letters to nature typically slower than 1 km s-1 -RRB- might differ significantly from what is assumed by current modelling efforts27 . The expected equation-of-state differences among small bodies -LRB- ice versus rock , for instance -RRB- presents another dimension of study ; having recently adapted our code for massively parallel architectures -LRB- K. M. Olson and E.A , manuscript in preparation -RRB- , we are now ready to perform a more comprehensive analysis . The exploratory simulations presented here suggest that when a young , non-porous asteroid -LRB- if such exist -RRB- suffers extensive impact damage , the resulting fracture pattern largely defines the asteroid 's response to future impacts . The stochastic nature of collisions implies that small asteroid interiors may be as diverse as their shapes and spin states . Detailed numerical simulations of impacts , using accurate shape models and rheologies , could shed light on how asteroid collisional response depends on internal configuration and shape , and hence on how planetesimals evolve . Detailed simulations are also required before one can predict the quantitative effects of nuclear explosions on Earth-crossing comets and asteroids , either for hazard mitigation28 through disruption and deflection , or for resource exploitation29 . Such predictions would require detailed reconnaissance concerning the composition and internal structure of the targeted object . Received 4 February ; accepted 18 March 1998 . 1 . Asphaug , E. & Melosh , H. J . The Stickney impact of Phobos : A dynamical model . Icarus 101 , 144 164 -LRB- 1993 -RRB- . 2 . Asphaug , E. et al. . Mechanical and geological effects of impact cratering on Ida . Icarus 120 , 158 184 -LRB- 1996 -RRB- . 3 . Nolan , M. C. , Asphaug , E. , Melosh , H. J. & Greenberg , R. Impact craters on asteroids : Does strength or gravity control their size ? Icarus 124 , 359 371 -LRB- 1996 -RRB- . 4 . Love , S. J. & Ahrens , T. J. Catastrophic impacts on gravity dominated asteroids . Icarus 124 , 141 155 -LRB- 1996 -RRB- . 5 . Melosh , H. J. & Ryan , E. V. Asteroids : Shattered but not dispersed . Icarus 129 , 562 564 -LRB- 1997 -RRB- . 6 . Housen , K. R. , Schmidt , R. M. & Holsapple , K. A. Crater ejecta scaling laws : Fundamental forms based on dimensional analysis . J. Geophys . Res . 88 , 2485 2499 -LRB- 1983 -RRB- . 7 . Holsapple , K. A. & Schmidt , R. M. Point source solutions and coupling parameters in cratering mechanics . J. Geophys . Res . 92 , 6350 6376 -LRB- 1987 -RRB- . 8 . Housen , K. R. & Holsapple , K. A. On the fragmentation of asteroids and planetary satellites . Icarus 84 , 226 253 -LRB- 1990 -RRB- . 9 . Benz , W. & Asphaug , E. Simulations of brittle solids using smooth particle hydrodynamics . Comput . Phys . Commun . 87 , 253 265 -LRB- 1995 -RRB- . 10 . Asphaug , E. et al. . Mechanical and geological effects of impact cratering on Ida . Icarus 120 , 158 184 -LRB- 1996 -RRB- . 11 . Hudson , R. S. & Ostro , S. J. Shape of asteroid 4769 Castalia -LRB- 1989 PB -RRB- from inversion of radar images . Science 263 , 940 943 -LRB- 1994 -RRB- . 12 . Ostro , S. J. et al. . Asteroid radar astrometry . Astron . J. 102 , 1490 1502 -LRB- 1991 -RRB- . 13 . Ahrens , T. J. & O'Keefe , J. D. in Impact and Explosion Cratering -LRB- eds Roddy , D. J. , Pepin , R. O. & Merrill , R. B. -RRB- 639 656 -LRB- Pergamon , New York , 1977 -RRB- . 14 . Tillotson , J. H. Metallic equations of state for hypervelocity impact . -LRB- General Atomic Report GA-3216 , San Diego , 1962 -RRB- . 15 . Nakamura , A. & Fujiwara , A. Velocity distribution of fragments formed in a simulated collisional disruption . Icarus 92 , 132 146 -LRB- 1991 -RRB- . 16 . Benz , W. & Asphaug , E. Simulations of brittle solids using smooth particle hydrodynamics . Comput . Phys . Commun . 87 , 253 265 -LRB- 1995 -RRB- . 17 . Bottke , W. F. , Nolan , M. C. , Greenberg , R. & Kolvoord , R. A. Velocity distributions among colliding asteroids . Icarus 107 , 255 268 -LRB- 1994 -RRB- . 18 . Belton , M. J. S. et al. . Galileo encounter with 951 Gaspra -- First pictures of an asteroid . Science 257 , 1647 1652 -LRB- 1992 -RRB- . 19 . Belton , M. J. S. et al. . Galileo 's encounter with 243 Ida : An overview of the imaging experiment . Icarus 120 , 1 19 -LRB- 1996 -RRB- . 20 . Asphaug , E. & Melosh , H. J . The Stickney impact of Phobos : A dynamical model . Icarus 101 , 144 164 -LRB- 1993 -RRB- . 21 . Asphaug , E. et al. . Mechanical and geological effects of impact cratering on Ida . Icarus 120 , 158 184 -LRB- 1996 -RRB- . 22 . Housen , K. R. , Schmidt , R. M. & Holsapple , K. A. Crater ejecta scaling laws : Fundamental forms based on dimensional analysis . J. Geophys . Res . 88 , 2485 2499 -LRB- 1983 -RRB- . 23 . Veverka , J. et al. . NEAR 's flyby of 253 Mathilde : Images of a C asteroid . Science 278 , 2109 2112 -LRB- 1997 -RRB- . 24 . Asphaug , E. et al. . Impact evolution of icy regoliths . Lunar Planet . Sci . Conf . -LRB- Abstr . -RRB- XXVIII , 63 64 -LRB- 1997 -RRB- . 25 . Love , S. G. , Horz , F. & Brownlee , D. E. Target porosity effects in impact cratering and collisional disruption . Icarus 105 , 216 224 -LRB- 1993 -RRB- . 26 . Fujiwara , A. , Cerroni , P. , Davis , D. R. , Ryan , E. V. & DiMartino , M. in Asteroids II -LRB- eds Binzel , R. P. , Gehrels , T. & Matthews , A. S. -RRB- 240 265 -LRB- Univ. . Arizona Press , Tucson , 1989 -RRB- . 27 . Davis , D. R. & Farinella , P. Collisional evolution of Edgeworth-Kuiper Belt objects . Icarus 125 , 50 60 -LRB- 1997 -RRB- . 28 . Ahrens , T. J. & Harris , A. W. Deflection and fragmentation of near-Earth asteroids . Nature 360 , 429 433 -LRB- 1992 -RRB- . 29 . Resources of Near-Earth Space -LRB- eds Lewis , J. S. , Matthews , M. S. & Guerrieri , M. L. -RRB- -LRB- Univ. . Arizona Press , Tucson , 1993 -RRB- . Acknowledgements . This work was supported by NASA 's Planetary Geology and Geophysics Program . Correspondence and requests for materials should be addressed to E.A. -LRB- e-mail : asphaug@earthsci.ucsc . edu -RRB- . * Present address : Paul F. Lazarsfeld Center for the Social Sciences , Columbia University , 812 SIPA Building , 420 W118 St , New York , New York 10027 , USA . Collective dynamics of ` small-world ' networks Duncan J. Watts * & Steven H. Strogatz Department of Theoretical and Applied Mechanics , Kimball Hall , Cornell University , Ithaca , New York 14853 , USA ... 