cells: Cells must be highly viable and, if using primary isolated cells, purity of cell populations must be guaranteed (e.g., FACS analysis for primary T cells). Even slightly stressed cells can influence the results of these very sensitive sequencing methods and lower the amount of newly transcribed or translated RNA, and lead to unwanted readouts of the stress response in the sequencing results. The centrifugation speed mentioned in this protocol to pellet cells is optimized for primary T cells. Thus, adjust the speed according to the cell type.
4sU effects on cell physiology: In addition to the aforementioned options for verifying minimal perturbation to cellular physiology upon 4sU addition, further and/or additional analysis can be performed, especially when cell numbers are limited. Effects on cell proliferation can be tested by verifying the doubling time of cells by simply counting labeled and unlabeled cells. Nucleolar stress induction could also be tested by analyzing cell morphology via immunofluorescence staining of nucleolin and nuclei. To further verify the impact of 4sU, altered global gene expression could be measured by correlating read counts from labeled total RNA to unlabeled total RNA.
Cell numbers: For in vitro generated T cells, we recommend starting with at least the amount of cells indicated in Table 2. Choose adequate numbers per method according to the type of cells. Since T cells have less cytoplasm and RNA compared to other cells, most likely lower amounts of other cells will be adequate. For ChIP-seq, cell numbers highly depend on the antibody used and the expression level of the protein of interest within the cells. For histone or RNAPII ChIP, fewe cells can be used, whereas cell numbers need to be increased when transcription factors are used, especially if they are expressed at low levels.
4sU-labeling and RNA biotinylation: When using adherent cells, 4sU labeling can be directed as described by R&#228;dle et al.19&#160;Since cells very rapidly incorporate 4sU, it can be added directly to the medium of suspension, adherent, or semi-adherent cells.
It is recommended to start the biotinylation with 60 - 80 &#181;g of RNA. Nevertheless, lower amounts of RNA can be used, although we did not test for less than 30 &#181;g. Add a coprecipitant (e.g., GlycoBlue) when precipitating RNA if the pellet is hard to see. Duffy et al. have also shown that methylthiosulfonate-activated biotin (MTS-biotin) more efficiently reacts with 4sU-labeled RNA than HPDP-biotin31. Hence, it might be worth considering switching to MTS-biotin, in particular, for the recovery of small RNAs, which tend to have fewer uridine residues (refer to the biotinylation protocol mentioned by Duffy et al.; see Purification of 4sU-labeled RNA, Experimental Procedures).
For the recovery of newly transcribed RNA, it is possible to use paramagnetic beads or RNA Cleanup beads of your choice. Always take into account that these kits may or may not purify for specific RNAs. For example, if you are interested in miRNAs, consider using specific kits for miRNA capture and sequencing.
Quantification of newly transcribed RNA: To accurately quantify newly transcribed RNA, measurement should be performed by a suitable fluorometer (see Table of Materials). Within 1 h of 4sU exposure, newly transcribed RNA represents about 1 - 4% of total RNA. Newly transcribed RNA of 1 h labeled, activated T cells consists of ~90 - 94% of rRNA11.
Ribosome Profiling: When establishing the method, we determined that using 1.5x the amount of nuclease than suggested in the original protocol guarantees proper digestion. Also, no adverse effects have been reported for elevated amounts of nuclease. Since it is quite difficult to overdigest the RPFs while they are part of the RNA bound by ribosomal proteins, you can still slightly increase the amount to titrate optimal nuclease digestion.
If less than 500 ng of RPF RNA were recovered in step 4.4.2, repeat rRNA depletion and pool purified RPFs with RNA Clean &#38; Concentrator-5 columns. Alternatively, load two identical samples next to each other on the gel (step 4.5.3) and pool gel slices during RNA elution from the gel (step 4.5.6).
We recommend cutting the RPFs on a gel as tightly as possible to the 28 and 30 nt bands. This helps in eliminating unwanted fragments from rRNAs and tRNAs, which later will become part of your library and reduce sequencing reads for your RPFs.
It is also recommended to avoid UV light during gel purification. This can create nicks in the RNA fragments, as well as pyrimidine dimers, that in the end can severely affect the library preparation and sequencing results.
Library preparation and sequencing of data: Ribosome profiling protocol enables to generate a cDNA library suitable for sequencing. Samples generated by 4sU-labeling can be directly used for library preparation with any appropriate RNA sequencing kit. Since newly transcribed RNA, especially when using short labeling times, may not yet be polyadenylated, no poly-A selection should be performed. Instead, we strongly recommend rRNA depletion to prevent reducing sequencing depth for the actual sample. Using T cells, we started with 400 ng of newly transcribed and total RNA (depending on the kit, see materials), performed rRNA depletion and reduced cycles for PCR amplification to minimize PCR bias. Library preparation can be performed with less starting material. To account for library complexity numbers of PCR cycles should be optimized.
For ChIP-seq there are also many kits available for library preparation. In our hands library preparation worked well starting with 2 ng of ChIP DNA (see materials for a suggestion on which kit to use). Be sure to check the indices for color balance during sequencing. We recommend a sequencing depth of &#8805;40 x 106 reads each for 4sU-seq, total RNA-seq, and ChIP-seq samples, and &#8805;80 x 106 reads for ribosome profiling samples. The sequencing depth depends on the sample and the downstream bioinformatics analysis and should be considered carefully. To analyze intronic reads for cotranscriptional splicing, 100 bp paired-end sequencing needs to be chosen.
