Recent advances in molecular barcoding have enabled the high-throughput sequencing of the transcriptomes of thousands of individual cells from a single tissue. Recent advances in molecular barcoding have enabled the high-throughput sequencing of the transcriptomes of thousands of individual cells from a single tissue. CITATION: Klein AM, Mazutis L, Akartuna I, Tallapragada N, Veres A, Li V, et al. Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell 2015; 161: 1187–1201. CITATION: Macosko EZ, Basu A, Satija R, Nemesh J, Shekhar K, Goldman M, et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 2015; 161: 1202–1214. CITATION: Shalek AK, Satija R, Shuga J, Trombetta JJ, Gennert D, Lu D, et al. Single-cell RNA-seq reveals dynamic paracrine control of cellular variation. Nature 2014; 510: 363–369. Cellular biology during the 20th century largely focused on the analysis of populations of cells, and mechanisms underlying heterogeneity between cells within a given population have remained largely unknown. Now, single-cell RNA–seq based approaches are revolutionizing our understanding of cell-to-cell variability by providing unbiased exploration of the molecular underpinnings of heterogeneity within a given cell population. In a 2014 report in Nature, Shalek et al. used a microfluidics device to prepare approximately 1700 single-cell RNA-seq libraries of individual murine bone marrow–derived dendritic cells responding to viral infection. Their results showed marked variation in transcriptomes between identically stimulated dendritic cells. Specifically, following exposure to viral pathogen, relatively few “precocious” cells began to express antiviral gene signatures at early timepoints, while more of the cells acquired these transcripts later on. Interestingly, inhibiting cell-to-cell communication by individually stimulating cells in sealed microfluidics chambers resulted in the uniform upregulation of expression of the core antiviral genes at early timepoints in all cells, suggesting that the individual heterogeneity observed under normal conditions is not the result of some pre-existing difference between the “early responder” and “late responder” cells, but that cell-to-cell heterogeneity is in fact an active process that is highly coordinated by these few early responder cells. The power of this approach has been further strengthened in a pair of 2015 studies by Macosko et al. and Klein et al. that reported on the use of a highly parallel approach for sequencing single cells, which may significantly broaden the use of this technology. In their approach, individual cells are separated into nanoliter-sized aqueous droplets and a distinct barcode is linked with each individual cell’s RNA (Figure 1). Sequencing of thousands of droplets is then performed in parallel, with the barcode retaining the identity of the cell from which the RNA in the droplet was derived. The result is the simultaneous acquisition of transcriptomic information from each individual cell in the tissue. Of particular interest to transplant, these new methods may enable the transcriptional profiling of entire organs at much greater depth than what has been previously possible. These results have important implications for transplantation on many levels. First, they provide important data on the molecular mechanisms underlying heterogeneity within the immune response. The idea that immune responses (for dendritic cells, at least) may be regulated by a few “driver cells” is an important concept that could have therapeutic implications for immunosuppressive strategies following transplantation. Secondly, the use of high-throughput single-cell RNA-seq could be applied to molecular profiling of biopsies during episodes of suspected rejection or infection, or for the identification of tolerance. Currently, tissue-level transcriptomic analysis of biopsies is limited by the fact that it precludes the determination of whether elevated expression of a particular gene is the result of increased gene transcription within a subset of cells, or simply due to the increased presence of that subset within the biopsy. Single-cell RNA-seq will allow for the identification of the type, frequency, and gene expression profile of both graft-derived and infiltrating immune cells in order to better assess the molecular atlas of rejecting versus stable allografts following transplantation. One could even speculate that in the future, amalgamation of large single-cell transcriptomes with known spatial expression patterns of marker genes could facilitate the reconstruction of the complex 3D architecture of an entire kidney, heart, liver, or lung, essentially providing the instruction manual for de novo assembly of new organs for use in transplantation.
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Open Access
Oct 28, 2017
Anna Salvati + 10