8 Networks of coupled dynamical systems have been used to model biological oscillators1 4 , Josephson junction arrays5 ,6 , excitable media7 , neural networks8 10 , spatial games11 , genetic control networks12 and many other self-organizing systems . Ordinarily , the connection topology is assumed to be either completely regular or completely random . But many biological , technological and social networks lie somewhere between these two extremes . Here we explore simple models of networks that can be tuned through this middle ground : regular networks ` rewired ' to introduce increasing amounts of disorder . We find that these systems can be highly clustered , like regular lattices , yet have small characteristic path lengths , like random graphs . We call them ` small-world ' networks , by analogy with the small-world phenomenon13 ,14 -LRB- popularly known as six degrees of separation15 -RRB- . The neural network of the worm Caenorhabditis elegans , the power grid of the western United States , and the collaboration graph of film actors are shown to be small-world networks . Models of dynamical systems with small-world coupling display enhanced signal-propagation speed , computational power , and synchronizability . In particular , infectious diseases spread more easily in small-world networks than in regular lattices . To interpolate between regular and random networks , we consider the following random rewiring procedure -LRB- Fig. 1 -RRB- . Starting from a ring lattice with n vertices and k edges per vertex , we rewire each edge at random with probability p . This construction allows us to ` tune ' the graph between regularity -LRB- p 0 -RRB- and disorder -LRB- p 1 -RRB- , and thereby to probe the intermediate region 0 p 1 , about which little is known . We quantify the structural properties of these graphs by their characteristic path length L -LRB- p -RRB- and clustering coefficient C -LRB- p -RRB- , as defined in Fig. 2 legend . Here L -LRB- p -RRB- measures the typical separation between two vertices in the graph -LRB- a global property -RRB- , whereas C -LRB- p -RRB- measures the cliquishness of a typical neighbourhood -LRB- a local property -RRB- . The networks of interest to us have many vertices with sparse connections , but not so sparse that the graph is in danger of becoming disconnected . Specifically , we require n q k q ln n q 1 , where k q ln n guarantees that a random graph will be connected16 . In this regime , we find that L n = 2k q 1 and C 3 = 4 as p 0 , while L Lrandom ln n = ln k and C C random k = n p 1 as p 1 . Thus the regular lattice at p 0 is a highly clustered , large world where L grows linearly with n , whereas the random network at p 1 is a poorly clustered , small world where L grows only logarithmically with n . These limiting cases might lead one to suspect that large C is always associated with large L , and small C with small L. On the contrary , Fig. 2 reveals that there is a broad interval of p over which L -LRB- p -RRB- is almost as small as Lrandom yet C p q Crandom . These small-world networks result from the immediate drop in L -LRB- p -RRB- caused by the introduction of a few long-range edges . Such ` short cuts ' connect vertices that would otherwise be much farther apart than Lrandom . For small p , each short cut has a highly nonlinear effect on L , contracting the distance not just between the pair of vertices that it connects , but between their immediate neighbourhoods , neighbourhoods of neighbourhoods and so on . By contrast , an edge 440 Nature Macmillan Publishers Ltd 1998 NATURE | VOL 393 | 4 JUNE 1998 letters to nature removed from a clustered neighbourhood to make a short cut has , at most , a linear effect on C ; hence C -LRB- p -RRB- remains practically unchanged for small p even though L -LRB- p -RRB- drops rapidly . The important implication here is that at the local level -LRB- as reflected by C -LRB- p -RRB- -RRB- , the transition to a small world is almost undetectable . To check the robustness of these results , we have tested many different types of initial regular graphs , as well as different algorithms for random rewiring , and all give qualitatively similar results . The only requirement is that the rewired edges must typically connect vertices that would otherwise be much farther apart than Lrandom . The idealized construction above reveals the key role of short cuts . It suggests that the small-world phenomenon might be common in sparse networks with many vertices , as even a tiny fraction of short cuts would suffice . To test this idea , we have computed L and C for the collaboration graph of actors in feature films -LRB- generated from data available at http://us.imdb.com -RRB- , the electrical power grid of the western United States , and the neural network of the nematode worm C. elegans17 . All three graphs are of scientific interest . The graph of film actors is a surrogate for a social network18 , with the advantage of being much more easily specified . It is also akin to the graph of mathematical collaborations centred , traditionally , on P. Erdos -LRB- partial data available at http : / / www.acs.oakland.edu / grossman/erdoshp.html -RRB- . The graph of the power grid is relevant to the efficiency and robustness of power networks19 . And C. elegans is the sole example of a completely mapped neural network . Table 1 shows that all three graphs are small-world networks . These examples were not hand-picked ; they were chosen because of their inherent interest and because complete wiring diagrams were available . Thus the small-world phenomenon is not merely a curiosity of social networks13 ,14 nor an artefact of an idealized model -- it is probably generic for many large , sparse networks found in nature . We now investigate the functional significance of small-world connectivity for dynamical systems . Our test case is a deliberately simplified model for the spread of an infectious disease . The population structure is modelled by the family of graphs described in Fig. 1 . At time t 0 , a single infective individual is introduced into an otherwise healthy population . Infective individuals are removed permanently -LRB- by immunity or death -RRB- after a period of sickness that lasts one unit of dimensionless time . During this time , each infective individual can infect each of its healthy neighbours with probability r. On subsequent time steps , the disease spreads along the edges of the graph until it either infects the entire population , or it dies out , having infected some fraction of the population in the process . 