18 January

Thesis defense Mauro Muraro: gene expression in individual pancreas cells

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Mauro Muraro, PhD, Hubrecht researcher in the Van Oudenaarden group, studied the proceedings of single-cell sequencing and applied this technology to the pancreas. Muraro successfully defended his thesis on January 18th, 2018.

Muraro researched the experimental and computational progress booked in the field of single-cell sequencing. Next, he applied the researched methods to the biology and development of the pancreas.

To get an overview of the abundance of cells in the human pancreas, Muraro used the single-cell sequencing technology. Our DNA is the blueprint for all proteins that are produced by a cell and that determine cell function. Every cell in the human body contains roughly the same DNA, but different cell types only use different parts of that common blueprint. mRNA molecules are the step between the DNA and a protein – they act as messengers, transmitting which proteins can be produced. That function makes mRNA very suitable as an indicator for cell function. By discovering their sequence, their code, single-cell sequencing grants us an overview of all these mRNA molecules. Until recently, the sequencing technology only allowed analyses of thousands of cells simultaneously, drawing an image of the average gene expression in these cells, thereby outshining the more uncommon cells.

(c) Jean-Charles Boisset

Individual cells
Single-cell sequencing allows us to determine the gene expression profile of individual cells. First, a single cell is sorted, its mRNA is multiplied and the material receives a molecular barcode. Next, the mRNA of various cells can be combined and sequenced in the traditional way. The barcode allows researchers to trace back the data to the original cell. Therefore, these experiments give us information on the genes expressed by each individual cell.

Muraro applied single-cell sequencing to characterize human pancreatic cells. To that end, he and his colleagues processed thousands of pancreatic cells from four different donors. With this technology, they were able to describe the complete mRNA profile of all present cells. They also found new genes specific for the processed pancreatic cells, and found several sub-species of cells that were already known, but behave just a little different compared to their known siblings. Likewise, by studying embryonal pancreas cells of rodents, Muraro was able to form a lineage tree, describing the trajectory from stem cell to adult pancreatic cell. The researchers also found a new kind of cell, that seems to be the missing link between pancreatic stem cells and adult cell types. The characteristics of this new cell type have yet to be determined.

Antibodies are not always available for human cells. For those occasions, this method offers a solution.

Native cellular information
In the last part of his thesis, Muraro describes a new algorithm designed for cell sorting based on sequencing data. Individual cells are characterized based on native cellular information, like size, internal complexity and fluorescence. Muraro managed to sort cells according to these parameters. The advantage of this method is that a sample can be enriched for a desired cell type using intrinsic cell properties, in contrast to sorting with antibodies that bind to the surface of a cell. Muraro: ‘Those antibodies are not always available for human cells. For those occasions, this method offers a solution.’

New dimension
The ability to characterize individual cells adds a new dimension to cell biology. With single-cell sequencing, the gene expression of thousands of individual cells can be researched, without the most prevalent cell type dominating the obtained data. In this way, rare cell types can be discovered and characterized that would not have been detected using traditional sequencing methods. The ‘genetic atlases’ Muraro formulated allow other researchers to search for genetic expression patterns based on the known cell types in the adult human pancreas, and the developing murine pancreas. That information could prove to be a useful ally for those who research pancreatic biology and development.