Image-based methods for measuring global nuclear patterns as epigenetic markers of cell differentiation
The invention provides methods for determining the differentiation state of cells. The methods include non-invasive, non-perturbing, automatable, and quantitative methods of analysis of cell colonies, individual cells, and/or cellular structures.
1. A method for identifying viscoelastic phase transitions of test cells, comprising:
(a) obtaining images of one or more test cells over a period of time;
(b) measuring one or more feature dynamics of the test cells in the images;
(c) using a processor to model the one or more feature dynamics as a function of time; and
(d) comparing models of feature dynamics from the test cells with models of feature dynamics derived from reference cells at reference viscoelastic phases;
whereby the viscoelastic phase transitions in the test cells are determined.
2. The method of claim 1 , wherein the phase transitions represent transitions between distinct phases of the test cells.
3. The method of claim 1 , wherein test cells are deformable in a first viscoelastic phase and transition to a solid-like state in a second viscoelastic phase.
4. The method of claim 1 , wherein the phase transitions are transitions between one or more states of chromatin condensation.
5. The method of claim 4 , wherein test cells in a first state of chromatin condensation with a diffuse chromatin structure transition to a second state of chromatin condensation with a dense chromatin structure.
6. The method of claim 1 , wherein the phase transitions are transitions between states characterized by expression levels of markers in the test cells.
7. The method of claim 6 , wherein test cells in a first state express high levels of markers NAP1 and ASF1 and transition to a second state in which the test cells express low levels of NAP1 and ASF1.
8. The method of claim 1 , wherein the one or more test cells is a colony of cells.
9. The method of claim 1 , further comprising varying environmental conditions over the period of time in step (a).
10. The method of claim 9 , wherein the environmental conditions are at least one of temperature, humidity, O 2 levels, and composition of culture media in which test cells grow.
11. The method of claim 1 , wherein the one or more feature dynamics is a change in a level or a distribution of one or more proteins in the test cell.
12. The method of claim 1 , wherein the one or more feature dynamics is shape variation.
13. The method of claim 1 , wherein the one or more feature dynamics is elasticity of a nucleus in the test cell.
14. The method of claim 1 , wherein the one or more feature dynamics is a colony feature dynamic.
15. The method of claim 14 , wherein the colony feature dynamic is at least one of colony texture and nuclear dynamics.
16. The method of claim 1 , wherein the one or more feature dynamics varies according to the differentiation state of the test cell.
17. The method of claim 1 , wherein using a processor to model the one or more feature dynamics comprises modeling the feature dynamics at two levels.
18. The method of claim 17 , wherein the two levels are lower levels and higher levels.
19. The method of claim 18 , wherein the feature dynamics are modeled as a function of time in the lower level.
20. The method of claim 19 , wherein the feature dynamics change over time in response to environmental conditions.
21. The method of claim 20 , comprising representing feature dynamics as a power spectrum.
22. The method of claim 18 , wherein phase transitions are modeled in the higher level.
23. The method of claim 17 , further comprising determining changes in the feature dynamics from step (c) as a function of the environmental conditions, and optionally adjusting environmental conditions on the basis of feature dynamics.