8 Table 1 Empirical examples of small-world networks ... . Lactual Lrandom 2.99 12.4 2.25 Cactual Crandom ... . Characteristic path length L and clustering coefficient C for three real networks , compared to random graphs with the same number of vertices -LRB- n -RRB- and average number of edges per vertex -LRB- k -RRB- . -LRB- Actors : n 225 ; 226 , k 61 . Power grid : n 4 ; 941 , k 2:67 . C. elegans : n 282 , k 14 . -RRB- The graphs are defined as follows . Two actors are joined by an edge if they have acted in a film together . We restrict attention to the giant connected component16 of this graph , which includes 90 % of all actors listed in the Internet Movie Database -LRB- available at http://us.imdb.com -RRB- , as of April 1997 . For the power grid , vertices represent generators , transformers and substations , and edges represent high-voltage transmission lines between them . For C. elegans , an edge joins two neurons if they are connected by either a synapse or a gap junction . We treat all edges as undirected and unweighted , and all vertices as identical , recognizing that these are crude approximations . All three networks show the small-world phenomenon : L Lrandom but C q Crandom . Film actors Power grid C. elegans 3.65 18.7 2.65 0.79 0.080 0.28 0.00027 0.005 0.05 1 Regular Small-world Random 0.8 C -LRB- p -RRB- / C -LRB- 0 -RRB- 0.6 0.4 0.2 L -LRB- p -RRB- / L -LRB- 0 -RRB- p = 0 Increasing randomness p = 1 0 0.0001 0.001 0.01 0.1 1 p Figure 2 Characteristic path length L -LRB- p -RRB- and clustering coefficient C -LRB- p -RRB- for the family of randomly rewired graphs described in Fig. 1 . Here L is defined as the number of edges in the shortest path between two vertices , averaged over all pairs of vertices . The clustering coefficient C -LRB- p -RRB- is defined as follows . Suppose that a vertex v has kv neighbours ; then at most kv kv 1 = 2 edges can exist between them -LRB- this occurs when every neighbour of v is connected to every other neighbour of v -RRB- . Let Cv denote the fraction of these allowable edges that actually exist . Define C as the average of Cv over all v. For friendship networks , these statistics have intuitive meanings : L is the average number of friendships in the shortest chain connecting two people ; Cv reflects the extent to which friends of v are also friends of each other ; and thus C measures the cliquishness of a typical friendship circle . The data shown in the figure are averages over 20 random realizations of the rewiring process described in Fig. 1 , and have been normalized by the values L -LRB- 0 -RRB- , C -LRB- 0 -RRB- for a regular lattice . All the graphs have n 1 ; 000 vertices and an average degree of k 10 edges per vertex . We note that a logarithmic horizontal scale has been used to resolve the rapid drop in L -LRB- p -RRB- , corresponding to the onset of the small-world phenomenon . During this drop , C -LRB- p -RRB- remains almost constant at its value for the regular lattice , indicating that the transition to a small world is almost undetectable at the local level . Figure 1 Random rewiring procedure for interpolating between a regular ring lattice and a random network , without altering the number of vertices or edges in the graph . We start with a ring of n vertices , each connected to its k nearest neighbours by undirected edges . -LRB- For clarity , n 20 and k 4 in the schematic examples shown here , but much larger n and k are used in the rest of this Letter . -RRB- We choose a vertex and the edge that connects it to its nearest neighbour in a clockwise sense . With probability p , we reconnect this edge to a vertex chosen uniformly at random over the entire ring , with duplicate edges forbidden ; otherwise we leave the edge in place . We repeat this process by moving clockwise around the ring , considering each vertex in turn until one lap is completed . Next , we consider the edges that connect vertices to their second-nearest neighbours clockwise . As before , we randomly rewire each of these edges with probability p , and continue this process , circulating around the ring and proceeding outward to more distant neighbours after each lap , until each edge in the original lattice has been considered once . -LRB- As there are nk/2 edges in the entire graph , the rewiring process stops after k/2 laps . -RRB- Three realizations of this process are shown , for different values of p. For p 0 , the original ring is unchanged ; as p increases , the graph becomes increasingly disordered until for p 1 , all edges are rewired randomly . One of our main results is that for intermediate values of p , the graph is a small-world network : highly clustered like a regular graph , yet with small characteristic path length , like a random graph . -LRB- See Fig. 2 . -RRB- NATURE | VOL 393 | 4 JUNE 1998 Nature Macmillan Publishers Ltd 1998 441 letters to nature Two results emerge . First , the critical infectiousness rhalf , at which the disease infects half the population , decreases rapidly for small p -LRB- Fig. 3a -RRB- . Second , for a disease that is sufficiently infectious to infect the entire population regardless of its structure , the time T -LRB- p -RRB- required for global infection resembles the L -LRB- p -RRB- curve -LRB- Fig. 3b -RRB- . Thus , infectious diseases are predicted to spread much more easily and quickly in a small world ; the alarming and less obvious point is how few short cuts are needed to make the world small . Our model differs in some significant ways from other network models of disease spreading20 24 . All the models indicate that network structure influences the speed and extent of disease transmission , but our model illuminates the dynamics as an explicit function of structure -LRB- Fig. 3 -RRB- , rather than for a few particular topologies , such as random graphs , stars and chains20 23 . In the work closest to ours , Kretschmar and Morris24 have shown that increases in the number of concurrent partnerships can significantly accelerate the propagation of a sexually-transmitted disease that spreads along the edges of a graph . All their graphs are disconnected because they fix the average number of partners per person at k 1 . An increase in the number of concurrent partnerships causes faster spreading by increasing the number of vertices in the graph 's largest connected component . In contrast , all our graphs are connected ; hence the predicted changes in the spreading dynamics are due to more subtle structural features than changes in connectedness . Moreover , changes in the number of concurrent partners are obvious to an