Researchers Develop Platform to Track Gene Expression Through Generations of Cells

    MIT 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 in Nature Communications.

    “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,” says Robert Kimmerling, a graduate student in biological engineering and the lead author of a paper (“A microfluidic platform enabling single-cell RNA-seq of multigenerational lineages”) describing the technique in Nature Communications.

    The new method incorporates single-cell RNA-seq, which sequences a single cell’s transcriptome and reveals which genes are being transcribed inside a cell at a given point in time. This helps scientists understand, for example, what makes a skin cell so different from a heart cell even though the cells share the same DNA.

    “Scientists have well-established methods for resolving diverse subsets of a population, but one thing that’s not very well worked out is how this diversity is generated. That’s the key question we were targeting: how a single founding cell gives rise to very diverse progeny,” points out Kimmerling.

    To try to answer that question, the researchers designed a microfluidic device that traps first an individual cell and then all of its descendants. The device has several connected channels, each of which has a trap that can capture a single cell. After the initial cell divides, its daughter cells flow further along the device and get trapped in the next channel. The researchers showed that they can capture up to five generations of cells this way and keep track of their relationships.

    To get the cells off the chip, the researchers temporarily reverse the direction of the fluid flowing across the chip, allowing them to remove the cells one at a time to perform single-cell RNA-seq.

    In this study, the team captured and sequenced T cells that—when they encounter a cell infected with a virus or bacterium—create effector T cells, which seek and destroy infected cells, as well as memory T cells that retain a “memory” of the encounter and circulate in the body indefinitely in case of a subsequent encounter.

    “A single founding cell can give rise to both effector and memory cell subtypes, but how that diversity is generated isn’t very clear,” explain Kimmerling.

    The scientists analyzed RNA from recently activated T cells and two subsequent generations. When comparing genes with functions related to T-cell activation and differentiation, they found that sister cells produced from the same division event are much more similar in their gene expression profiles than two unrelated cells. They also found that “cousin” cells, which have the same “grandmother,” are more similar than unrelated cells. This suggests unique, family-specific transcriptional profiles for single T cells.

    The researchers hope that future studies with this device could help to resolve the long-standing debate over how T cells differentiate into effector cells and memory cells. One theory is that the distinction occurs as early as the first T cell division following activation, while a competing theory suggests that the distinction happens later on, as a result of changes in the cells’ microenvironment.

    To address this question, the researchers believe they would need to analyze the development of T cells taken from a mouse that had been exposed to a foreign pathogen, providing a useful model of T cell activation in response to infection.