Here we describe a protocol for efficient chromatin immunoprecipitation (ChIP) followed by high-throughput DNA sequencing (ChIP-seq) of brown adipose tissue (BAT) isolated from a mouse. This protocol is suitable for both mapping histone modifications and investigating genome-wide localization of non-histone proteins of interest in vivo.
Most cellular processes are regulated by transcriptional modulation of specific gene programs. Such modulation is achieved through the combined actions of a wide range of transcription factors (TFs) and cofactors mediating transcriptional activation or repression via changes in chromatin structure. Chromatin immunoprecipitation (ChIP) is a useful molecular biology approach for mapping histone modifications and profiling transcription factors/cofactors binding to DNA, thus providing a snapshot of the dynamic nuclear changes occurring during different biological processes.
To study transcriptional regulation in adipose tissue, samples derived from in vitro cell cultures of immortalized or primary cell lines are often favored in ChIP assays because of the abundance of starting material and reduced biological variability. However, these models represent a limited snapshot of the actual chromatin state in living organisms. Thus, there is a critical need for optimized protocols to perform ChIP on adipose tissue samples derived from animal models.
Here we describe a protocol for efficient ChIP-seq of both histone modifications and non-histone proteins in brown adipose tissue (BAT) isolated from a mouse. The protocol is optimized for investigating genome-wide localization of proteins of interest and epigenetic markers in the BAT, which is a morphologically and physiologically distinct tissue amongst fat depots.
While white adipose tissue (WAT) is specialized for energy storage, brown adipose tissue (BAT) dissipates energy in the form of heat due to its ability to convert carbohydrates and lipids into thermal energy via mitochondrial uncoupling1. Because of this specialized function, the BAT depot is required for maintenance of body temperature in physiological conditions and in response to cold exposure. While gene expression changes during BAT differentiation and upon thermogenic stress have been extensively studied in vivo and in vitro, the molecular mechanisms underlying these changes have been mostly dissected in immortalized cell lines and primary pre-adipocytes, with the exception of several in vivo studies2,3,4,5.
Regulation of specific gene expression programs through transcriptional regulation is achieved by coordinated changes in chromatin structure via various transcription factors and co-factors actions. Chromatin immunoprecipitation (ChIP) is a valuable molecular biology approach for investigating the recruitment of these factors to DNA and for profiling the associated changes in the chromatin landscape. Key factors for the success of ChIP experiments include optimizations of crosslinking conditions and chromatin shearing consistency throughout different samples, availability of adequate starting material, and, most notably, quality of the antibodies. When performing ChIP from whole tissues, it is also important to consider heterogeneity of the samples and optimize the protocol to improve efficiency of nuclei isolation, with the latter being a particularly sensitive step when working with adipose tissue due to the elevated lipid content. In fact, molecular isolation techniques from whole adipose depots are complicated by the presence of high levels of triglycerides, and protocols must be optimized to increase the amount of chromatin isolation. Finally, when high-throughput sequencing is performed after ChIP-DNA isolation, the sequencing depth is critical for determining the number of peaks that are confidently detected.
Here, we refer to the working standards and general guidelines for ChIP-seq experiments recommended by the ENCODE and modENCODE consortia6 for best practices, and we focus on a step-by-step description of a protocol optimized for ChIP-seq from BAT. The described protocol allows for efficient isolation of chromatin from adipose tissue to perform genome-wide sequencing for DNA-binding factors with well-defined peaks as well as histone marks with more diffuse signals.
The animal handling steps of the protocol have been approved by Boston University’s Institutional Animal Care and Use Committee (IACUC).
1. Day 1: Dissection and Preparation of BAT for Chromatin Immunoprecipitation (ChIP)
2. Day 2: Collection of the Immune Complexes
3. Day 3: Recovery of DNA with Phenol/Chloroform Extraction
4. Analysis of ChIP using qPCR (Single/Multiple Genes Readout)
5. Amplification of DNA from ChIP for High-throughput Sequencing (Genome-wide Readout)
NOTE: This step can be outsourced to an academic core facility or commercial sequencing company when sequencing capabilities are not available in-house.
6. Raw Data Analysis
Figure 1: ChIP validation by qPCR. ChIP-qPCR analysis of representative GPS2 target genes NDUFV1 (left) and TOMM20 (right) in the BAT of WT and GPS2-AKO mice, showing relative changes in the level of H3K9 methylation and GPS2 and Pol2 binding. The bar graphs represent the sample mean of 3 replicates with *p < 0.05 and **p < 0.01 as calculated with Student's t-test. This figure is modified from Cardamone et al.2. Please click here to view a larger version of this figure.
Examples of ChIP-qPCR using BAT isolated from WT or GPS2-AKO mice are shown in Figure 12. Having found that GPS2 was required for the expression of nuclear-encoded mitochondrial genes in different cell lines2, we tested the recruitment of GPS2 on two specific nuclear-encoded mitochondrial genes, NDUFV1 and TOMM20, in BAT from mice as an example of a tissue highly enriched in mitochondria. We first compared GPS2 promoter occupancy in GPS2-AKO mice and wild-type littermates, observing an expected decrease in GPS2 binding on selective target genes in the BAT from GPS2-AKO mice . Using the protocol described here, we also recorded increased binding of RNA polymerase 2 (Pol2) and the repressive histone mark H3K9me3 in the BAT from GPS2-AKO mice as compared to wild-type littermates. For all antibodies, the binding was significant as compared to the background signal observed in the IgG control sample. These results confirm the recruitment of GPS2 on selected nuclear-encoded mitochondrial genes and show that GPS2 is required for preventing the accumulation of H3K9me3, and thus required for the stalling of Pol2 transcriptional activity on target promoters. See the Table of Materials for more details on the antibodies and the original publication for additional data and more comprehensive discussion of these results2.