individual , whereas transitions leading to a smaller world are not . We have also examined the effect of small-world connectivity on three other dynamical systems . In each case , the elements were coupled according to the family of graphs described in Fig. 1 . -LRB- 1 -RRB- For cellular automata charged with the computational task of density classification25 , we find that a simple ` majority-rule ' running on a small-world graph can outperform all known human and genetic algorithm-generated rules running on a ring lattice . -LRB- 2 -RRB- For the iterated , multi-player ` Prisoner 's dilemma '11 played on a graph , we find that as the fraction of short cuts increases , cooperation is less likely to emerge in a population of players using a generalized ` titfor-tat '26 strategy . The likelihood of cooperative strategies evolving out of an initial cooperative/non-cooperative mix also decreases with increasing p. -LRB- 3 -RRB- Small-world networks of coupled phase oscillators synchronize almost as readily as in the mean-field model2 , despite having orders of magnitude fewer edges . This result may be relevant to the observed synchronization of widely separated neurons in the visual cortex27 if , as seems plausible , the brain has a small-world architecture . We hope that our work will stimulate further studies of smallworld networks . Their distinctive combination of high clustering with short characteristic path length can not be captured by traditional approximations such as those based on regular lattices or random graphs . Although small-world architecture has not received much attention , we suggest that it will probably turn out to be widespread in biological , social and man-made systems , often with important dynamical consequences . Received 27 November 1997 ; accepted 6 April 1998 . 1 . Winfree , A. T . The Geometry of Biological Time -LRB- Springer , New York , 1980 -RRB- . 2 . Kuramoto , Y. Chemical Oscillations , Waves , and Turbulence -LRB- Springer , Berlin , 1984 -RRB- . 3 . Strogatz , S. H. & Stewart , I. 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Measures of concurrency in networks and the spread of infectious disease . Math . Biosci . 133 , 165 195 -LRB- 1996 -RRB- . 25 . Das , R. , Mitchell , M. & Crutchfield , J. P. in Parallel Problem Solving from Nature -LRB- eds Davido , Y. , Schwefel , H.-P . & Manner , R. -RRB- 344 353 -LRB- Lecture Notes in Computer Science 866 , Springer , Berlin , 1994 -RRB- . 26 . Axelrod , R . The Evolution of Cooperation -LRB- Basic Books , New York , 1984 -RRB- . 27 . Gray , C. M. , Konig , P. , Engel , A. K. & Singer , W. Oscillatory responses in cat visual cortex exhibit intercolumnar synchronization which reflects global stimulus properties . Nature 338 , 334 337 -LRB- 1989 -RRB- . Acknowledgements . We thank B. Tjaden for providing the film actor data , and J. Thorp and K. Bae for the Western States Power Grid data . This work was supported by the US National Science Foundation -LRB- Division of Mathematical Sciences -RRB- . Correspondence and requests for materials should be addressed to D.J.W. -LRB- e-mail : djw24@columbia.edu -RRB- . 8 a 0.35 0.3 r half 0.25 0.2 0.15 0.0001 0.001 0.01 0.1 1 p b 1 0.8 T -LRB- p -RRB- / T -LRB- 0 -RRB- L -LRB- p -RRB- / L -LRB- 0 -RRB- 0.6 0.4 0.2 0 0.0001 0.001 0.01 0.1 1 p Figure 3 Simulation results for a simple model of disease spreading . The community structure is given by one realization of the family of randomly rewired graphs used in Fig. 1 . a , Critical infectiousness rhalf , at which the disease infects half the population , decreases with p. b , The time T -LRB- p -RRB- required for a maximally infectious disease -LRB- r 1 -RRB- to spread throughout the entire population has essentially the same functional form as the characteristic path length L -LRB- p -RRB- . Even if only a few per cent of the edges in the original lattice are randomly rewired , the time to global infection is nearly as short as for a random graph . 442 Nature Macmillan Publishers Ltd 1998 NATURE | VOL 393 | 4 JUNE 1998

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O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O B O O O O O O B O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O B O O O O O O O B O O O O O O O O O O O B O O O O O O O O O O O O B O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O

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Vol 444 | 16 November 2006 | doi : 10.1038 / nature05284 LETTERS A protein interaction network for pluripotency of embryonic stem cells Jianlong Wang1 , Sridhar Rao1 , Jianlin Chu1 , Xiaohua Shen1 , Dana N. Levasseur1 , Thorold W. Theunissen1 & Stuart H. Orkin1 ,2 Embryonic stem -LRB- ES -RRB- cells are pluripotent1 ,2 and of therapeutic potential in regenerative medicine3 ,4 . Understanding pluripotency at the molecular level should illuminate fundamental properties of stem cells and the process of cellular reprogramming . Through cell fusion the embryonic cell phenotype can be imposed on somatic cells , a process promoted by the homeodomain protein Nanog5 , which is central to the maintenance of ES cell pluripotency6 ,7 . Nanog is thought to function in concert with other factors such as Oct4 -LRB- ref . 8 -RRB- and Sox2 -LRB- ref . 9 -RRB- to establish ES cell identity . Here we explore the protein network in which Nanog operates in mouse ES cells . Using affinity purification of Nanog under native conditions followed by mass spectrometry , we have identified physically associated proteins . In an iterative fashion we also identified partners of several Nanog-associated proteins -LRB- including Oct4 -RRB- , validated the functional relevance of selected newly identified components and constructed a protein interaction network . The network is highly enriched for nuclear factors that are individually critical for maintenance of the ES cell state and co-regulated on differentiation . The network is linked to multiple co-repressor pathways and is composed of numerous proteins whose encoding genes are putative direct transcriptional targets of its members . This tight protein network seems to function as a cellular module dedicated to pluripotency . To recover Nanog with its associated proteins , we used a biotinylation/proteomics approach10 . Nanog complementary DNA bearing an amino-terminal Flag epitope and a short peptide tag that serves as a substrate for in vivo biotinylation -LRB- Fig. 1a -RRB- was expressed at about 20 % of the endogenous level in ES cells previously engineered to express