Dynamical-Systems Perspective to Stem-cell Biology: Relevance of oscillatory gene expression dynamics and cell-cell interaction

Transcription

1 Dynamical-Systems Perspective to Stem-cell Biology: Relevance of oscillatory gene expression dynamics and cell-cell interaction Kunihiko Kaneko Universal Biology Inst., Center for Complex-Systems Biology, University of Tokyo *Oscillatory expression ~ pluripotency? (20 years ago) *Pluripotency by oscillator expression (revisit) *Robustness in Cell differentiation process *Epigenetic Fixation and induced Pluripotency Minimalist (Poor Physicist s) Approach

2 Complex-Systems Biology : Consistency between different levels as guiding principle Ecosystem Evolutionary relationship on Robustness and Fluctuation Multicelluarity Genotype Phenotype Consistency between Multicelluar development and cell reprodcution Cell Adaptation as a result of consistency between cell growth and gene expression dynamics Molecule Gene regulation network Consistency between Cell reproduction & molecule replication Stochsatic dynamics Catalytic reaction network

3 Waddington s image on Cell Differentiation Waddington s Canalization (stability of each cell type) How genes guide this? phase-space diagram of development Cell types as attractors (cf Kauffman)

4 1 Dynamical Systems s View Cellular State Expression of Proteins P1 P2 P3 P4 Cellular state as a point in N-dimensional space P1 P2 proteinp2 proteinp3 Mutual Activation /Inhibition GRN Representation ti by differential eq. Temporal Evolution= Orbit

5 Multiple attractors in 1-cell dynamics cell types (Kauffman,,,) Limit -- How initial condition for each attractor is chosen? Just by noise?? Stability of differentiation process (Homeorhesis)?Stability of cell number ratio?irreversible Loss of Potency Sui Huang Bioessay 2008 (Stemness) Relevance of cell-cell interaction? Stem cell = proliferate ( stable ) & differentiate to other type(s) = ( unstable ) ---- how compatible?

6 Simple abstract model for cell differentiation (KK-Yomo ,Furusawa-KK 98-02) Intra-cellular reaction dynamics + Growth and Cell division + Cell-cell interaction dx dt m f x x x 1 2 k m(,,.., ) GROWTH Divisoin Coupled Dynamical Systems with cell-number growth Oscillations in protein concentrations in time Differentiation irreversible and robust developmental process based on the study of coupled dynamical systems (cf, KK s)

7 Isologous Diversification (KK,Yomo 94(Physica D), 97(B Math Bio ), 99 (J Theor. Biol) Assuming oscillatory dynamics as a single cell Chemical 2 Chemical 1 Synchronous division: no differentiation Instability of homogeneous state through cell-cell interaction Formation of discrete types with different chemical compositions: stabilize each other recursive production

8 Oscillation with transition of states ~ stemness ( differentiate + proliferate) + cell-cell interaction with the cell number increase Hierarchical Differentiation (Furusawa, KK 98,2001)

9 A simple model of multicellular development activation repression Screening of regulatory networks that can generate cell type diversity. Extract general features independent of details of modeling. cell cell interaction (diffusion of proteins) [1] N. Suzuki, C. Furusawa, and K. Kaneko, PLoS One, 6(11), e27232, 2011 [2] C. Furusawa and K. Kaneko, Science, 338(6104), 215-7, 2012

10 A cell model with on/off switching expression dynamics Cellular State mrna expression levels protein expression levels m, m, 2, 1 p, p 2,, 1 m n p n Dynamics of mrna expressions p j activation i th gene dm dt i 1 H j m H i p p j H: Hill coef. (=2) p j repression dm dt H i i th gene p i 1 1 j m p j repression i th gene p k activation dm dt i 1 1 p j H 1 p k p k H H m i Or we adopted thershold function model tanh( Jij pj) synthesis degradation

11 A cell model with on/off switching expression dynamics Dynamics of protein expressions dp dt i m synthesis i p i D i p degradation i p i diffution through the membrane, Di pi : : constant protein concentration in environment For example: dm dt 1 1 p 2 p 2 H H m 1 dm dt p 3 H 1 p 2 p 2 H H m 2 dm dt 3 1 H p1 p 1 H m 3 dp dt 1 m1 p p 1 D1 p1 1 : :

12 Screening regulatory networks Screening regulatory networks that can maintain multiple cell types by simulating all possible regulatory networks (~ networks) 5 genes, 10 regulatory paths cell cell interaction (diffusion of proteins) [1] N. Suzuki, C. Furusawa, and K. Kaneko, PLoS One, 6(11), e27232, 2011 [2] C. Furusawa and K. Kaneko, Science, 338(6104), 215-7, 2012

13 3Simulations of all GRN with 5 gene and 10 paths S 145,269,760 Differntiated at 32 i networks m cells (14,997) A:Turing-type( no stem cells both with proliferation & differentiation u l a Type A-I(fixed pt-> differentiated at 2 cells, fixed)~3600 Overlaid plot of given protein conc Type A-II(oscillation diff. at 2) ~11000 B:Itinerant dynamics+ Interaction=>stem cell Type B-I(oscillaion-> instability-> differentiation) ~200 Type B-II(chaotic oscillation differntiation) ~10

14 TypeA: Turing ( diffusion of inhibitor + activator) 3 Expression level 1 Type A1 ^diffusive Expression level Type A-II time <-diffusive 1 50 time No cells that satisfy both prolifereation and differentiation stem