Sequencing bias: Sequencing has become the gold standard when determining global changes in transcription, translation, or transcription factor binding. Within recent years, existing methods were pushed to their limits or new techniques were developed for sequencing increasingly small starting amounts of RNA. This requires amplification of cDNA, which introduces noise or bias. Recently, unique molecular identifiers (UMIs) were developed to experimentally identify duplicates introduced by PCR. Recently, it was shown that UMIs just mildly improve sequencing power and false discovery rate for differential gene expression32. Nevertheless, consider using unique molecular identifiers (UMIs) for all sequencing libraries to control for library complexity, especially when starting with low amounts of RNA and when many PCR cycles are needed.
Buffer and stock solutions: All buffers for 4sU-seq and ribosome profiling must be prepared under strict RNase-free conditions using nuclease-free water. It is recommended to buy pre-made nuclease-free NaCl, Tris-HCl, EDTA, sodium citrate, and water. To ensure nuclease-free conditions, an RNase decontaminating solution can be used to clean pipettes or surfaces. All buffers for ChIP-seq need to be at least DNase-free and can be stored at room temperature. Always add protease inhibitors and, optionally, phosphatase inhibitors right before use and keep on ice.
Bioinformatics: Analysis of all sequencing data (i.e., ChIP-seq, RNA-seq, and ribsosome profiling) involves quality control (e.g., using FastQC, http://www.bioinformatics.babraham.ac.uk/projects/fastqc/), adapter trimming (e.g., with cutadapt20) followed by mapping to the reference genome for the cells under study. For RNA-seq data (both total and 4sU-seq), as well as ribosome profiling data, a spliced RNA-seq mapper is required, such as ContextMap 221. For ChIP-seq data unspliced alignments, using BWA-MEM22 is sufficient. Gene expression can be calculated using the RPKM model (Reads per Kilobase of Exon per Million Fragments Mapped)1, after determining read counts per gene using a program, e.g. featureCounts23. For peak calling from ChIP-seq data, a number of programs are available, e.g., MACS24 or GEM25. Further downstream analyses can be performed in R26, in particular using tools provided by the Bioconductor project27.
Here, a major challenge in integrating 4sU- and total RNA levels and translational activity from ribosome profiling is normalization. A classical approach to address this problem is to normalize to levels of house-keeping genes. To reduce noise due to random fluctuations for individual house-keeping genes, it is recommended to not just use a few house-keeping genes but median levels for a larger set, e.g. the &#62;3,000 house-keeping genes compiled by Eisenberg and Levanon28. For calculation of RNA turnover rates from ratios of 4sU- to total RNA, normalization is based on median turnover rates (e.g., assuming an RNA half-life of 5h)29. However, since this assumes no overall changes for house-keeping genes, we recommend using analysis approaches independent of normalization, e.g., correlation-based clustering of a time-series of the different data types to identify groups of genes with distinct behavior in transcription and translation during activation. For a detailed description on bioinformatical integration of the different data types, we refer to the original publication11.
Analysis of turnover rates and data integration: A recently published paper33 comparing half-lives determined by a multiplexed gene control (MGC) to global methods could show that half-lives correlated best with those obtained by metabolic labeling methods compared to other methods (e.g., general inhibition of transcription by drugs). However, it should be mentioned that differences between half-life calculations can arise and have been described 15,34. We account for most of the problems and differences that are introduced by the stress response due to prolonged 4sU exposure. Therefore, it is indispensable to exclude the stress response introduced by 4sU-labeling. To further validate turnover rates, we recommend the use of MGCs.
Additionally, a data set as generated here could also be used for a more integrative data analysis (e.g., regulation of long non-coding RNAs)35,36.

In recent years, RNA-sequencing (RNA-seq) has become the standard tool to analyze all expressed RNAs within a cell or an organism1. However, to understand the whole process of cells adapting in response to a specific stimulus/drug, it is necessary to fully determine all underlying processes, ranging from mRNA transcription to processing, turnover, and translation. Short-term changes in RNA transcription can hardly be measured by total RNAseq, since changes of total RNA depend on factors e.g. RNA half-lives and transcriptional activity, which are a poor template for reflecting the adaptation of cells to environmental effects2,3. Indeed, a variety of new sequencing techniques have been developed that allow an analysis of the different steps in the process of gene regulation4&#160;when combined in the right manner. This protocol describes how to combine some rather easily applicable sequencing techniques that allow tracking the regulation of the essential layers of mRNA in a comparative manner. For analyzing transcriptional activity, a variety of methods have been described, such as Cap-analysis of gene expression (CAGE)5, native elongation transcript sequencing (NET-seq)6, and genome-wide nuclear run-on (GRO-seq)7,8, as well as bromouridine-sequencing (Bru-seq) and 4-thiouridine-sequencing (4sU-seq), which use metabolites that are incorporated in newly transcribed RNA9,10, just to mention a few. While CAGE identifies the exact transcription start site, NET-seq and GRO-seq deliver more accurate information about reading directions, and 4sU-seq (which is the method described here) detects only newly transcribed RNA. However, 4sU-seq is highly sensitive and can be applied in different time frames to measure quantitative transcriptional activity in actively changing cells, as well as quantitative changes in mRNA processing (which happens within minutes)9,11,12. Furthermore, 4sU-seq is ideal to combine with RNA-seq to calculate RNA turnover rates for genes9. The transcription of mRNA is carried out by RNA Polymerase II (RNAPII), which is in turn influenced by a multitude of factors, such as transcription factors, histone modifications, and general activators/repressors that can even be part of the transcriptional complex. To test how many gene/promoter/enhancer regions are bound by one factor, ChIP-seq has been developed, which is now the standard method for this purpose, due to many commercially available antibodies13. However, although ChIPseq gives clear information on where regulating factors bind, it does not reflect if it indeed leads to changes in transcription14. Therefore, performing ChIP-seq with 4sU-seq is the ideal combination for such biological questions. Regulation of gene expression can also occur at a later stage, since mRNA and protein levels do not necessarily correlate15,16, indicating potentially significant regulation on the translational or post-translational level, depending on the context. In the year 2011, ribosome profiling had been first combined with RNA-seq and is now the method of choice to quantify changes that occur rapidly in protein, since there are still some sensitivity limits with mass spectrometry17. Indeed, translation rates obtained from such methods have been shown to deliver a relatively good estimate of changes in protein levels (at least measured for long-term changes) and allow an even more detailed view on the process of translation, e.g. the determination of start-side and alternative translation frames17. The combinatorial use of all four methods can be used in steady state, between various cell types, or in a time-serial experiment of a rapidly changing cell11. This use provides a genome-wide overview of changes in transcription factor binding influencing RNA transcription, processing, and translation.

