Genome-wide analysis of self-renewal in Drosophila neural stem cells by transgenic RNAi
May 06, 2011
Spectacular recent advances in the field of stem cell biology have raised enormous hopes for regenerative medicine. One key property of stem cells is their ability to "self-renew", that is to generate identical copies of themselves while at the same time producing more specialized cells, which then replace damaged cells in the tissue. One of the key challenges in stem cell biology is to understand how the balance between self-renewal and specialization is regulated - with the goal to some day manipulate this balance to increase or decrease the regenerative capacity of individual tissues.
The fruitfly Drosophila has emerged as a simple key model system for stem cell biology. Neural stem cells in the developing fly brain follow a simple lineage and divide reproducibly into one self-renewing and one differentiating daughter cell. So far, all the components of the cellular machinery responsible for this asymmetric division are also present in human stem cells and many of them fulfill the same role.
Researchers in the laboratory of Juergen Knoblich at IMBA have now made a huge effort to identify essentially all the components that are important in Drosophila neural stem cells. They used a transgenic RNAi library from the Vienna Drosophila RNAi Center (VDRC) to inhibit almost all genes in the fly genome in neural stem cells. One by one, they studied the effects of inhibiting individual genes and carefully described the effects on the neural stem cells. Importantly, those experiments were done in whole living flies and not in cell culture where those effects can be very different. The results provide a unique resource for the stem cell community as most of the genes they identify are also present in human stem cells. The precise quantification of the resulting effects has allowed an unprecedented bioinformatic analysis of the data which allowed insights into stem cell biology that were not possible before. The data obtained through this study provide a unique starting point for a systems-level analysis of stem cells.
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