NEW YORK (GenomeWeb) – Massachusetts Institute of Technology researchers have developed a microfluidic platform allowing them to trace cells as they divide. Using the platform, the researchers were also able to remove the daughter cells for single-cell analysis, as MIT's Scott Manalis and his colleagues reported today in Nature Communications.
The researchers used their device to follow mouse CD8+ T-cell and lymphocytic leukemia cell line lineages, and generate transcriptomic profiles of single cells from those lineages. They found that cells have more intra-lineage than inter-lineage transcriptional similarities. The transcriptomes of CD8+ T-cells, for instance, were enriched for genes involved in lymphocyte differentiation and function.
"Existing methods allow for snapshot measurements of single-cell gene expression, which can provide very in-depth information. What this new approach offers is the ability to track cells over multiple generations and put this information in the context of a cell's lineal history," first author Robert Kimmerling, a graduate student in biological engineering at MIT, said in a statement.
In addition, by pinpointing where in their cell cycle the cells were analyzed, the researchers uncovered cell type-specific transcriptional signatures linked to cell cycle progression.
Manalis, Kimmerling, and their colleagues devised a fluidic device that houses an array of hydrodynamic traps to capture and culture single cells on chip. The traps rely on differences in hydrodynamic resistance between the trap pockets and channels to capture single cells. At the same time, pressure applied upstream and downstream creates a pressure gradient that enables media and nutrients to perfuse through the channels and traps.
As the cells divide, the daughter cells are shunted downstream and captured in empty traps. Each lane of traps, the researchers noted, can accommodate 40 cells, or track one cellular lineage for five generations.
Time-lapse imaging, the researchers added, enables the determination of single-cell proliferation kinetics and the identification of linear relationship of cells.
Cells can be removed from the traps by reversing the pressure differential across the trap lanes, enabling them to be collected in the bypass channel and flushed out.
Kimmerling and his colleagues cultured single CD8+ T-cells and lymphocytic leukemia cells on their microfluidic chip for two generations before releasing them for RNA sequencing. This way, they noted, they could compare sister and cousin cell pairs for each lineage.
They found that sister cell pairs exhibited higher transcriptional similarity than unrelated cell pairs for both CD8+ T-cell and lymphocytic leukemia cells. For CD8+ T-cells, cousin pairs also exhibited high transcriptional similarity.
Clustering largely reconstructed the lineage relationships of most, but not all, of the cells, which indicated to the researchers that computational approaches might not be as effective as direct observation of cellular division in predicting single-cell lineage relationships.
The researchers focused their analyses on a subset of genes involved in CD8+ T-cell activation, differentiation, and cytotoxic function to again find greater intra-clonal transcriptional similarity. Those genes that showed more intra-clonal and inter-clonal similarity were enriched for gene ontology annotations linked to T-cell activation and immune cell function, they added.
The team further found that gene expression of Granzyme B (Gzmb), whose protein product plays a key part in cytotoxic T-cell-mediated target cell killing, exhibited one of the highest levels of clonal similarity between sister and cousin pairs, as compared to unrelated pairs.
Where cells fall in the cell cycle also influences what genes they express, Kimmerling and his colleagues noted. Cultured cells from the same lineage are more likely to be at the same point in the cell cycle as they are derived from common division events, whereas unrelated pairs are, on average, likely to be at differing points in the cell cycle. This could confound whether similarities are due to their lineage relationship or due to them being at similar cell cycle stages, the team added.
As the researchers had followed the cells since they arose from previous cells, they knew the approximate time since the last division, and they used that timing as a proxy for where they were in cell cycle progression.
Unrelated L1210 and CD8+ T-cell pairs with smaller differences in time from cell division were more transcriptionally similar than pairs that had greater differences in time since last cell division, the researchers reported. For CD8+ T-cell pairs, they added, the effect was especially marked for genes with cell cycle-related functions.
This, the researchers said, indicates that the global transcriptional similarities observed in related L1210 and CD8+ T-cell pairs is likely due in part to their closeness in cell cycle stage.
Still, Kimmerling and his colleagues found that this cell cycle effect was less pronounced for the subset of CD8+ T-cell genes associated with T-cell activation and function. Expression levels of these genes, including that of Gzmb, exhibited a strong correlation between related cells, but not with time since cell division. In addition, when they limited their analyses to unrelated cell pairs at similar cell cycle stages, sister and cousin cell pairs still showed greater transcriptional similarity.
The researchers also uncovered a set of some 300 genes that corresponded with time since cell division — most of which are involved in cell division itself — and, they added, the expression levels of these 300 genes could be used to gauge cellular age.
According to Kimmerling and his colleagues, such a cellular tracing approach coupled with single-cell analyses could help researchers better understand cellular differentiation, especially in stem and immune cells, as well as in cancer cells.