<table>
	<tbody>
		<tr>
			<td>4sU-labeling</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>4-thiouridine (100 mg)</td>
			<td>Carbosynth</td>
			<td>13957-31-8</td>
			<td>Prepare 50 mM stock in sterile H2O/PBS; store at &#8211;20&#176;C in aliquots of 50-500 &#181;l; do not refreeze.</td>
		</tr>
		<tr>
			<td>1.5 ml safe-lock tubes</td>
			<td>Eppendorf</td>
			<td>30121589</td>
			<td>Optional</td>
		</tr>
		<tr>
			<td>1.5 ml screw-top polypropylene tubes</td>
			<td>Sarstedt</td>
			<td>72692005</td>
			<td>Compatible with Dimethylformamide</td>
		</tr>
		<tr>
			<td>15 ml tubes</td>
			<td>BD Falcon</td>
			<td>352096</td>
			<td>Compatible with Dimethylformamide</td>
		</tr>
		<tr>
			<td>2.0 ml screw-top polypropylene tubes</td>
			<td>Sarstedt</td>
			<td>72694005</td>
			<td>Compatible with Dimethylformamide</td>
		</tr>
		<tr>
			<td>50 ml tubes</td>
			<td>BD Falcon</td>
			<td>352070</td>
			<td>Compatible with Dimethylformamide</td>
		</tr>
		<tr>
			<td>Agencourt RNAClean XP</td>
			<td>Beckman Coulter</td>
			<td>A63987</td>
			<td>We recommend to use these paramagnetic beads. Aliquot and store at 4&#176;C</td>
		</tr>
		<tr>
			<td>Chloroform</td>
			<td>Sigma Aldirch</td>
			<td>372978</td>
			<td>WARNING &#8211; HAZARDOUS TO HEALTH</td>
		</tr>
		<tr>
			<td>Dimethylformamide</td>
			<td>Sigma Aldrich</td>
			<td>D4551</td>
			<td></td>
		</tr>
		<tr>
			<td>Dithiothreitol (DTT)</td>
			<td>Roth</td>
			<td>6908.1</td>
			<td>Prepare as 100 mM DTT in nuclease-free H2O; always prepare fresh</td>
		</tr>
		<tr>
			<td>Ethanol</td>
			<td>Merck</td>
			<td>1.00983.1000</td>
			<td></td>
		</tr>
		<tr>
			<td>EZ-Link Biotin-HPDP (50 mg)</td>
			<td>Pierce</td>
			<td>21341</td>
			<td>Prepare 1 mg/ml stock solution by dissolving 50 mg Biotin-HPDP in 50 ml DMF. Gentle warming enhances solubilisation. Store at 4&#176;C in aliquots of 1 ml. DMF dissolves some plastic materials. We recommend to use glass pipettes to transfer DMF from ist stock glass bottle to 50 ml Falcon tubes.</td>
		</tr>
		<tr>
			<td>High Sensitivity DNA Kit</td>
			<td>Agilent Technologies</td>
			<td>5067-4626</td>
			<td></td>
		</tr>
		<tr>
			<td>Isopropanol</td>
			<td>Merck</td>
			<td>1.09634.1011</td>
			<td></td>
		</tr>
		<tr>
			<td>NaCl (5M)</td>
			<td>Sigma Aldrich</td>
			<td>71386</td>
			<td>Stock solution</td>
		</tr>
		<tr>
			<td>nuclease-free EDTA (500 mM ), pH 8.0</td>
			<td>Invitrogen</td>
			<td>15575-020</td>
			<td>Stock solution</td>
		</tr>
		<tr>
			<td>Nuclease-free H2O</td>
			<td>Sigma Aldrich</td>
			<td>W4502</td>
			<td>Stock solution</td>
		</tr>
		<tr>
			<td>nuclease-free Tris Cl (1M), pH 7.4</td>
			<td>Lonza</td>
			<td>51237</td>
			<td>Stock solution</td>
		</tr>
		<tr>
			<td>Phase Lock Gel Heavy tubes (2.0 ml)</td>
			<td>5Prime</td>
			<td>2302830</td>
			<td>Use in step 1.3.4.</td>
		</tr>
		<tr>
			<td>Polypropylene 15&#160;ml centrifuge tubes</td>
			<td>Greiner Bio-One</td>
			<td>188271</td>
			<td>Or equivalent; they have to tolerate up to 15,000 &#215; g</td>
		</tr>
		<tr>
			<td>QIAzol Lysis Reagent (200 ml)</td>
			<td>Qiagen</td>
			<td>79306</td>
			<td>Use this or equivalent TRI reagent for RNA isolation, WARNING &#8211; CORROSIVE and HAZARDOUS TO HEALTH! Ensure immediate access to Phenol antidote (PEG-Methanol)</td>
		</tr>
		<tr>
			<td>Qubit RNA HS assay kit</td>
			<td>Life Technologies</td>
			<td>Q32852</td>
			<td>Use this kit for quantifying RNA quantity in step 1.4.11</td>
		</tr>
		<tr>
			<td>RNeasy MinElute Kit</td>
			<td>Qiagen</td>
			<td>74204</td>
			<td>Optional; includes Buffer RLT</td>
		</tr>
		<tr>
			<td>Sodium citrat</td>
			<td>Sigma Aldrich</td>
			<td>C8532</td>
			<td>Prepare 1.6 M stock solution using nuclease-free water</td>
		</tr>
		<tr>
			<td>Tween 20</td>
			<td>Sigma Aldrich</td>
			<td>P1379</td>
			<td></td>
		</tr>
		<tr>
			<td>&#181;Macs Streptavidin Kit</td>
			<td>Miltenyi</td>
			<td>130-074-101</td>