Figure 2: Plot of quality scores from raw sequencing reads isolated from BAT. (A) Quality scores reflect a prediction of the probability of an error during base-calling. It is commonly expressed as an integer value, Q = -10log10(P), in which P is the probability of an error in base-calling. Shown above is a per base sequence quality plot generated by FastQC based on raw, unprocessed sequencing reads generated from BAT. (B) GC content distribution of reads after adapter removal and read trimming from BAT samples. GC content should roughly resemble a normal distribution with a peak centered around the species' actual fraction of GC genomic content. Please click here to view a larger version of this figure.
In Figure 2, sequencing quality scores are shown at a per base level, and reads may be further processed by trimming any residual adapter contamination and removing reads where the average quality score across a sliding window falls below a specified threshold. Also shown is the GC content distribution across reads after adapter removal and read trimming. Sequence quality and GC content distribution are two widely used metrics to evaluate next generation sequencing data before computational analyses are performed. These results demonstrate that the protocol produces a sufficient amount of high-quality chromatin isolated from BAT that is compatible with downstream next-generation sequencing technologies.
Figure 3: Normalized bigwig files generated from ChIP-seq data from the BAT of WT and GPS2-AKO mice. This figure shows the normalized read coverage along the Slc25a25 gene locus with a significantly called peak in the promoter region. GPS2 was shown to regulate the expression of nuclear-encoded mitochondrial genes by altering the chromatin state of target gene promoters. These results display the visualization of a significantly called peak on a representative nuclear-encoded mitochondrial gene. Please click here to view a larger version of this figure.
Shown in Figure 3 are bigWig tracks of the WT and GPS2-AKO aligned BAM files normalized to 1x depth (reads per genome coverage) as implemented in deepTools. Shown is the presence of a statistically significant peak located in the promoter region of the mitochondrial gene Slc25a25. The normalized tracks allow visualization of the enrichment of reads corresponding to the called peak and the reduction of reads at this location in the BAT of GPS2-AKO mice relative to wild-type littermates.
The protocol described here represents a valuable tool for performing ChIP from murine tissues, specifically optimized for brown adipose tissue. One of the greater challenges in performing ChIP from tissue is recovering a sufficient number of cells during sample preparation. Shearing the BAT using a tissue homogenizer blender coupled with stainless steel beads instead of a canonical glass pestle significantly reduces the number of cells lost due to unbroken tissue. Moreover, homogenizing the tissue directly in a hypotonic buffer helps the release of lipids that can then be easily separated and removed from the nuclei via high-speed centrifugation.
Proper sonication is also critical for performing consistent and reproducible ChIP assays. The use of a water bath ultra-sonicator allows for the simultaneous processing of multiple samples, thus improving reproducibility of chromatin shearing and reducing the risk of sample cross-contamination. In addition, use of a temperature-controlled sonication system reduces overheating of the samples, which should be avoided to prevent sample degradation and loss of epitope recognition by the antibody (see Table of Materials for details).
Another challenging step is the recovery of immunoprecipitated complexes. Magnetic beads are often preferred for this step because they allow for faster and more effective washes when used together with a magnetic rack. However, they have a lower rate of DNA recovery compared to Protein A Agarose, which can be a serious limitation when working with small amount of starting material. We find that the combination of Protein A Agarose slurry with PVDF 0.45 µm centrifugal filter columns is a great solution to achieve maximum DNA yield with minimal washing time and higher reproducibility.
Regarding the DNA isolation, plenty of columns-based DNA isolation kits can be used. In our experience, one limitation of this approach is the capacity of the columns to have an effect on the yield of DNA recovery. To overcome the problem, we prefer using a more traditional method as phenol/chloroform for DNA extraction.
The listed ChIP-seq pipeline incorporates a number of widely accepted tools and utilities for next generation sequencing experiments. Briefly, the reads are subjected to basic quality control using FastQC and Trimmomatic, then aligned to the mouse MM10 genome using Bowtie2. Surviving reads are filtered by mapping quality before being used for peak calling through the MACS2 algorithm. However, it should be noted that other available and validated tools may also be used depending on the nature of the experiment and data being generated. The use of any customized parameters during pre-processing, alignment, or peak calling may also be appropriate.
Bullet Blender Tissue Homogenizer | Next Advence | BBX24 | |
Stainless Steel Beads 3.2mm Diameter | Next Advence | SSB32 | |
Bioruptor Sonicator | Diagenode | ||
1.5 ml Micro Tube TPX Plastic | Diagenode | C30010010-5 | |
Complete-Protease inhibitor | Roche | 11836145001 | |
Protein A Agarose Slurry | Invitrogen | 101041 | |
GPS2 antibody | In house | Rabbit polyclonal, Ct antibody (Cardamone et al., Mol Cell 2018) | |
Pol2 antibody | Diagenode | C15100055 | |
h3K9me3 antibody | Millipore | 05-1242 | |
Fast Syber Green Master Mix | Aplied Biosytem | 4385612 | |
ViiA7 | Aplied Biosytem | ||
TruSeq ChIP Library Preparation Kit | Illumina | IP-202-1012 | |
HiSeq 2000 | Illumina |