Escherichia coli biotin ligase BirA -LRB- Fig. 1b , left -RRB- . Low-level expression reduces the likelihood that non-physiological interactions will be identified or that the stoichiometry of protein complexes will be perturbed11 . Biotinylated Nanog -LRB- bioNanog -RRB- is efficiently recovered from ES cell nuclear extracts with streptavidin -LRB- SA -RRB- - agarose -LRB- Fig. 1b right -RRB- , and is biologically active , because its expression attenuates the dependence of ES cells on leukaemia inhibitory factor -LRB- LIF ; Supplementary Fig . S1 -RRB- . Cells coexpressing BirA and bioNanog are functionally equivalent to wild-type ES cells in stem-cell marker gene expression -LRB- Supplementary Fig . S1 -RRB- . On size fractionation of ES cell nuclear extracts , bioNanog and endogenous Nanog behave similarly , broadly distributed with an apparent molecular mass of more than 160 kDa to 1 MDa , far greater than that of the predicted polypeptide -LRB- 34 kDa -RRB- -LRB- Fig. 1c -RRB- . To identify Nanog-associated proteins we used single-step capture on streptavidin beads10 , as well as tandem purification with anti-Flag immunoprecipitation followed by capture with streptavidin . Nuclear extracts of ES cells expressing either BirA alone or BirA plus bioNanog were processed in parallel . Total peptides sequenced and proteins identified by whole-lane liquid chromatography tandem mass spectrometry -LRB- LC MS/MS -RRB- are summarized in Fig. 1d -LRB- left panel ; see also Supplementary Data -RRB- . With criteria described in the Supplementary Methods , putative Nanog-associated proteins were chosen -LRB- Fig. 1d , right panel -RRB- . The candidates , which are predominantly transcription factors or components of transcriptional complexes , include proteins previously studied in an ES cell context -LRB- for example Oct4 or Dax1 -RRB- and fall into three groups . The first group includes proteins present in at least two of three independent one-step purifications and tandem purification . These proteins -LRB- Sall1 , Sall4 , Rif1 , Tif1b , Mybbp , Dax1 and Nac1 -RRB- are prime interaction candidates . The second group includes proteins -LRB- Zfp281 , Err2 , Elys , Oct4 , Zfp198 , NF45 and HDAC2 -RRB- that may be part of unstable or transient complexes that dissociate during tandem purification . Proteins in the third group -LRB- REST , Sp1 and Wapl -RRB- seem ` masked ' in one-step purifications but are recovered in the tandem procedure . Proteins identified by our approach may interact directly with Nanog , or more often indirectly through their association with other components of a protein complex . We then validated selected Nanog-interacting candidates by performing co-immunoprecipitation experiments . Interactions between Nanog and Dax1 , Nac1 , Zfp281 and Oct4 were confirmed in heterologous 293T -LRB- Supplementary Fig . S2 -RRB- and ES -LRB- Fig. 2a d -RRB- cells transiently transfected with constructs as indicated -LRB- see the figure legend for details -RRB- . In addition , we generated ES cells expressing biotinylated Nac1 , Zfp281 , Dax1 and Oct4 , at or below endogenous protein levels -LRB- Supplementary Fig . S3 -RRB- , for affinity capture with anti-streptavidinagarose and western blotting with anti-streptavidin horseradish peroxidase -LRB- HRP -RRB- antibody . We confirmed that Nanog co-purifies with bio Nac1 , bioZfp281 , bioDax1 and bioOct4 -LRB- Fig. 2e -RRB- and that Nac1 copurifies with bioNanog -LRB- Fig. 2f -RRB- . Furthermore , we confirmed the association of Rif1 with endogenous Nanog -LRB- Fig. 2g -RRB- , as well as ectopically expressed Nanog -LRB- Fig. 2h , i -RRB- . To test the functional relevance of selected components , we employed inhibition of endogenous RNAs by short hairpin RNA -LRB- shRNA ; Supplementary Fig . S4 -RRB- . If Nanog-associated proteins influence Nanog 's transcriptional activity , their loss of function would be expected to affect ES cell pluripotency . We first examined shRNAs directed to Dax1 and Sall4 in ES cells that express green fluorescent protein -LRB- GFP -RRB- under the control of Oct4 regulatory elements . In both instances a loss of pluripotency was observed , as revealed by diminished Oct4 expression and concomitant derepression of selected lineage-specific markers -LRB- Supplementary Fig . S5 -RRB- . Recent conditional gene targeting of Dax1 -LRB- ref . 12 -RRB- and Sall4 -LRB- ref . 13 -RRB- provides independent support for their crucial function in ES cells . Further functional validation included shRNA inhibition of two Nanog-associated proteins , Nac1 and Zfp281 , not previously 1 Division of Hematology Oncology , Children 's Hospital and Dana Farber Cancer Institute , Harvard Medical School , Harvard Stem Cell Institute , 2Howard Hughes Medical Institute , Boston , Massachusetts 02115 , USA . 364 2006 Nature Publishing Group NATURE | Vol 444 | 16 November 2006 LETTERS examined in ES cells . Nac1 is a BTB-domain containing protein14 ,15 related to Drosophila bric-a-brac/tramtrack , which prevents inappropriate neural gene expression . Zfp281 , the mouse homologue of human zinc-finger protein ZBP99 , may regulate cell proliferation , differentiation and oncogenesis16 . We infected wild-type ES cells with retrovirus containing an shRNA vector carrying a GFP cassette -LRB- Supplementary Fig . S4 -RRB- and isolated GFPhigh clones harbouring Nac1 and Zfp281 shRNAs . Two clones each with similar extents of RNA knockdown -LRB- about 80 % for Nac1 and about 70 % for Zfp281 ; Fig. 3a -RRB- were studied in detail . Nac1 or Zfp281 knockdown cells maintained on a feeder layer formed small colonies , yet they retained proper ES cell morphology -LRB- Fig. 3b , top panels -RRB- . On passage to gelatin in the presence of LIF , knockdown cells grew poorly and formed disorganized clumps of small cells -LRB- Fig. 3b , bottom panels -RRB- . Striking derepression of primitive endoderm -LRB- Gata6/4 -RRB- , mesoderm/visceral endoderm -LRB- Bmp2 -RRB- and neuroectoderm -LRB- Isl1 -RRB- markers was observed , despite normal expression of the stem-cell markers -LRB- Nanog , Oct4 and Rex1 ; Fig. 3c -RRB- . Validation of these findings was achieved through the use of an independent shRNA directed to Zfp281 and by examination of gene-targeted Nac11/2 ES cells -LRB- Supplementary Figs S4 and S6 -RRB- . To assess the relevance of Nac1 and Zfp281 with respect to transcriptional control , we examined chromatin occupancy of these proteins at the Gata6 promoter in wild-type ES cells . As shown in Fig. 3d , Nac1 and Zfp281 , as well as Nanog , are highly enriched at the Gata6 promoter . These data strongly implicate Nac1 and Zpf281 , along with Nanog , in the tight control of this crucial target gene and also show that derepression of Gata6 expression in knockdown cells is not due to off-target effects of shRNAs . The broad pattern of Nanog on size fractionation , and the identification and validation , both physically and functionally , of associated proteins suggest that Nanog is a component of multiple protein complexes . By performing similar proteomic analyses on several of the Nanog-associated proteins , as well as another stemcell marker protein Rex1 -LRB- ref . 