			<td>Store at 4&#176;C, includes &#181;Macs columns used in step 1.4.6. (store at RT)</td>
		</tr>
		<tr>
			<td>Cell viability and stress assay</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>PE Annexin V Apoptosis Detection Kit I</td>
			<td>BD Biosciences</td>
			<td>559763</td>
			<td>Optional</td>
		</tr>
		<tr>
			<td>Thapsigargin</td>
			<td>Sigma-Aldrich</td>
			<td>T9033</td>
			<td>Optional</td>
		</tr>
		<tr>
			<td>p53</td>
			<td>abcam</td>
			<td>ab26</td>
			<td>Optional</td>
		</tr>
		<tr>
			<td>p-EIF2a (Ser51)</td>
			<td>Cell Signaling</td>
			<td>9721</td>
			<td>Optional</td>
		</tr>
		<tr>
			<td>BH3I-1</td>
			<td>Sigma-Aldrich</td>
			<td>B 8809</td>
			<td>Optional</td>
		</tr>
		<tr>
			<td>Buffers</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>4sU Washing Buffer</td>
			<td></td>
			<td>store at RT</td>
			<td>100 mM Tris pH 7.4, 10 mM EDTA, 1 M NaCl, 0.1% Tween 20 in nuclease-free H2O</td>
		</tr>
		<tr>
			<td>Biotinylation Buffer (10x)</td>
			<td></td>
			<td>store at 4 &#176;C</td>
			<td>100 mM Tris pH 7.4, 10 mM EDTA in nuclease-free water; make aliquots of 1 ml; store at 4&#176;C</td>
		</tr>
		<tr>
			<td>RNA precipitation buffer</td>
			<td></td>
			<td>store at RT</td>
			<td>1.2 M NaCl, 0.8 M sodium citrate in nuclease free water. Prepare in advance under nuclease-free conditions. Store at room temperature in 50 ml falcon tubes.</td>
		</tr>
		<tr>
			<td>Equipment</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>2100 Bioanalyzer instrument</td>
			<td>Agilent</td>
			<td>G2939BA</td>
			<td></td>
		</tr>
		<tr>
			<td>RNA 6000 Nano Kit</td>
			<td>Agilent</td>
			<td>5067-1511</td>
			<td>Use this kit to verify RNA integrity in step 1.3.10</td>
		</tr>
		<tr>
			<td>RNA 6000 Pico Kit</td>
			<td>Agilent</td>
			<td>5067-1513</td>
			<td>Optional</td>
		</tr>
		<tr>
			<td>UV/VIS spectrophotometer</td>
			<td>Thermo Scientific</td>
			<td>NanoDrop 1000</td>
			<td>Or equivalent. Use in step 1.2.2/3.1.8/3.3.3/3.4.3</td>
		</tr>
		<tr>
			<td>High-speed centrifuge</td>
			<td>Thermo Scientific</td>
			<td>Heraeus Multifuge X3R</td>
			<td rowspan="3">Or equivalent equipment capable of reaching 13,000&#160;&#215;&#160;g</td>
		</tr>
		<tr>
			<td>High-speed rotor</td>
			<td>Thermo Scientific</td>
			<td>Fiberlite F15-6 x 100y</td>
		</tr>
		<tr>
			<td>Adaptors for 15 ml tubes</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Refrigerated table-top centrifuge</td>
			<td>Eppendorf</td>
			<td>5430 R</td>
			<td>Or equivalent.</td>
		</tr>
		<tr>
			<td>Thermomixer</td>
			<td>Eppendorf</td>
			<td>Thermomixer C</td>
			<td>Or equivalent.</td>
		</tr>
		<tr>
			<td>Magnetic stand</td>
			<td>Miltenyi Biotec</td>
			<td>130-042-109</td>
			<td>One stand holds 8 &#181;Macs columns.</td>
		</tr>
		<tr>
			<td>Ultra-fine scale</td>
			<td>Mettler Toledo</td>
			<td>ML204T</td>
			<td>Or equivalent.</td>
		</tr>
		<tr>
			<td>E-Gel iBase Power System</td>
			<td>Invitrogen</td>
			<td>G6400UK</td>
			<td>For RNA gels; or equivalent.</td>
		</tr>
		<tr>
			<td>E-Gel EX 1% agarose precast gels</td>
			<td>Invitrogen</td>
			<td>G4020-01</td>
			<td>For RNA gels; or equivalent.</td>
		</tr>
		<tr>
			<td>DynaMag-2 Magnet-1 each</td>
			<td>Life Technologies</td>
			<td>12321D</td>
			<td></td>
		</tr>
		<tr>
			<td>RNaseZap</td>
			<td>Sigma</td>
			<td>R2020</td>
			<td>Optional</td>
		</tr>
		<tr>
			<td>TruSeq stranded total RNA library prep kit</td>
			<td>Illumina</td>
			<td>RS-122-2201</td>
			<td>Or equivalent. For T cells we used 400 ng 4sU and Total RNA with 11 cycles for PCR amplification. rRNA depletion is included in this kit</td>
		</tr>
		<tr>
			<td>Nanodrop</td>
			<td>Thermo Scientific</td>
			<td></td>
			<td>use a Nanodrop or equivalent instrument to measure RNA concentration</td>
		</tr>
		<tr>
			<td>Ribosome Profiling</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>TruSeq Ribo Profile kit (Mammalian or Yeast)</td>
			<td>Illumina</td>
