博文
An introduction to the 'attractor' theory of gene regulatory networks
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本文仍然转自本人Blog on Researchgate。本来说在有进展之前只写短文，不料还是写长了。不过这也算是阅读与思考的进展吧～
在我眼中，HUANG Sui老师的研究属于非常前沿，既富于理论性，属基础研究，又离应用前景不远，很符合我的理想。其实本站博主周旭老师在一年多之前就已经介绍过这项研究，我只是继续跟进关注。
写完这篇博文之后，又在数据库中检索了一下，发现已经有很多相关研究，有一些跟我所提到的几个创新点有关，但重合不多。他们未必提到Huang老师的工作，因为做相关模型的也有其他人。
目前干细胞与癌症相关研究非常热门。我虽然对热门的东西不感冒，但是这次例外，因为这个领域即将出现微观生命科学中第一个统一性的理论。当然了，个人之见而已。
Dr. HUANG Sui at the University of Calgary has spent the last few years exemplifying and improving the State Space & Attractor theory of gene regulatory networks (GRN), which was initially proposed by Prof. Stuart KAUFFMAN from 1960’s. Incorporating the original concept of epigenetics (Waddington 1942) and methodology of systems biology, the theory seems surprisingly simple to be understood and, in my opinion, a promising framework for future stem cell and cancer researches.
Assuming each gene has two alternative states (ON or OFF), a genome containing N genes will have 2^N possible states, composing the so-called high-dimensional State Space. However, due to the mutual interactions between all the genes within a genome, some positions in the space are impossible to occur, and the realistic positions of the genome expression profile are limited to the space surrounding some lines, or ‘trajectories’. In the whole life of a cell, its genome expression profile is like ‘walking’ through these trajectories within the presumed state space.
What’s more, there are ‘attractors’ on the way of the trajectories. This means some positions in the state space are the most likely to occur to a cell; they are like black holes in the cosmos and any walking-by cells will be attracted towards them. If we were given a known genome and the information about all the interactions between the genes involved, we could be able to determine what the trajectories look like and where the attractors are located within the state space.
Unsurprisingly, these attractors could correspond to different cell types (or cell fates) in terms of cell development. In an analogy from Huang and Kauffman, a cell as a pluripotent progenitor is like to be at a mountain top, and its daughter cells will just ‘fall’ into surrounding valleys driven by the imaginary ‘potential energy’. Each valley is literally an attractor, and cells ‘falling’ into different valleys will turn to be different types of cells. This is not only an analogy now because it is already well formulated and supported by data from Huang and other scientists’ studies. (See Figure 1 from Huang 2009.)
Figure I. A diagram of the 'mountain and valley' analogy (from Huang 2009)
It remains a question whether genome expression profile can solely and exhaustively explain cell differentiation, I think. Anyway, case studies of a simple system were able to show that the expression profile of a pair of cross-inhibiting genes (GATA1 and PU.1) can sufficiently decide whether a colony of progenitor blood cells will develop to be red or white blood cells.
The theory seems an exciting blueprint from which a plural of more specific inferences can be derived, perhaps at first in the area of induced Pluripotent Stem (iPS) cells. Imagine if Dr. YAMANAKA Shinya could benefit from special ‘trajectories’ from this theory, he would be able to develop more efficient ways of cell induction and quality control, rather than just overexpressing some candidate genes and checking them in the culture media, and shortly he will be able to move those procedures from bench to factory.
Huang himself says that he aims at building up a unifying theory of multi-cellularity. I really appreciate his ambition. And again I agree that good works in basic (or pure) science never went against application research.
However, the present theory is still steps away from its final success. Several questions have to be answered to make it more rigorous and applicable.
1) The first question is how pluri/multipotency is maintained (and escaped) as the status of stem cells and all levels of progenitor cells.
Huang gave a possible explanation by providing a model in which auto-stimulation of cross-inhibiting genes leads to a ‘meta-stable’ state, which serves as an attractor as well. As shown in Figure 1, there is an assumed 'lake' on the mountaintop where the stem/pluri/multipotent cells are supposed to locate. But even if the pluripotent status is not an attractor, i.e., the 'lake' does not exist, we can still go on looking for mechanisms keeping cells there and driving them out of it.
