This article explores the advancements made in ChIP-seq analysis with small samples, which include ChIP-seq using limited amounts of samples, optimizing amplification for small ChIP samples and reducing samples required for the ChIP-seq analysis.
Heterogeneity exists in many other cell types, including tumor cells. As a result, scientists continue to explore different experimental methods that enable small and homogeneous samples to be analyzed in efficiently.
Earlier in 2007, ChIP-seq revolutionized epigenetic analysis. It provided significant advantages such as higher resolution, fewer artifacts, wider genome coverage, and considerable reductions in the cost per interaction profiled.
Despite this fact, it needed a large amount of input sample (about 10 million cells) (Barski et al, 2007), but such large amounts of material are difficult to obtain, particularly when researching specific sub-populations, cell-types, or when trying to use clinical samples. The good news is that several enhancements have been made to the pre-amplification methods, ChIP methodology, and sequencing library construction reagents that make it more viable to work with small amounts of sample.
At present, it has become a fairly routine process to run detailed ChIP-seq experiments with 1 million cells, but groups strive to push technological limitation in order to extract even better performance. This article discusses a number of latest developments that continue to lower the sample input for ChIP sequencing analyses.
N-ChIP shines with limited samples
ChIP-seq that uses a limited number of cells poses a challenge because the recovered immunoprecipitated DNA does not have increased complexity, which may negatively impact both reproducibility and sensitivity. As a result, immunoprecipitation techniques are required that are optimized for low input settings.
Promising results have been obtained in the attempts to create low cell ChIP-seq protocols with the more standard, formaldehyde cross-linked chromatin (X-ChIP). ChIP-seq was effectively carried out from 1 million human stem cells (Hitchler et al, 2011) using standard Illumina library prep protocols.
Conversely, X-ChIP is more suitable for studying chromatin associated proteins or weakly binding transcription factors but becomes less effective due to the cross-linking procedure when a limited amount of sample material is used. In order to overcome those shortcomings, certain researchers have turned to Native ChIP (N-ChIP) techniques.
This is because with N-ChIP techniques, cross-linking is not required and as a result reduced non-specific interactions and better resolution are realized when compared to X-ChIP methods (O’Neil et al, 2003). This can present a significant benefit when researchers are trying to work with small numbers of cells.
Of late, a highly optimized N-ChIP technique was applied to genome-wide analysis using ChIP-seq (Gilfillan et al, 2012) and this showed extremely reliable results using 100,000 cells for each immunoprecipitation (IP). Being a low input oriented method, the N-ChIP implemented several tweaks to the usual immunoprecipitation protocol.
In this method, the chromatin is diluted in a concentrated IP buffer but the dialysis step is not performed which reduces handling as well as sample loss. A specialized sonication step is then added using TPX plastic ware which reduces both contamination and sample loss and also assures unbiased, consistent fragmentation.
Then, in order to visualize the small amounts, the subsequent MNase digestion is tracked using an Agilent 2100 Bioanalyzer. Following digestion, an adjustment was made to the Illumina library construction to capture nucleosome-sized fragments on the basis of size selection. Lastly, column-based cleanup was swapped out with SPRI-beads for better retention of DNA at each step.
While the optimized N-ChIP needs more cells when compared to some other techniques, it reduces the need for amplification and is especially useful when studying histone modifications across the genome. According to researchers, additional improvements can be realized by improving the robustness and efficiency of DNA purification, immunoprecipitation, and sequencing library construction protocols.
Optimizing amplification for small ChIP samples
After chromatin immunprecipitation, amplification of the ChIP’ed material is the next stage in the process that is ready for optimization. Traditional library preparation procedures are associated with sample loss. These procedures are used for making ChIP DNA that is ready for next-generation sequencing but they also involve a number of purifications and enzymatic steps, which are highly inefficient and may lead to sample loss.
The sample recovery from ChIP is also extremely low, especially if the input sample headed for the ChIP reaction is small. Hence, sufficient material should be obtained from the ChIP reaction for the following sequencing library preparation. In such cases, sample amplification may need to be done before library construction to assure the availability of sufficient material.
This is accomplished by using the following methods while minimizing the biases which are inherent in the amplification of nucleic acids (Ponzielli et al, 2008), in the subsequent analysis of ChIP-seq data.
Using alternative, amplification-based approaches that deploy primer extension or linear amplification followed by PCR before proceeding with the library generation, optimized methods have been able to considerably lower the input cell requirements for ChIP-seq analysis to just 5,000-10,000 cells. (Adli et al, 2010 and Shankaranarayanan et al, 2011):
The amplification method, Nano-ChIP-seq (Adli et al, 2010), was devised to function with rare cell types in particular. Using a three-step process, nano-ChIP-seq generates a ChIP-seq library from just 10,000 cells. A random hairpin primer is initially utilized and then an exonuclease digestion step is performed that produces an amplified sample from small initial amounts of ChIP DNA.
Non-specific products are also reduced by this process. In the next stage, using optimized additives, PCR enzymes, and cycling conditions, high fidelity amplification of ChIP DNA is realized while maintaining an accurate representation of GC-rich sequences.
Amplified DNA is finally digested at BciVI sites, which are located close to the ends of the ChIP fragments. The digestion of amplified DNA produces double-stranded DNA products with 3′ A overhangs that are suited for direct ligation to Illumina adapters before sequencing.
Linear DNA amplification methods are used by the LinDA protocol (Shankaranarayanan et al, 2011) to increase the amount of DNA available following the ChIP protocol. Just 30 picograms of chromatin immunoprecipitated DNA, which is the equivalent of 5,000 to 10,000 cells, is enough to initiate the LinDA protocol and achieve genome-wide ChIP-seq analysis of chromatin-associated proteins and transcription factors. Other key features of the LinDA protocol include:
- LinDA is fully compatible with next generation sequencing, unlike previous low cell number ChIP protocols
- Minimum number of PCR cycles and ligation steps reduces the number of potential artifacts introduced
- It is compared to other T7 procedures devised for small amounts of input DNA, because the whole reaction is performed using just a single buffer inside a single tube
Going lower with ChIP sequencing
New advances in next-generation sequencing library preparation techniques, pre-amplification techniques, and ChIP protocols have significantly lowered the minimum sample amount required for effective ChIP sequencing, from the vicinity of 10 million cells to down to 5,000 or 10,000 cells.
While this indicates a marked improvement, the research community aims to ultimately study a single cell or even a single molecule of DNA. Considering the major advances made thus far, single cell analysis could well become a technological breakthrough within the next few years.
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