			<td>RPYSC12116 (Yeast)</td>
			<td></td>
		</tr>
		<tr>
			<td>TruSeq Ribo Profile kit (Mammalian or Yeast)</td>
			<td>Illumina</td>
			<td>RPHMR12126 (Mammalian)</td>
			<td></td>
		</tr>
		<tr>
			<td>Illustra MicroSpin S-400 HR Columns</td>
			<td>GE Healthcare</td>
			<td>27-5140-01</td>
			<td></td>
		</tr>
		<tr>
			<td>RNA Clean &#38; Concentrator-25 kit</td>
			<td>Zymo Research</td>
			<td>R1017</td>
			<td></td>
		</tr>
		<tr>
			<td>RNA Clean &#38; Concentrator-5 kit</td>
			<td>Zymo Research</td>
			<td>R1015</td>
			<td></td>
		</tr>
		<tr>
			<td>Ribo-Zero Gold rRNA Removal Kit (Human/Mouse/Rat)</td>
			<td>Illumina</td>
			<td>MRZG126 or MRZG12324</td>
			<td></td>
		</tr>
		<tr>
			<td>(High Sensitivity DNA Kit)</td>
			<td>Agilent Technologies</td>
			<td>5067-4626</td>
			<td>Already needed for 4sU-seq</td>
		</tr>
		<tr>
			<td>All other consumables and equipment are listed in the User guide</td>
			<td>!!!</td>
			<td></td>
			<td>Carefully read the user guide and order required consumables in advance (consider a long delivery time for some consumables e.g. gels)</td>
		</tr>
		<tr>
			<td>ChIP</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>10 mM Tris-HCl (pH 8.0)</td>
			<td>gereral lab supplier</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>100 bp Plus Marker</td>
			<td>Thermo Fisher</td>
			<td>SM0323</td>
			<td></td>
		</tr>
		<tr>
			<td>16 % Formaldehyde</td>
			<td>Thermo Fisher</td>
			<td>28908</td>
			<td>Add to a final concentration of 1 %</td>
		</tr>
		<tr>
			<td>70% EtOH</td>
			<td>gereral lab supplier</td>
			<td></td>
			<td>Always prepare fresh</td>
		</tr>
		<tr>
			<td>Agarose</td>
			<td>gereral lab supplier</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Agencourt RNAClean XP beads</td>
			<td>Beckman Coulter</td>
			<td>A63987</td>
			<td>We recommend to use these paramagnetic beads. Aliquot and store at 4&#176;C</td>
		</tr>
		<tr>
			<td>ChIP library preparation kit</td>
			<td>KapaBiosystems</td>
			<td>KK8504</td>
			<td>Or use the kit of your choice</td>
		</tr>
		<tr>
			<td>DNA low bind microcentrifuge tubes</td>
			<td>Eppendorf</td>
			<td>Z666548-250EA</td>
			<td>or equivalent</td>
		</tr>
		<tr>
			<td>Dynabeads Protein G</td>
			<td>Invitrogen</td>
			<td>10004D</td>
			<td>Use these superparamagnetic beads coupled to protein G in step 4.3.1.; Bring to RT before use</td>
		</tr>
		<tr>
			<td>Glycine</td>
			<td>gereral lab supplier</td>
			<td></td>
			<td>Prepare a 2M stock solution</td>
		</tr>
		<tr>
			<td>Glycogen</td>
			<td>Roche</td>
			<td>10-901-393-001</td>
			<td></td>
		</tr>
		<tr>
			<td>MinElute PCR Purification Kit</td>
			<td>Qiagen</td>
			<td>28004</td>
			<td>Use this kit (or equivalent) to purify chromatin in step 4.2.4.</td>
		</tr>
		<tr>
			<td>Phosphatase Inhibitor (PhosStop)</td>
			<td>Roche</td>
			<td>4906837001</td>
			<td>Add freshly to the buffer and keep on ice</td>
		</tr>
		<tr>
			<td>Power SYBRgreen Master mix</td>
			<td>Thermo Fisher</td>
			<td>4367659</td>
			<td></td>
		</tr>
		<tr>
			<td>Protease Inhibitor (cOmplete, EDTA-free)</td>
			<td>Roche</td>
			<td>11873580001</td>
			<td>Add freshly to the buffer and keep on ice</td>
		</tr>
		<tr>
			<td>Proteinase K</td>
			<td>Invitrogen</td>
			<td>25530049</td>
			<td></td>
		</tr>
		<tr>
			<td>Qubit dsDNA HS Assay kit</td>
			<td>Invitrogen</td>
			<td>Q32851</td>
			<td>Use this kit for quantifying DNA quantity in step 4.6.4. on a Qubit Fluorometer</td>
		</tr>
		<tr>
			<td>Rnase, DNase free</td>
			<td>Roche</td>
			<td>11-119915001</td>
			<td></td>
		</tr>
		<tr>
			<td>Salmon sperm (sonicated to around 100bp)</td>
			<td>Sigma</td>
			<td>D1626</td>
			<td></td>
		</tr>
		<tr>
			<td>TE pH 8.0</td>
			<td>gereral lab supplier</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Antibodies (ChIP grade if possible)</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>anti-RNA Pol II [8WG16]</td>
			<td>abcam</td>