2) The second question is how the imaginary ‘walking’ of cells along the trajectories is coupling with cell division. Are the ‘walking’ potential and the proliferation potential correlated with each other?
Considering the imaginary ‘potential energy’ in the ‘mountain and valley’ analogy, there is a possibility that the non-attractor status or the height of the mountain indeed provides a driving force for cell proliferation. If so, the ‘potential energy’ will turn out a realistic energy, not only an mathematical derivative in the abstract model. However, things are not so easy to be tackled. Extremely clever minds are needed to define this energy, if it does exist.
A specific question derived here is whether the cell ‘walking’ is discrete or continuous when the overall trajectory is divided into cell generations. To answer this question, the very recent techniques of single cell profiling are needed.
3) A mechanistic question is how the rules of interaction between genes/regulators can be elaborated in molecular terms.
Referring to the belief that functions are determined by structures, we may have to go back to those trivial things like miRNAs, DNA methylation, histone modification, etc. But this time we will look into them from a brand new perspective and towards a more comprehensive understanding.
4) An even deeper and basic question is how the rules in question 3) and the all the mechanisms had evolved when multi-cellular organisms emerged in the world.
This should be part of Huang’s final goal in constructing his theory. I am very interested in this question, but I think it may not be solved within one or two decades. Anyway, one could be more optimistic because we are living in an accelerated era and we all can expect miracles.
Literatures:
Huang, S. (2010). Cell Lineage Determination in State Space: A Systems View Brings Flexibility to Dogmatic Canonical Rules. PLoS Biology, 8(5), e1000380. doi: 10.1371/journal.pbio.1000380
Huang, S. (2009). Reprogramming cell fates: reconciling rarity with robustness. BioEssays, 31(5), 546-560. doi: 10.1002/bies.200800189
Huang, S., Guo, Y.-P., May, G., & Enver, T. (2007). Bifurcation dynamics in lineage-commitment in bipotent progenitor cells. Developmental Biology, 305(2), 695-713. doi: 10.1016/j.ydbio.2007.02.036
Huang, S., Eichler, G., Bar-Yam, Y., & Ingber, D. (2005). Cell Fates as High-Dimensional Attractor States of a Complex Gene Regulatory Network. Physical Review Letters, 94(12), 1-4. doi: 10.1103/PhysRevLett.94.128701
在我眼中，HUANG Sui老师的研究属于非常前沿，既富于理论性，属基础研究，又离应用前景不远，很符合我的理想。其实本站博主周旭老师在一年多之前就已经介绍过这项研究，我只是继续跟进关注。
写完这篇博文之后，又在数据库中检索了一下，发现已经有很多相关研究，有一些跟我所提到的几个创新点有关，但重合不多。他们未必提到Huang老师的工作，因为做相关模型的也有其他人。
目前干细胞与癌症相关研究非常热门。我虽然对热门的东西不感冒，但是这次例外，因为这个领域即将出现微观生命科学中第一个统一性的理论。当然了，个人之见而已。
Dr. HUANG Sui at the University of Calgary has spent the last few years exemplifying and improving the State Space & Attractor theory of gene regulatory networks (GRN), which was initially proposed by Prof. Stuart KAUFFMAN from 1960’s. Incorporating the original concept of epigenetics (Waddington 1942) and methodology of systems biology, the theory seems surprisingly simple to be understood and, in my opinion, a promising framework for future stem cell and cancer researches.
Assuming each gene has two alternative states (ON or OFF), a genome containing N genes will have 2^N possible states, composing the so-called high-dimensional State Space. However, due to the mutual interactions between all the genes within a genome, some positions in the space are impossible to occur, and the realistic positions of the genome expression profile are limited to the space surrounding some lines, or ‘trajectories’. In the whole life of a cell, its genome expression profile is like ‘walking’ through these trajectories within the presumed state space.
What’s more, there are ‘attractors’ on the way of the trajectories. This means some positions in the state space are the most likely to occur to a cell; they are like black holes in the cosmos and any walking-by cells will be attracted towards them. If we were given a known genome and the information about all the interactions between the genes involved, we could be able to determine what the trajectories look like and where the attractors are located within the state space.