15 3 typeb=stem-cell=self-renewal+differentiation more than single differentiations observed with the increase of cell number 3:diffu sive Type B-I( phase of oscillations differentiated-> 1 instability-> then differenciate) Expression level Expression) level 1 time 0:diffusive time

16 Movie is available at youtube. Search with the words Suzuki, Furusawa, Kaneko Differentiated Type (self-renew only) Stem Cell type Oscillation Self-renew+ differentiation

17 Dynamical Systems Mechanism Cell number Mutually stabilize Oscillatory Dynamics Desynchronized irregular oscillation by cell-cell interaction some cells switch to a novel state (bifurcation & stabilized by interaction) Robustness of number ratio of each cell type: differentiation or self-renewal depends on the number ratio of each cell type autonomous regulation

18 Turing-type Turingoscillation type Oscillation death Transient differentiation Just scattering of phases Repeated Differentiation from STEM cell

19 Common Network Structure for Stemness --Combination of Oscillation & Switch Modules Oscillation: (Plural) negative feedback loops Switch: Positive Plural is better for complex oscillation, needed to keep desynchronization (Turing type) 3-gene examples

20 Minimal GRN of 2 proteins (bit narrow in parameter range) (Goto,KK,Phys.Rev.E,2013) Nullcline Analysis ; generation of fixed point by cell-cell interaction Interaction Oscillatory to Fixed point

21 Cf: Oscillation + Spatially Local Interaction by diffusion +Fixed Boundary Temporal Oscillation is Transformed into Spatial Stripe (EuroPhys Lett. 2017) Relevant to Somitogenesis?? Time Space Homogeneous Oscillation is stable but by fixed boundary condition Temporal oscillation is transformed to spatial pattern This is predicted by spatial map

22 Comparison with the stochastic switching among multistationary states Alternative view; Multi-fixed points + switch by noise (commonly found if higher noise) (i)robustness in number-ratio of cell-types: difficult (ii) needs fine tuning of noise level Ours: (i) robust cell number ratio (ii)robust Developmental course (iii) Robust to noise level (cf Pfeuty-kk) (iv)diversification with hierarchic differentiation easy

23 Design of hierarchical differentiation to multiple cell types (Combination of Oscillation+ Switch Modules) Combine in Parallel S A or B or C Oscillation Module Combine in Sequence: S->A->A1 On/off Switch module More complex hierarchical differentiation can be designed

24 Stable HierarchicalDifferentiation pa ps pb Ratio A decreased then Differentiation ration S A is increased Stable ratio among cell types (Furusawa, KK 98,2001) Gene Expression dynamics in stem cell = Oscillatory with transition of several states + cell-cell interaction robust differentiation Loss of Pluripotency== Loss of such dynamics

25 Experimental Verification? Pluripotency characterized by (i) diversity of expressed genes (ii) Larger cell-cell variation (exp. Heterogeneity confirmed) (iii) Oscillation in gene expression (Chambers et alnature07) Experimental confirmation Oscillation of Hes1 expression~4hr for ES Lost when differentiated Kobayashi et al. Genes Development 2009 Gene expression dynamics Itinerancy over several states Chang et al (Nature 08)

26 To recover Stemness increase in degrees of freedom (Furusawa,KK 2001)? Yamanaka s ips (2006)by expressing 4 genes

27 Further Stabilization by Epigenetic change Epigenetic Fixation (methylation etc ) protein composition change (expression level) embedded into epigenetic change (e.g., histon modification) Epigenetic Feedback model : Expressed then threshold for expression decreases (cf Furusawa,KK, Plos One 2013) Differentiation is irreversibly fixed as if ball deepens the valley of potential ε feedback rate Or, in the form of Hill

28 Confirmation by a Model Based on observed GRN x1 x1 time Epigenetic Feedback Regulation Recovery of Pluripotency requires compulsive expression of several genes

29 Differentiation then is embedded into epigenetic change (threshold) It works if the time scale of epigenetic change is slower (but not too slow) Weak-interaction case Timescale for epigenetic change (log) Strong-interaction case

30 Reprogramming possible by over expressing a few genes Taking differentiated cells with epigenetic fixation, and overexpressing a few (4 in this case) genes, they come back to the pluripotent cells with oscillation (The 4 happen to agree with Yamanaka s factor, but could be else)

31 Degree of overexpression ( time amount) should be in a certain range

32 Speculation on Cancer State(?): (KK,Bioessays2011) (1)Through evolution, robustness to noise leads to robustness to mutation for normal cells (kk, Plos One 2007) (2)For complex GRN, there exists aberrant attracting states (cf. Kauffman,1971) (3)(i)The states no stabilizing relationship with other cells ( selfish )-loss of consistency (ii) Not robust to mutation, since they are not under selection in evolution With mutations, robustness is aquired thus mutations can be accumulated (iv) Due to lack of robustness to noise, the phenotypes will be heterogeneous ( over cells) Cancer: loss of robustness and consistency

33 Stem-Cell differentiation: Oscillatory dynamics + Cell-cell interaction Desynchronized differentiation through bifurcation Irreversible loss of pluripotency --- Robustness at cellular and multi-cellular level Epigenetic Fixation Cancer: From Aberrant Attractor losing Robustness Collaborators: Chikara Furusawa (RIKEN QBiC) Tadashi Miyamoto Narito Suzuki, Yusuke Goto Most papers available at