			<td>ab817</td>
			<td></td>
		</tr>
		<tr>
			<td>anti-Histon H3K36me3</td>
			<td>abcam</td>
			<td>ab9050</td>
			<td></td>
		</tr>
		<tr>
			<td>or antibody of interest</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Buffers</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Binding/Blocking buffer</td>
			<td></td>
			<td>Store at RT</td>
			<td>PBS with 0.5 % BSA and 0.5 % Tween 20</td>
		</tr>
		<tr>
			<td>Cell-Lysis buffer</td>
			<td></td>
			<td>Store at RT</td>
			<td>5 mM Pipes [pH 8.0], 85 mM KCl, and 0.5 % NP40</td>
		</tr>
		<tr>
			<td>ChIP IP buffer</td>
			<td></td>
			<td>Store at RT</td>
			<td>0.01 % SDS; 1. 1% Triton X-100;1.2&#160;mM EDTA; 16.7&#160;mM Tris-HCl, pH 8.1; 16.7&#160;mM NaCl</td>
		</tr>
		<tr>
			<td>Elution buffer</td>
			<td></td>
			<td>Store at RT up to 6 months</td>
			<td>10 mM Tris-HCl (pH 8.0), 5 mM EDTA (pH 8.0), 300 mM NaCl and 0.5 % SDS</td>
		</tr>
		<tr>
			<td>Nuclei-Lysis buffer</td>
			<td></td>
			<td>Store at RT</td>
			<td>50 mM Tris [pH 8.0], 10 mM EDTA, and 1 % SDS</td>
		</tr>
		<tr>
			<td>Wash buffer I</td>
			<td></td>
			<td>Store at RT</td>
			<td>0.1 % SDS; 1 % Triton X-100; 2 mM EDTA; 20mM Tris-HCL pH 8.1; 150 mM NaCl</td>
		</tr>
		<tr>
			<td>Wash buffer II</td>
			<td></td>
			<td>Store at RT</td>
			<td>0.1 % SDS; 1 % Triton X-100; 2&#160;mM EDTA; 20&#160;mM Tris-HCL pH 8.1; 500&#160;mM NaCl</td>
		</tr>
		<tr>
			<td>Wash buffer III</td>
			<td></td>
			<td>Store at RT</td>
			<td>0.25&#160;M LiCl; 1% NP-40; 1&#160;mM EDTA; 10&#160;mM Tris-HCl, pH 8.1</td>
		</tr>
		<tr>
			<td>Equipment</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>2100 Bioanalyzer instrument</td>
			<td>Agilent</td>
			<td>G2939BA</td>
			<td>use this instrument for electrophoretical analysis</td>
		</tr>
		<tr>
			<td>Nanodrop</td>
			<td>Thermo Scientific</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Bioruptor TBX microtubes 1.5 ml</td>
			<td>Diagenode</td>
			<td>C30010010</td>
			<td></td>
		</tr>
		<tr>
			<td>or tubes special for your sonication device</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Bioruptor sonication device or sonication device of your choice</td>
			<td></td>
			<td></td>
			<td>Sonication of T cells with Bioruptor: 20 - 25 cycles (30 s on, 30 s off at high in two 1.5 ml bioruptor microtubes with 500 &#181;l each tube)</td>
		</tr>
		<tr>
			<td>Magnetic stand for tubes</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Thermomixer</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Agarose gel electrophoresis</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Qubit Fluorometer</td>
			<td>Thermo Scientific</td>
			<td></td>
			<td>Use this Fluorometer for quantifying low amounts of RNA/DNA</td>
		</tr>
	</tbody>
</table>

real-time analysis of transcription factor binding, transcription, translation, and turnover to display global events during cellular activation

Upon activation, cells rapidly change their functional programs and, thereby, their gene expression profile. Massive changes in gene expression occur, for example, during cellular differentiation, morphogenesis, and functional stimulation (such as activation of immune cells), or after exposure to drugs and other factors from the local environment. Depending on the stimulus and cell type, these changes occur rapidly and at any possible level of gene regulation. Displaying all molecular processes of a responding cell to a certain type of stimulus/drug is one of the hardest tasks in molecular biology. Here, we describe a protocol that enables the simultaneous analysis of multiple layers of gene regulation. We compare, in particular, transcription factor binding (Chromatin-immunoprecipitation-sequencing (ChIP-seq)), de novo transcription (4-thiouridine-sequencing (4sU-seq)), mRNA processing, and turnover as well as translation (ribosome profiling). By combining these methods, it is possible to display a detailed and genome-wide course of action.