Unsurprisingly, these attractors could correspond to different cell types (or cell fates) in terms of cell development. In an analogy from Huang and Kauffman, a cell as a pluripotent progenitor is like to be at a mountain top, and its daughter cells will just ‘fall’ into surrounding valleys driven by the imaginary ‘potential energy’. Each valley is literally an attractor, and cells ‘falling’ into different valleys will turn to be different types of cells. This is not only an analogy now because it is already well formulated and supported by data from Huang and other scientists’ studies. (See Figure 1 from Huang 2009.)
Figure I. A diagram of the 'mountain and valley' analogy (from Huang 2009)
It remains a question whether genome expression profile can solely and exhaustively explain cell differentiation, I think. Anyway, case studies of a simple system were able to show that the expression profile of a pair of cross-inhibiting genes (GATA1 and PU.1) can sufficiently decide whether a colony of progenitor blood cells will develop to be red or white blood cells.
The theory seems an exciting blueprint from which a plural of more specific inferences can be derived, perhaps at first in the area of induced Pluripotent Stem (iPS) cells. Imagine if Dr. YAMANAKA Shinya could benefit from special ‘trajectories’ from this theory, he would be able to develop more efficient ways of cell induction and quality control, rather than just overexpressing some candidate genes and checking them in the culture media, and shortly he will be able to move those procedures from bench to factory.
Huang himself says that he aims at building up a unifying theory of multi-cellularity. I really appreciate his ambition. And again I agree that good works in basic (or pure) science never went against application research.
However, the present theory is still steps away from its final success. Several questions have to be answered to make it more rigorous and applicable.
1) The first question is how pluri/multipotency is maintained (and escaped) as the status of stem cells and all levels of progenitor cells.
Huang gave a possible explanation by providing a model in which auto-stimulation of cross-inhibiting genes leads to a ‘meta-stable’ state, which serves as an attractor as well. As shown in Figure 1, there is an assumed 'lake' on the mountaintop where the stem/pluri/multipotent cells are supposed to locate. But even if the pluripotent status is not an attractor, i.e., the 'lake' does not exist, we can still go on looking for mechanisms keeping cells there and driving them out of it.
2) The second question is how the imaginary ‘walking’ of cells along the trajectories is coupling with cell division. Are the ‘walking’ potential and the proliferation potential correlated with each other?
Considering the imaginary ‘potential energy’ in the ‘mountain and valley’ analogy, there is a possibility that the non-attractor status or the height of the mountain indeed provides a driving force for cell proliferation. If so, the ‘potential energy’ will turn out a realistic energy, not only an mathematical derivative in the abstract model. However, things are not so easy to be tackled. Extremely clever minds are needed to define this energy, if it does exist.
A specific question derived here is whether the cell ‘walking’ is discrete or continuous when the overall trajectory is divided into cell generations. To answer this question, the very recent techniques of single cell profiling are needed.
3) A mechanistic question is how the rules of interaction between genes/regulators can be elaborated in molecular terms.
Referring to the belief that functions are determined by structures, we may have to go back to those trivial things like miRNAs, DNA methylation, histone modification, etc. But this time we will look into them from a brand new perspective and towards a more comprehensive understanding.
4) An even deeper and basic question is how the rules in question 3) and the all the mechanisms had evolved when multi-cellular organisms emerged in the world.
This should be part of Huang’s final goal in constructing his theory. I am very interested in this question, but I think it may not be solved within one or two decades. Anyway, one could be more optimistic because we are living in an accelerated era and we all can expect miracles.
Literatures:
Huang, S. (2010). Cell Lineage Determination in State Space: A Systems View Brings Flexibility to Dogmatic Canonical Rules. PLoS Biology, 8(5), e1000380. doi: 10.1371/journal.pbio.1000380
Huang, S. (2009). Reprogramming cell fates: reconciling rarity with robustness. BioEssays, 31(5), 546-560. doi: 10.1002/bies.200800189
Huang, S., Guo, Y.-P., May, G., & Enver, T. (2007). Bifurcation dynamics in lineage-commitment in bipotent progenitor cells. Developmental Biology, 305(2), 695-713. doi: 10.1016/j.ydbio.2007.02.036
Huang, S., Eichler, G., Bar-Yam, Y., & Ingber, D. (2005). Cell Fates as High-Dimensional Attractor States of a Complex Gene Regulatory Network. Physical Review Letters, 94(12), 1-4. doi: 10.1103/PhysRevLett.94.128701
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