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Just four hours after landing in Vancouver for the 2014 meeting of the International Society for Stem Cell Research, I was delighted to attend the late afternoon plenary session on Cell Heterogeneity. Both John Dick and Connie Eaves – juggernauts of the Canadian stem cell community – reminded us of the differences between stem and progenitor cells of the human and mouse blood system respectively and Kateri Moore nicely summarized her group’s efforts to make hematopoietic cells from fibroblasts. For me, however, the really exciting and novel talk was by Alexander van Oudenaarden, who described his group’s recent efforts to develop a procedure for assessing the gene expression program of cells without sacrificing information on where they live in the body.
The van Oudenhaarden group has recently produced very interesting papers on feedback control of gene expression and single cell transcriptomics, clearly demonstrating an expertise in the quantitative assessment of single cells. Indeed, one of his first slides highlighted the recent and exciting convergence of single cell biology and global gene expression techniques that now permit researchers to study interaction networks and heterogeneity in single stem cell populations. However, as van Oudenhaarden points out, all of these techniques lose a critical piece of information – location.
Typically, researchers are forced to pull out individual stem and progenitor cell populations from their more numerous differentiated progeny based on their differential expression of cell surface proteins. This is all completed outside of the body and as a consequence, it severs any attachment to other cells and removes the cells from their normal location.
His group therefore has developed a new technique called Tomo-seq (tomos is Greek for slice/section and Seq is the suffix of choice for many recent technologies using high throughput sequencing). Put simply, Tomo-seq combines high throughput gene sequencing with tissue sectioning protocols. In essence this means that they are shaving off very tiny fractions of fixed tissue to assess the cells in each section. Each sample is given a molecular barcode and these samples can then be pooled for sequencing, markedly reducing the cost.
This new technique allows researchers to understand whether location differences impact gene expression programs, a very important step toward understanding which pathways might be involved in stem cell niche regulation and biology. This becomes particularly important in situations where the environment has been strongly suggested to play a major role in the regulation and function of stem cell populations. For example, multiple “homes” (e.g., alongside the edge of the bone, in areas with lots of blood vessels) have been proposed for blood stem cells and numerous groups suggest different roles in cell cycle and active contribution to day-to-day blood creation. However, very little is understood about the differential signaling networks involved in cells from these different homes.
The technique appears quite robust for detecting broad differences between environments, but it may struggle with broad utility unless it can be adapted to isolate homogeneous cell populations from these sectioned populations. Moreover, laser capture micro-dissection already serves this purpose for identifying “tumour” vs. “normal” in cancer samples from solid tissue. For now, I suspect Topo-seq will be very useful in model organisms and solid tissues where the environments are clearly defined and the cell populations reasonably well-defined.
Research cited:
Pereira C.F., Jiajing Qiu, Xiaohong Niu, Dmitri Papatsenko, Caroline E. Hendry, Neil R. Clark, Aya Nomura-Kitabayashi, Jason C. Kovacic, Avi Ma’ayan & Christoph Schaniel & (2013). Induction of a Hemogenic Program in Mouse Fibroblasts, Cell Stem Cell, 13 (2) 205-218. DOI: http://dx.doi.org/10.1016/j.stem.2013.05.024
Grün D. & Alexander van Oudenaarden (2014). Validation of noise models for single-cell transcriptomics, Nature Methods, 11 (6) 637-640. DOI: http://dx.doi.org/10.1038/nmeth.2930
Ji N., Remco A. Mentink, Marco C. Betist, Satto Tonegawa, Dylan Mooijman, Hendrik C. Korswagen & Alexander van Oudenaarden (2013). Feedback Control of Gene Expression Variability in the Caenorhabditis elegans Wnt Pathway, Cell, 155 (4) 869-880. DOI: http://dx.doi.org/10.1016/j.cell.2013.09.060
David Kent
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