Sequencing newly transcribed RNA is especially recommended when analyzing rapidly adapting or changing systems, since this depicts the transcriptional activity of all genes during the time of 4sU exposure (irrespective of whether they are up- or downregulated). The combinatorial use of total RNA-seq and ribosome profiling additionally allows the calculation of RNA turnover and translation rates. Bioinformatic analysis of high-throughput sequencing results allows for many means for analysis and interpretation of the data. The generated data also enables tracking co-transcriptional and alternative splicing, just to mention a few possible outcomes.
The combined approach described here can be applied for different model organisms or cell types, including primary cells. Furthermore, we provide detailed protocols for each method used, including quality controls, and discuss potential problems and pitfalls.

4sU labeling: Verify optimal 4sU-labeling conditions (apoptosis, nuclear stress, cytoplasmic stress), time, and concentration: High levels of 4sU can inhibit the production and processing of rRNA and induce cytoplasmic as well as nuclear stress30. Therefore, cells of interest should be tested for 4sU-induced stress as well as apoptosis. Western blot analysis is recommended for visualizing p53 accumulation, which indicates nuclear stress, increasing phospho-EIF2a levels which display cytoplasmic stress and fluorescence-activated cell sorting (FACS) analysis for apoptosis. High levels and lengthy exposure to 4sU or drugs like thapsigargin or arsenite can be used to induce cellular stress. To induce apoptosis or cell death, cells were treated with BH3I-1 (500 ng/&#181;L) or incubated for 5 min at 95 &#176;C (heat shock). Annexin V/7-AAD staining was used to determine apoptotic (Annexin V) and dead (7-AAD) cells. Labeling of in vitro generated primary Th1 cells for 0.5 h with 500 &#181;M 4sU (final concentration) or 1 h with 200 &#181;M 4sU neither induces signs of cellular stress nor apoptosis (Figure 1) but lead to sufficient 4sU incorporation.
RNA labeling time can also be shortened (&#8804;5 min) which leads to an increase in short-lived intronic sequences compared to longer labeling times. To visualize co-transcriptional splicing rates, 4sU-labeling times should not exceed 30 min. For further details regarding 4sUlabeling, please refer to R&#228;dle et al.19
Quality Control: RNA integrity is of great importance when processing RNA. It is most convenient to check the RNA quality of 4sU-labeled RNA after biotinylation by electrophoretical analysis (see Table of Materials). Consider verifying isolated RNA from step 2.2.2, especially when using it for sequencing of total RNA. RNA integrity number (RIN) should be &#8805;8 to ensure RNA integrity for further processing (Figure 3).
Electrophoretical analysis can also be used to verify newly transcribed RNA. Be aware that newly transcribed RNA contains significantly less mature rRNAs compared to total RNA with the typical rRNA bands being much less prominent.
Ribosome profiling: PCR amplification of the cDNA library: cDNA amplification (step 4.9.1) is a critical step to ensure good sequencing results. Analyze amplified libraries by electrophoretical analysis. A good sample of amplified libraries shows a peak around 140 - 160 bp (Figure 4A). Excessive amounts of adapter dimers should be avoided (Figure 4B) and those samples should be further purified using the PAGE purification procedure according to the manufacturer&#39;s protocol (PAGE purification of PCR products). Too much template or too many PCR cycles can result in over-amplification characterized by the appearance of higher-than-expected molecular weight bands, smeared PCR products, and adapter dimer products (Figure 4C). For most samples 1 - 5 &#181;L of circularized cDNA and 9 PCR cycles for amplification will typically yield sufficient amounts of the correct PCR product.
ChIP: Chromatin shearing: Optimal shearing conditions need to be adjusted for each type of cell. Determine shearing conditions (e.g., number of cycles, high or low power) in advance. Use the same number of cells and the same volume for testing purposes, since a lower cell density increases the shearing efficiency. Try to avoid over- or under-shearing the chromatin. Large chromatin fragments can dramatically affect ChIP results by clogging, and over-shearing can destroy epitopes on the protein of interest, leading to a lower binding efficiency by the antibody. In this experiment, the best results were achieved when the main fraction of the sheared chromatin was around 1,000 bp or slightly lower (Figure 5A).
Verifying ChIP by qPCR: Before starting the ChIP, it is advisable to test if the used antibody is suitable for ChIP (if possible, use ChIP grade antibodies) by ChIP-qPCR. Verify the ChIP for sequencing by qPCR before starting the library preparation (see step 5.6.5). Design primers that bind to a known target site of the protein of interest. If the exact target site within a gene is unknown, several primer pairs can be used to scan the gene and associated regulatory elements. For RNAPII ChIP of Th1 cells Ifng, which is transcriptionally upregulated upon stimulation, and actin primers can be used as a positive control. Sox9&#160;and insulin serve as a negative control, since these genes are not expressed in Th1 cells (Figure 5B). Remember not to use exon-spanning primers, which are normally used for qPCR of mRNA. An IgG control can also be used to prove specificity of the used antibody. Immunoprecipitated DNA can be measured with a suitable fluorometer (see Table of Materials). Amounts of nonspecifically bound DNA by the IgG control should be significantly lower compared to the DNA amount bound by the antibody of interest.
Replicates: proof of biological significance: It is strongly advised to perform the kinetic experiment for all methods starting from the same pool of cells to ensure cells have the same identity for all untreated and treated samples (Figure 2). Nevertheless, it is recommended to take small aliquots of main time points for each method to compare samples to a biological replicate (e.g., by qPCR, FACS analysis). This allows for a rough estimation if the treatment for both replicates was reproducible and you could proceed with sequencing. Validation of the replicates should be performed by means of bioinformatical analysis. Reproducibility of results can be assessed in terms of correlation between FPKM values between replicates and visualized using scatter plots (Figure 6).