17 -RRB- , we sought to identify additional previously unknown proteins and components shared between complexes and to develop a protein network -LRB- Fig. 4a -RRB- . The size distributions of complexes containing Oct4 , Dax1 , Nac1 , Zfp281 and Rex1 overlap that of Nanog -LRB- Supplementary Fig . S7 -RRB- . We employed ES cell lines expressing bioDax1 , bioNac1 , bioZfp281 , bio Oct4 and bioRex1 -LRB- Fig. 2e , and Supplementary Fig . S3 -RRB- for the a MSGLNDIFEAQKIEWHEGAPSSR Bio b Total lysates BirA + + + bioNanog bioNanog NE IP anti-SAagarose BirA + + bioNanog + endbioP bioNanog a IP anti-V5 5 V 5 1V i rA ax B D b 5 V5 c A V c1 Bi r Na V5 V 5 81 d i rA Zfp2 B Bir 5 5 AV ct4V O WB BirA + FL Anti-Nanog Anti-V5 < BirA Anti-Nanog Co-express in J1 ES Cells cells Purify biotinylated protein using SA Anti-SA HRP bio Nanog 1 2 3 Anti-Nanog endNanog Input 1 2 Anti-SA HRP 158 kDa bioNanog c AntiNanog Anti-SA Void 700 kDa 440 kDa 232 kDa * BirA BirA bioNac1 BirA BirA BirA bioNanog = end Nanog Anti-V5 < BirA - bioNanog Protein ID Peptide nos -LRB- MS1 + MS2 + MS3 -RRB- 4 +7 +8 3 +2 +1 4 +2 +14 12 +5 +5 11 +16 +13 8 +14 +15 0 +1 +2 2 +0 +2 1 +2 +4 7 +2 +1 1 +2 +1 2 +0 +1 0 +2 +5 4 +0 +1 2 +1 +0 0 +0 +1 0 +1 +0 0 +0 +1 Peptide nos -LRB- Tandem -RRB- 4 1 8 3 15 e IP SA f bioZfp281 bioDax1 bioOct4 bioNanog BirA + + + d 10 168 98 One-step -LRB- MS1 -RRB- Nanog Sall1 Nanog WB anti-Nanog IP SA -LRB- bioNanog -RRB- WB Anti-Nac1 Nac1 Anti-SA bioNanog Total 2,530 peptides -LRB- 178 proteins -RRB- Total 3,410 peptides -LRB- 266 proteins -RRB- Nanog WB anti-Nanog rA V Na 5 no gV se An rum tiR An if1 tiNa no g Rif1 Tif1 Mybbp Dax1 Nac1 Zfp281 Err2 Elys Oct4 Zfp198 NF45 HDAC2 h IP anti-V5 5 20 132 66 One-step -LRB- MS2 -RRB- 2 1 2 0 0 0 0 0 0 0 12 1 1 g IP WB AntiRif1 AntiNanog AntiRif1 AntiSA Input i PI Bi bioNanog BirA + + + Input Sall4 Input Rif1 Input endNanog Input 10 107 88 One-step -LRB- MS3 -RRB- bioNanog/lgG Rif1 WB anti-Rif1 IP SA -LRB- bioNanog -RRB- WB Rif1 Anti-Rif1 * Rif1 bioNanog Rif1 WB anti-Rif1 Anti-SA bioNanog 1 10 30 Tandem REST Sp1 Wapl Figure 1 | Protein complexes containing Nanog protein in mouse ES cells . a , Strategy for biotinylation of Nanog in ES cells . Flag -LRB- FL -RRB- and 23-aminoacid biotin -LRB- Bio -RRB- tags are indicated . SA , streptavidin . b , Western blot analyses of expression of biotinylated Nanog -LRB- bioNanog -RRB- as well as endogenous Nanog -LRB- endNanog -RRB- -LRB- left -RRB- , and binding of bioNanog to SA beads -LRB- right -RRB- . IP , immunoprecipitation . c , Western blots of fractions using antiNanog -LRB- top -RRB- and anti-SA HRP antibodies -LRB- bottom -RRB- . d , Summary of LC MS / MS results from three independent one-step purifications and a tandem purification . Total peptides sequenced and proteins identified in BirA -LRB- black circles -RRB- and bioNanog -LRB- red circles -RRB- samples are indicated . Components of Nanog complexes selected with the criteria described in Supplementary Methods are listed in the table . Figure 2 | Confirmation of Nanog association by co-immunoprecipitation in ES cells . a d , Co-immunoprecipitation of Nanog and Dax1 -LRB- a -RRB- , Nac1 -LRB- b -RRB- , Zfp281 -LRB- c -RRB- and Oct4 -LRB- d -RRB- in ES cells expressing BirA without -LRB- a , b -RRB- or with -LRB- c , d -RRB- bioNanog . The asterisk marks a faint band in a. IP , immunoprecipitation . e , f , Co-immunoprecipitation of Nanog and Nac1 , Zfp281 , Dax1 and Oct4 in ES cells expressing bioNac1 , bioZfp281 , bioDax1 , bio Oct4 -LRB- e -RRB- and bioNanog -LRB- f -RRB- . g i , Co-immunoprecipitation of Nanog and Rif1 in ES cells . In g , nuclear extracts from ES cells expressing BirA and bio Nanog were incubated with preimmune -LRB- PI -RRB- serum , anti-Rif1 antibody , and anti-Nanog antibody , respectively , followed by capture with protein-A / G agarose . The asterisk indicates endogenous Nanog immunoprecipitated by anti-Rif1 antibody . Note that bioNanog migrates together with the IgG band . Antibodies for IP and western blot -LRB- WB -RRB- analyses are indicated . In h and i , experiments similar to those in a and f were performed except that different constructs and antibodies were used . 365 2006 Nature Publishing Group LETTERS NATURE | Vol 444 | 16 November 2006 Mock Nac1 .2872 shRNA Zfp281 .1691 shRNA a shRNA/mock Zfp281 0.31 2 b Nac1 0.16 0.19 e on 2 o Cl o Cl ne 1 Cl ne 11.9 9.0 6.6 8.8 15.0 25.9 Biotin-tagged/BirA 1.8 1.9 1.8 1.7 2.5 shRNA/mock 46.6 0.9 1.0 2.4 4.0 2.1 0.8 8.6 1.7 1.6 1.1 0.9 0.9 9.9 21.9 69.6 4.2 1.6 2.2 101.6 0.8 bioNac1 c 0.34 1 Cl e on d O ct 4 Re x1 G at a G 6 at H a4 N F La 4a Br m ac b1 hy ur Bm y p Bm 2 p C 4 dx 2 Fg f5 Is l1 N an 1.0 bioNanog bioZfp281 Figure 3 | Functional validation by RNA-mediated interference . a , Quantitative reverse transcriptase polymerase chain reaction -LRB- RT PCR -RRB- analysis of Nac1 and Zfp281 gene expression -LRB- two clones each -RRB- after shRNAmediated knockdown in wild-type ES cells . b , Morphology of ES cells infected with virus containing empty shRNA vector -LRB- Mock ; left -RRB- , Nac1 shRNA -LRB- middle -RRB- or Zfp281 shRNA -LRB- right -RRB- . ES cells were grown either on feeders -LRB- top -RRB- or on gelatin in the presence of LIF -LRB- bottom -RRB- . c , Quantitative RT PCR analysis of stem-cell markers as well as lineage-specific markers as indicated in Nac1 .2872 knockdown cells -LRB- top -RRB- and Zfp281 .1691 knockdown cells -LRB- bottom -RRB- . d , Quantitative real-time chromatin immunoprecipitation of biotin-tagged proteins on Gata6 -LRB- black bars -RRB- as well as Gapdh -LRB- grey bars -RRB- and b2 microglobulin -LRB- white bars -RRB- promoter sequences -LRB- as negative controls -RRB- . Results are shown as means and s.e.m. from two clones in c and three independent experiments in d. affinity purification of complexes , as described for bioNanog . Proteins were