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Recipes and mechanisms of cellular reprogramming: a case study on budding yeast Saccharomyces cerevisiae.

Ding S, Wang W - BMC Syst Biol (2011)

Bottom Line: A key challenge is to find the recipes of perturbing genes to achieve successful reprogramming such that the reprogrammed cells function in the same way as the natural cells.We present here a systems biology approach that allows systematic search for effective reprogramming recipes and monitoring the reprogramming progress to uncover the underlying mechanisms.As the heterogeneity of natural cells is important in many biological processes, we find that the extent of this heterogeneity restored by the reprogrammed cells varies significantly upon reprogramming recipes.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Chemistry and Biochemistry, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0359, USA.

ABSTRACT

Background: Generation of induced pluripotent stem cells (iPSCs) and converting one cell type to another (transdifferentiation) by manipulating the expression of a small number of genes highlight the progress of cellular reprogramming, which holds great promise for regenerative medicine. A key challenge is to find the recipes of perturbing genes to achieve successful reprogramming such that the reprogrammed cells function in the same way as the natural cells.

Results: We present here a systems biology approach that allows systematic search for effective reprogramming recipes and monitoring the reprogramming progress to uncover the underlying mechanisms. Using budding yeast as a model system, we have curated a genetic network regulating cell cycle and sporulation. Phenotypic consequences of perturbations can be predicted from the network without any prior knowledge, which makes it possible to computationally reprogram cell fate. As the heterogeneity of natural cells is important in many biological processes, we find that the extent of this heterogeneity restored by the reprogrammed cells varies significantly upon reprogramming recipes. The heterogeneity difference between the reprogrammed and natural cells may have functional consequences.

Conclusions: Our study reveals that cellular reprogramming can be achieved by many different perturbations and the reprogrammability of a cell depends on the heterogeneity of the original cell state. We provide a general framework that can help discover new recipes for cellular reprogramming in human.

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Divergent properties of recipes reprogramming sporulation to cell cycle under growth condition. (A) Potency versus efficiency of a recipe. (B) Cell cycle attractors are unequal in terms of their capability to sporulate. When starting from the states within 5 evolving steps to the 12 cell cycle attractors, their percentages of converging to sporulation attractors under sporulation condition vary significantly. (C) Heterogeneity deviation versus efficiency of a recipe. The six Pareto optimal recipes are highlighted on the Pareto frontier. Right panel: heterogeneity profiles for the wild type and reprogrammed cells. Wild type cells under growth condition populate in 12 basins (A1 to A12 and colored differently) and the basin size is proportional to the width of each color in the profile bar. Cells reprogrammed by different recipes show different extent of deviation from the natural cells. See also Additional file 4, Table S4.
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Figure 5: Divergent properties of recipes reprogramming sporulation to cell cycle under growth condition. (A) Potency versus efficiency of a recipe. (B) Cell cycle attractors are unequal in terms of their capability to sporulate. When starting from the states within 5 evolving steps to the 12 cell cycle attractors, their percentages of converging to sporulation attractors under sporulation condition vary significantly. (C) Heterogeneity deviation versus efficiency of a recipe. The six Pareto optimal recipes are highlighted on the Pareto frontier. Right panel: heterogeneity profiles for the wild type and reprogrammed cells. Wild type cells under growth condition populate in 12 basins (A1 to A12 and colored differently) and the basin size is proportional to the width of each color in the profile bar. Cells reprogrammed by different recipes show different extent of deviation from the natural cells. See also Additional file 4, Table S4.

Mentions: It is almost impossible to convert a fully differentiated mammalian cell back to the pluripotent state by only switching culture medium. Therefore, to mimic the generation of iPS cell, we examined the reprogramming of the yeast cells committed to sporulation, i.e. cells within 4 evolving steps from any sporulation attractor that cannot evolve to cell cycle attractors by only switching condition. For the 100 most potent reprogramming recipes, we checked the percentage of the 10,000 randomly sampled cell states that are committed to sporulation but can be reprogrammed to proliferation and we defined this percentage as the efficiency of the reprogramming recipe. Obviously, the efficiency of a high-potency recipe is not necessarily high (Figure 5A). Potency reflects the fixed points of the network under a given environmental condition and reprogramming perturbation, and all initial states are considered when calculating the percentage of cell cycle attractors. Efficiency defined here indicates the convergence to cell cycle attractors only from the cell states committed to sporulation.