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/56752/56752fig1.jpg" /> 
Figure 1: Verification of optimal 4sU-labeling conditions without perturbing cell physiology (Figure from Davari et al.11) 
(A) Detection of cell apoptosis by FACS analysis: In vitro generated Th0 cells were treated with different concentrations of 4sU (indicated in brackets) for 0.5 h, 1 h, and 2 h, respectively. BH3I-1 treatment was used to induce apoptosis determined by Annexin V, whereas heat shock (5 min at 95 &#176;C) was used to induce cell death determined by 7-AAD. (B) Western blot analysis for p53 of 4sU treated and activated T cells: samples were labeled with 200 &#181;M 4sU for the indicated time of activation, except the 0.5 h time point that was labeled with 500 &#181;M 4sU. (C) Western blot analysis of phospho-EIF2a and total EIF2a in activated Th1 cells with the same labeling conditions as in (B). Thapsigargin was used as a positive control. <a href="http://cloudflare.jove.com/files/ftp_upload/56752/56752fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/56752/56752fig2.jpg" /> 
Figure 2: Schematic overview of a kinetic setup to track genome-wide changes 
This scheme illustrates the setup for combining 4sU-seq, total RNA-seq, Ribosome Profiling, and ChIP-seq to study genome-wide changes upon cell treatment. Pool cells and set aside the required number of cells for untreated control. Treat remaining cells and split for each method and time point. Label untreated/treated cells for 4sU-seq with 4sU as described. Time points and samples for each method depend on the specific biological question being examined. Take samples for each time point and method, and follow the dedicated part of the protocol. <a href="http://cloudflare.jove.com/files/ftp_upload/56752/56752fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/56752/56752fig3.jpg" /> 
Figure 3: Quality control of 4sU-labeled RNA 
Total RNA and biotinylated RNA obtained from activated Th1 cells were analyzed on a Bioanalyzer. 18S rRNA and 28S rRNA are shown and RNA integrity number (RIN) is given by the instrument to determine integrity of the RNA. RIN should be &#8805;8 to ensure RNA integrity. <a href="http://cloudflare.jove.com/files/ftp_upload/56752/56752fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/56752/56752fig4.jpg" /> 
Figure 4: Bioanalyzer profiles of ribosome profiling libraries 
(A) A good library: The sample shows a peak at the expected size range (140 - 160 bp) and no further purification is needed. (B) This sample shows excessive adapter dimer amplified product (120 bp) relative to the desired product (140 - 160 bp). This library requires further purification. (C) An over-amplified sample: Higher-than-expected molecular weight peaks and smeared PCR amplicons are visible (indicated by arrows). <a href="http://cloudflare.jove.com/files/ftp_upload/56752/56752fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/56752/56752fig5.jpg" /> 
Figure 5: Optimal chromatin size after shearing and verification of ChIP by qPCR 
(A) Agarose gel picture shows the optimal fragment size of the sheared chromatin from three samples that were sheared for 25 cycles on a sonicator and purified as described before in the protocol. (B) Q-PCR results of a total RNAPII ChIP (anti-RNA Pol II, 8WG16, ab817) is represented as a percentage of input. Ifng and actin primers were used as a positive while Sox9&#160;and Insulin are negative controls (both genes are not expressed in activated Th1 cells). <a href="http://cloudflare.jove.com/files/ftp_upload/56752/56752fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/56752/56752fig6.jpg" /> 
Figure 6: Comparison of biological replicates (Figure from Davari et al. 11) 
Representative scatter plot comparing expression values (FPKM) between replicates of newly transcribed (4sU) RNA 4 h after stimulation of activated Th1 cells. The green line indicates equal FPKM values and rank correlation is indicated in each plot.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Duration of labeling (min)</td>
			<td>Recommended 4sU concentration (&#181;M)</td>
		</tr>
		<tr>
			<td>120</td>
			<td>100 - 200</td>
		</tr>
		<tr>
			<td>60</td>
			<td>200 - 500</td>
		</tr>
		<tr>
			<td>15 - 30</td>
			<td>500 - 1000</td>
		</tr>
		<tr>
			<td>&#60;10</td>
			<td>500 - 2000</td>
		</tr>
	</tbody>
</table>
Table 1: Recommended 4sU concentrations (from R&#228;dle, et al.19) 
The range of recommended 4sU concentrations is indicated for different times of labeling.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Method</td>
			<td>Cell number</td>
			<td>RNA amount</td>
		</tr>
		<tr>
			<td>4sU-labeling</td>
			<td>&#8805;2 x 107</td>
			<td>&#8805;60&#181;g</td>
		</tr>
		<tr>
			<td>Ribosome profiling</td>
			<td>&#8805;2 x107</td>
			<td></td>
		</tr>
		<tr>
			<td>ChIP-seq</td>
			<td>&#8805;2 x 107&#160;- 3 x 107</td>
			<td></td>
		</tr>
	</tbody>
</table>
Table 2: Required amount of primary T cells 
Minimum amount of required primary T cells for each method. Amounts can be less when using other cell types.

Watch this Scientific Journal Video about Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation at JoVE.com

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation

This protocol describes the combinatorial use of ChIP-seq, 4sU-seq, total RNA-seq, and ribosome profiling for cell lines and primary cells. It enables tracking changes in transcription-factor binding, de novo transcription, RNA processing, turnover and translation over time, and displaying the overall course of events in activated and/or rapidly changing cells.

Upon activation, cells rapidly change their functional programs and, thereby, their gene expression profile. Massive changes in gene expression occur, for ...

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