identified with the criteria applied for the selection of Nanog-associated proteins and are summarized in Fig. 4a . Multiple proteins are shared between the different complexes . A protein interaction map -LRB- or mini-interactome -RRB- 18 summarizes these observations -LRB- Fig. 4b -RRB- . Several features suggest that the network is specialized to establish and/or maintain ES cell pluripotency . First , the network is remarkably enriched for proteins that have been shown , or are likely , to be required individually for controlling the survival or differentiation of the inner cell mass , or aspects of early development . These include 15 proteins -LRB- Fig. 4b , green circles -RRB- with known phenotypic alleles in published knockout studies or communicated to us -LRB- Supplementary Table S1 -RRB- , and 4 proteins -LRB- blue circles -RRB- from shRNA-mediated inhibition described previously19 or in this study -LRB- Fig. 3 , and Supplementary Figs S5 and S6 -RRB- . Three other proteins -LRB- yellow circles -RRB- have known phenotypes that are not consistent with an early requirement in development -LRB- Supplementary Table S1 -RRB- . Thus , more than 80 % of proteins for which knockout or knockdown studies have been performed seem essential for early development and/or ES cell properties . To approximate the ` expected ' fraction of essential genes , we curated 300 random transcription factor genes and found that less than 15 % of those expressed in ES cells had knockout phenotypes consistent with an early requirement -LRB- data not shown -RRB- . Second , most genes encoding the proteins within the network are co-regulated , and specifically downregulated , on ES cell differentiation . In Fig. 4c , a rank order depicts the expression of transcripts 366 for the network proteins relative to Rex1 . For comparison , a ` control ' set of randomly chosen gene transcripts was similarly analysed -LRB- Supplementary Fig . S8 -RRB- . We chose Rex1 as a comparator because it is abruptly and extensively downregulated on the differentiation of ES cells . Co-regulation of genes in the network is consistent with their participation in a common cellular function or pathway . Third , in reinforcement of this hypothesis , we find that many -LRB- at least 56 % -RRB- of the genes encoding proteins of the mini-interactome have been reported as putative Nanog and/or Oct4 targets in recent ChIP-on-chip20 or ChIP-PET19 analyses of chromatin occupancy in human or mouse ES cells -LRB- Supplementary Table S2 -RRB- . Thus , ` downstream ' gene targets of Nanog and Oct4 also serve as ` upstream ' effectors in the pluripotency network . Although this feature may stabilize aspects of the ES cell state , it also renders the network vulnerable to attack at multiple points rather than at very few21 . Fourth , the network is linked to several cofactor pathways , which are largely involved in mediating transcriptional repression . These include the histone deacetylase NuRD -LRB- P66b and HDAC2 -RRB- , polycomb group -LRB- YY1 , Rnf2 and Rybp -RRB- and SWI/SNF chromatin remodelling -LRB- BAF155 -RRB- complexes . Of potential interest , Rex1 and Oct4 , as contrasted with Nanog or its closest partners -LRB- for example Dax1 , Sall4 and Nac1 -RRB- , are associated with polycomb components . Nanog is linked to HDAC/NuRD through its association with Sall1/4 -LRB- ref . 22 -RRB- and Nac1 -LRB- ref . 23 -RRB- . The involvement of multiple co-repressor complexes provides both a method of regulating different sets of target genes and a fail-safe mechanism to prevent differentiation 2006 Nature Publishing Group 1.1 1.3 og NATURE | Vol 444 | 16 November 2006 LETTERS a Nanog Rex-1 Dax1 Nac1 Zfp281 Oct4 Nanog complexes Nanog Oct4 Sall1 Nac1 Zfp281 Zfp198 Elys NF45 Wapl HDAC2 REST Sp1 Dax1 Err2 Sall4 Tif1 Rif1 Mybbp Dax1 complexes Nac1 complexes Zfp281 complexes Oct4 complexes Rex1 complexes Rex1 Oct4 Sall1 Nac1 Zfp609 Zfp281 Ari3a Arid3b Btbd14a EWS Zfp281 Oct4 RYBP EWS Zfp219 Oct4 YY1 Nac1 Etl1 Rai14 Arid3b NF45 Prmt1 Rnf2 Wapl PELO REST Sp1 Dax1 Err2 Sall4 Tif1 -LRB- Rif1 -RRB- -LRB- Rif1 -RRB- -LRB- Mybbp -RRB- -LRB- Rif1 -RRB- Sall4 P66 Wdr18 BAF155 Cdk1 Requiem Sall4 HDAC2 P66 Sp1 Cdk1 Requiem Sall4 Tif1 Wdr18 BAF155 Requiem b Requiem Rai14 Prmt1 P66 YY1 Rnf2 Arid3b Rybp Zfp219 Cdk1 EWS c Time -LRB- days -RRB- 0 0.25 0.5 0.75 1 1.5 2 4 7 9 14 Oct4 Etl1 Wapl NF45 Rex1 Wdr18 BAF155 Sall4 Zfp281 HDAC2 Sp1 Elys Nac1 Arid3a Btbd14a Sall1 Mybbp Tif1 Rif1 Nanog Zfp198 Err2 REST Dax1 Pelo Zfp609 Rex1 Dax1 Mybbp Etl1 Err2 Oct4 Tif1 Elys Prmt1 Wdr18 REST Rif1 BAF155 Zfp281 EWS Rai14 Sall1 Sall4 Nanog Nac1 NF45 HDAC2 Wapl Sp1 Zfp219 Btbd14a Cdk1 Zfp609 P66 Requiem YY1 Rnf2 Pelo Zfp198 Rybp Arid3b Arid3a Figure 4 | A protein interaction network in ES cells . a , Schematic depiction of the strategy for mapping protein protein interaction network in ES cells . Starting with the primary tagged baits Nanog and another stem-cell marker protein Rex1 , interaction partners of both Nanog and Rex1 were identified . The validated interactors such as Dax1 , Nac1 , Zfp281 and Oct4 served as secondary tagged baits for the identification of tertiary interacting partners . Selected high-confidence components of multiprotein complexes are listed in the table . Proteins shared by multiple tagged baits are shaded similarly . Proteins in parentheses are present predominantly in tagged samples with some peptide presence in one of the controls during one-step purifications . b , Depiction of the features of the interactome . Proteins with red labels are tagged baits for affinity purification . Green lines indicate interactions confirmed by co-immunoprecipitation and the red line indicates interaction confirmed in the literature27 . Green circles indicate proteins whose knockout results in defects in proliferation and/or survival of the inner cell mass or other aspects of early development ; blue circles indicate proteins whose reduction by RNA-mediated interference results in defects in self-renewal and/or differentiation of ES cells ; yellow circles are proteins whose knockout results in later developmental defects ; white circles denote proteins for which no loss-of-function data are available . c , Co-regulation of proteins in the network on differentiation . Microarray data were curated from the literature28 and are presented in rank order relative to Rex1 . 