Jeffrey Perkel has been a scientific writer and editor since 2000. He holds a PhD in Cell and Molecular Biology from the University of Pennsylvania, and did postdoctoral work at the University of Pennsylvania and at Harvard Medical School.
By now, almost every researcher knows the recipe, more or less, for making induced pluripotent stem cells (iPSCs). Take somatic cells, add four transcription factors, wait a few weeks and voila! Pluripotency: unlocked.
Precisely what occurs under the cellular hood to effect that change, though, has proven to be a tougher nut to crack. Clearly, epigenetics are involved: transitioning from fibroblasts to iPSCs means genes that once were off must be started up again. Other genes, hallmarks of cellular differentiation, must be dialed down.
“The genome is pretty much the same in every cell,” notes Andras Nagy, a senior scientist at the Mount Sinai Hospital Lunenfeld-Tanenbaum Research Institute in Toronto. “The epigenome specifies what genes are expressed, and what proteins are made.”
Such changes reflect multiple variables operating on genomic scales and changing over time, including DNA methylation, chromatin modification, the expression of long noncoding RNAs and more.
The general term for such changes is “chromatin dynamics,” and they are crucial in everything from cellular differentiation and organismal development to cancer.
“Chromatin dynamics refers to the remodeling and/or placement and removal of modifications to proteins associated with chromatin,” says John Rosenfeld, a platform technology manager at EMD Millipore.
In essence, chromatin-dynamics studies are simply epigenomic datasets collected over time, typically via either genome-scale chromatin immunoprecipitation (ChIP-Seq) or DNA methylation analysis (bisulfite sequencing). Simple in theory, such studies can nevertheless be massive undertakings.
Take, for instance, “Project Grandiose,” (PDF) which in December published five papers in Nature and Nature Communications on the dynamics of cellular reprogramming.
According to Nagy, who leads Project Grandiose, the name reflects the magnitude of the project’s efforts. Fifty scientists spent four years and tens of millions of cells per day compiling eight layers of ‘omics data on the transcriptional, proteomic and epigenomic changes that accompany the transition from fibroblast to iPS cell. Among the epigenomic variables the project monitored were transcription of noncoding RNA by RNA-Seq, DNA methylation by bisulfite sequencing and histone modification by ChIP-Seq.
“We are not really ashamed of being not too modest,” Nagy quips.
Among other things, the papers describe a previously unrecognized cell state called “F-class” for the fuzzy appearance of the cells under a microscope [1]. At the epigenomic level, the transition to F-class and iPS cells is associated with global changes in DNA methylation and histone modification, with an initial loss of repressive chromatin marks followed by changes in DNA methylation that seem to lock the new cell state into place. “The cells lose and forget their identity and are asking for a clue on how to develop a new one,” Nagy says.
State of the art
Although ChIP is by no means new, developers do continue to refine it. New ChIP validated antibodies are in constant development. And EMD Millipore, for instance, is preparing to launch in February its PureGenome Low Input NGS Library Construction Kit, which can sequence as little as 50 pg of ChIP-purified DNA, or about 1,000 cells’ worth, says Michael Sturges, senior product manager for target-specific reagents at EMD Millipore. (By comparison, the company’s Magna ChIP-Seq™ ChIP and NGS Library Preparation Kit requires 1 ng of DNA.)
But ChIP-Seq is just one of many epigenomic datasets that can figure into chromatin-dynamics studies, notes Kyle Hondorp, product manager at Active Motif. Also amenable, for instance, are methods that reveal genomic topography. These techniques, such as 3C (chromosome conformation capture), 5C (carbon-copy chromosome conformation capture) and ChIA-PET (chromatin interaction analysis by paired-end tag sequencing), capture distantly separated DNA regions that are brought together by intramolecular interactions—for instance, when an enhancer interacts with a distant gene promoter. By sequencing the resulting junctions, researchers can begin to visualize the chromatin superstructure, and how it changes over time.
William Greenleaf at the Stanford University School of Medicine, described in 2013 another useful method [2]. Called ATAC-Seq, the assay exploits the preference of the Tn5 transposase (which is a key component in Illumina’s Nextera sequencing-library preparation kit) for euchromatin ("open" chromatin) over heterochromatin ("closed") to identify transcriptionally active genomic regions. Greenleaf’s team used this method to characterize the chromatin state of the interleukin-2 locus in T cells from a single individual collected over three days.
Methods such as ChIRP (chromatin isolation by RNA purification), CHART (capture hybridization analysis of RNA targets) and RAP (RNA antisense purification) detail interactions between chromatin and noncoding RNAs. EMD Millipore recently released a kit implementation of ChIRP, called the EZ-Magna ChIRP RNA Interactome Kit, which enables users to isolate genomic DNA and/or proteins associated with a given noncoding RNA.
And for those interested in protein complex distribution, Active Motif now offers a service called RIME (rapid immunoprecipitation mass spectrometry of endogenous proteins). According to Hondorp, RIME is like ChIP—it uses an antibody to a specific protein to isolate associated genomic DNA. But in contrast to the traditional ChIP protocol, which reverses the protein-DNA crosslink and destroys protein using proteinase K, RIME preserves the protein, characterizing it using mass spectrometry. “That gives a sense of what proteins might be colocalizing to the same regions of chromatin [as the specifically immunoprecipitated protein],” she says.
Indeed, there’s no shortage of techniques researchers can use to explore chromatin dynamics. It’s just a matter of collecting epigenomics datasets over time. The difficulty, says Nagy, is in the analysis—specifically, obtaining a holistic view of the different ‘omics parameters as they ebb and flow in response to environmental and developmental cues. Tools for that purpose are lacking, Nagy says, but in development.
Bottom line: When it comes to epigenomics, the toolset, like chromatin itself, is dynamic.
References
[1] Tonge, PD, et al., “Divergent reprogramming routes lead to alternative stem-cell states,” Nature, 516:192–7, 2014. [PubMed ID: 25503232]
[2] Buenrostro, JD, et al., “Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position,” Nat Methods, 10:1213-8, 2013. [PubMed ID: 24097267]
Image: iStockPhoto