Recipes and mechanisms of cellular reprogramming: a case study on budding yeast Saccharomyces cerevisiae.

Ding S, Wang W - BMC Syst Biol (2011)

Divergent properties of recipes reprogramming sporulation to cell cycle under growth condition. (A) Potency versus efficiency of a recipe. (B) Cell cycle attractors are unequal in terms of their capability to sporulate. When starting from the states within 5 evolving steps to the 12 cell cycle attractors, their percentages of converging to sporulation attractors under sporulation condition vary significantly. (C) Heterogeneity deviation versus efficiency of a recipe. The six Pareto optimal recipes are highlighted on the Pareto frontier. Right panel: heterogeneity profiles for the wild type and reprogrammed cells. Wild type cells under growth condition populate in 12 basins (A1 to A12 and colored differently) and the basin size is proportional to the width of each color in the profile bar. Cells reprogrammed by different recipes show different extent of deviation from the natural cells. See also Additional file 4, Table S4.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3094211&req=5

Figure 5: Divergent properties of recipes reprogramming sporulation to cell cycle under growth condition. (A) Potency versus efficiency of a recipe. (B) Cell cycle attractors are unequal in terms of their capability to sporulate. When starting from the states within 5 evolving steps to the 12 cell cycle attractors, their percentages of converging to sporulation attractors under sporulation condition vary significantly. (C) Heterogeneity deviation versus efficiency of a recipe. The six Pareto optimal recipes are highlighted on the Pareto frontier. Right panel: heterogeneity profiles for the wild type and reprogrammed cells. Wild type cells under growth condition populate in 12 basins (A1 to A12 and colored differently) and the basin size is proportional to the width of each color in the profile bar. Cells reprogrammed by different recipes show different extent of deviation from the natural cells. See also Additional file 4, Table S4.
Mentions: It is almost impossible to convert a fully differentiated mammalian cell back to the pluripotent state by only switching culture medium. Therefore, to mimic the generation of iPS cell, we examined the reprogramming of the yeast cells committed to sporulation, i.e. cells within 4 evolving steps from any sporulation attractor that cannot evolve to cell cycle attractors by only switching condition. For the 100 most potent reprogramming recipes, we checked the percentage of the 10,000 randomly sampled cell states that are committed to sporulation but can be reprogrammed to proliferation and we defined this percentage as the efficiency of the reprogramming recipe. Obviously, the efficiency of a high-potency recipe is not necessarily high (Figure 5A). Potency reflects the fixed points of the network under a given environmental condition and reprogramming perturbation, and all initial states are considered when calculating the percentage of cell cycle attractors. Efficiency defined here indicates the convergence to cell cycle attractors only from the cell states committed to sporulation.

Bottom Line: A key challenge is to find the recipes of perturbing genes to achieve successful reprogramming such that the reprogrammed cells function in the same way as the natural cells.We present here a systems biology approach that allows systematic search for effective reprogramming recipes and monitoring the reprogramming progress to uncover the underlying mechanisms.As the heterogeneity of natural cells is important in many biological processes, we find that the extent of this heterogeneity restored by the reprogrammed cells varies significantly upon reprogramming recipes.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Chemistry and Biochemistry, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0359, USA.

ABSTRACT

Background: Generation of induced pluripotent stem cells (iPSCs) and converting one cell type to another (transdifferentiation) by manipulating the expression of a small number of genes highlight the progress of cellular reprogramming, which holds great promise for regenerative medicine. A key challenge is to find the recipes of perturbing genes to achieve successful reprogramming such that the reprogrammed cells function in the same way as the natural cells.

Results: We present here a systems biology approach that allows systematic search for effective reprogramming recipes and monitoring the reprogramming progress to uncover the underlying mechanisms. Using budding yeast as a model system, we have curated a genetic network regulating cell cycle and sporulation. Phenotypic consequences of perturbations can be predicted from the network without any prior knowledge, which makes it possible to computationally reprogram cell fate. As the heterogeneity of natural cells is important in many biological processes, we find that the extent of this heterogeneity restored by the reprogrammed cells varies significantly upon reprogramming recipes. The heterogeneity difference between the reprogrammed and natural cells may have functional consequences.

Conclusions: Our study reveals that cellular reprogramming can be achieved by many different perturbations and the reprogrammability of a cell depends on the heterogeneity of the original cell state. We provide a general framework that can help discover new recipes for cellular reprogramming in human.

Show MeSH
Related in: MedlinePlus