367 2006 Nature Publishing Group LETTERS NATURE | Vol 444 | 16 November 2006 along different lineages , which is a requisite for maintaining the pluripotent state . Last , the multiple interactions between critical factors also predict that proteins within the network influence the function of other members , either positively or negatively , and that the stoichiometry within complexes is important for maintaining pluripotency . This latter conclusion is consistent with dosage-dependent effects for Oct4 -LRB- ref . 24 -RRB- and Nanog25 . Given the numerous gene targets of the proteins within the network , it is likely that subsets of targets are regulated by different complexes . We have shown that Gata6 promoter sequences are bound by Nac1 , Zfp281 and Nanog . Presumably , proteins within the network , such as Dax1 and Sall4 , also bind other targets with Nanog , Oct4 and/or Sox2 -LRB- among other proteins -RRB- . Accordingly , the combinatorial control of target genes will be far greater in complexity than suggested by recent chromatin occupancy studies19 ,20 . Starting from a central regulator of transcription in ES cells , namely Nanog , followed by iterative tagging and purification of Nanog-associated proteins , we have developed a protein interaction network . Taken together , the extraordinary enrichment for essential genes , the coexpression of most genes , and their roles as both targets and effectors indicate that this mini-interactome might serve as a functional module committed to maintaining ES cell pluripotency . Whereas proteins of the network cooperate to maintain pluripotency , their interdependence renders the cell susceptible to rapid loss of pluripotency on the downregulation , or inactivation , of any one of many components . How differences between mouse and human ES cells are reflected in the network , and whether components of the network that are not strictly specific to ES cells are employed by other types of stem cells for controlling self-renewal versus differentiation , are topics worthy of future study . Last , the network provides a framework for exploring the combinations of factors that may permit faithful reprogramming of differentiated cells to an ES cell state26 . METHODS In vivo biotinylation , affinity purification and mass spectrometry . J1 ES cells were transfected with a plasmid construct expressing BirAV5his followed by selection with G418 -LRB- 300 mg ml21 -RRB- . Clones were picked and expanded for western blotting by using anti-V5 HRP -LRB- Invitrogen -RRB- . A BirA-expressing ES clone was then used for transfection with plasmid constructs containing biotin -LRB- or Flag biotin -RRB- tagged cDNAs . ES cells expressing tagged cDNA were identified by western blotting with anti-streptavidin HRP of the total lysates or nuclear extracts . One-step affinity purification with streptavidin-agarose was performed as described10 . In brief , nuclear extracts from ES cells expressing BirA and biotin-tagged cDNA were incubated with streptavidin-agarose in a buffer containing 1 3 Tris-buffered saline -LRB- TBS -RRB- , 350 mM NaCl and 0.3 % Nonidet P40 . Binding was performed at 4 uC for 1 h to overnight on a rocking platform , followed by six washes in binding solution . Bound material was eluted by boiling for 5 min in Laemmli buffer , fractionated on a 10 % SDS-polyacrylamide gel , and subjected to LC MS/MS sequencing and data analysis -LRB- see Supplementary Methods for details -RRB- . For tandem purification , nuclear extracts were incubated overnight with antiM2 Flag-agarose -LRB- Sigma -RRB- at 4 uC on a rocking platform . On day 2 , after extensive washing with 1 3 TBS , bound materials were eluted by using Flag peptide -LRB- Sigma -RRB- . The pooled eluate was then used for streptavidin-agarose capture as described above . Details of other methods are provided in Supplementary Materials . Received 10 April ; accepted 27 September 2006 . Published online 8 November 2006 . 1 . Martin , G. R. Isolation of a pluripotent cell line from early mouse embryos cultured in medium conditioned by teratocarcinoma stem cells . Proc . Natl Acad . Sci . USA 78 , 7634 7638 -LRB- 1981 -RRB- . Evans , M. J. & Kaufman , M. H. Establishment in culture of pluripotential cells from mouse embryos . Nature 292 , 154 156 -LRB- 1981 -RRB- . Donovan , P. J. & Gearhart , J . The end of the beginning for pluripotent stem cells . Nature 414 , 92 97 -LRB- 2001 -RRB- . Prelle , K. , Zink , N. & Wolf , E. Pluripotent stem cells -- model of embryonic development , tool for gene targeting , and basis of cell therapy . Anat . Histol . Embryol . 31 , 169 186 -LRB- 2002 -RRB- . 5 . 6 . 7 . 8 . 9 . 10 . 11 . 12 . 13 . 14 . 15 . 16 . 17 . 18 . 19 . 20 . 21 . 22 . 23 . 24 . 25 . 26 . 27 . 28 . Silva , J. , Chambers , I. , Pollard , S. & Smith , A. Nanog promotes transfer of pluripotency after cell fusion . 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Stimulation of Oct-4 activity by Ewing 's sarcoma protein . Stem Cells 23 , 738 751 -LRB- 2005 -RRB- . Perez-Iratxeta , C. et al. . Study of stem cell function using microarray experiments . FEBS Lett . 579 , 1795 1801 -LRB- 2005 -RRB- . Supplementary Information is linked to the online version of the paper at www.nature.com/nature . Acknowledgements We thank A. Cantor for biotin tagging constructs and for advice on affinity purification and chromatography ; Y. Fujiwara and M. Kaku for technical assistance and for Oct4 GFP ES cells ; T. De Lange for Rif1 antibody ; S. Mackler for Nac1 antibody ; S. Lowe and S. Elledge for shRNA vectors ; M. Vidal and A.-L . Barabasi for advice and discussion on networks ; and R. Tomaino and S. Gygi for performing LC MS/MS and for providing advice and assistance in data collection and analysis . S.H.O. is an Investigator of the HHMI . Author Contributions S.R. and J.C. contributed equally to this study . J.W. and S.H.O. conceived and initiated the study . J.W. , J.C. , X.S. , D.N.L. and T.W.T. performed the experiments . S.R. and J.W. analysed data and bioinformatics of the network . J.W. and S.H.O. wrote the manuscript . Author Information Reprints and permissions information is available at www.nature.com/reprints . The authors declare no competing financial interests . Correspondence and requests for materials should be addressed to S.H.O. -LRB- stuart_orkin@dfci.harvard.edu -RRB- . 2 . 3 . 4 . 368 2006 Nature Publishing Group

O O O O O O O O O O O O O O O O B O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O B O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B O O O O O O O O O O O O O O O B O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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