Spatial Pattern Dynamics of 3D Stem Cell Loss of Pluripotency via Rules-Based Computational Modeling
[['Pluripotent embryonic stem cells ( ESCs ) have the unique ability to differentiate into cells of the three germ lineages that form all of the tissues and organs of a mature organism .', 'Differentiation of pluripotent ESCs can be induced in vitro via a variety of existing approaches to emulate aspects of the developmental program .', 'One of the most widely used techniques relies upon the formation of multicellular aggregates composed of undifferentiated ESCs in suspension culture , commonly referred to as embryoid bodies ( EBs ) [1] , [2] , that spontaneously induce the differentiation of ESCs within the 3D aggregate [3] , [4] .', 'Due to the fact that EBs mimic the physical structure and cellular composition of the morphogenic embryonic microenvironment , they have been used to study aspects of development in vitro as well as the formation of primitive tissue complexes [3]–[5] .', 'Despite the utility of the approach , robust methods to control EB differentiation in vitro remain limited due to an incomplete understanding of the complex interactions within the 3D multicellular aggregates that mitigate cell fate decision [6] , [7] .', 'The development of techniques to control ESC differentiation in vitro requires an improved understanding of cellular cues that regulate differentiation and the means to precisely control these complex signals .', 'Considerable effort has focused on ascertaining the role of individual components of the cellular microenvironment in regulating cell fate decisions .', 'The extent to which cell-cell communication via paracrine [8] , [9] , autocrine [9]–[11] , or direct contact signaling [12]–[14] enhance or inhibit differentiation have been investigated in various contexts .', 'Exogenous manipulation has been used to control differentiation by the addition or removal of various soluble factors in a temporally regulated manner in an effort to mimic morphogenic cues .', 'Factors that preserve pluripotency ( e . g . LIF [15]–[17] , BMP-4 [15] ) and factors that can initiate differentiation ( e . g . Activin A [18] , FGF-2 [18] , and retinoic acid [19] ) have been thoroughly examined , both in terms of the appropriate doses and their temporal administration .', 'In many cases , the signaling pathways and modes of action of these growth factors are also known but the effects of combinatorial treatments can be difficult to predict a priori [16] , [20] .', 'Although exogenous factors have proven necessary for the in vitro and in vivo maintenance or differentiation of ESC populations , they are not the only factors regulating stem cell behaviors .', 'The biochemical composition of the cellular microenvironment [9] , [21] and extracellular matrix ( ECM ) [22]–[24] have also been implicated in the regulation of cellular niches .', 'In addition , the mechanics and physical properties of the microenvironment can also impact cell phenotype [25] .', 'Given that cell fate transitions occur in complex environments where biochemical and physical cues coexist , elucidating the role each of these combinatorial factors via experimental studies alone remains a significant challenge .', 'Therefore , although the aforementioned studies can provide information about certain individual factors in isolation , new approaches that allow systematic investigation of combinations of parallel factors that regulate stem cell differentiation are needed to more accurately predict cell response to complex microenvironmental cues .', 'In many instances , computational modeling strategies have been successfully used to recapitulate the integration of complex signals that direct cell fate decisions and correctly predict the resulting phenomena .', 'Depending on the desired resolution of the system , ordinary differential equations can be used to model a variety of processes in stem cells including - but not limited to - cellular signaling events [26]–[28] , protein interaction networks [29] , and genetic networks [30] .', 'Partial differential equations can be used to assess spatial changes introduced via diffusion of molecules; this approach has been extensively studied to examine gradients of nutrients in cancer cell spheroids [31] , as well as mass transfer limitations in EBs [32] .', 'Alternatively , to model the structure of cellular aggregates [33]–[35] , cellular division and tissue formation [36]–[43] , and pattern formation in biological systems [38] , [39] , agent-based modeling has been applied to overlay rules-based and physical modeling approaches [34] .', 'Moreover , agent-based models have been used to investigate dynamic processes of multicellular systems , such as morphogenesis [43] , [44] and formation of physical tissues [45] .', 'Investigation of the spatial and temporal regulation of stem cell differentiation using agent based model approaches has not been attempted , yet the ability to examine how structural features of the stem cell niche influence the spatial patterns associated with loss of pluripotency is attractive for studying differentiation in 3D EB systems .', 'This study demonstrates the utility of computational rules-based modeling to predict emergent spatial patterns associated with one pluripotent transcription factor in EBs ( Oct4 ) and investigate macroscopic principles that can play important roles in determining cell fate transitions .'], ['Embryoid bodies ( EBs ) are 3D multicellular spheroidal aggregates that self-assemble via E-cadherin mediated interactions in suspension conditions [46] , [47] .', 'Our first goal in constructing a model description of EBs was to accurately recapitulate the overall multicellular structure based on the physical properties of individual mouse embryonic stem cells ( mESCs ) .', 'Prior models of multicellular structures have described the individual cellular agents as incompressible objects consisting of ellipsoids [48] .', 'We opted to use a physics-based modeling approach in which cells were modeled as incompressible rigid spheres as this is a powerful and portable method for representing complex aggregate shapes .', 'To determine if modeling mESCs as spheres was appropriate , the effective surface area ( Fig . 1A ) and radii ( Fig . 1B ) of individual ESCs were experimentally determined via Coulter counter analysis .', 'The average surface area to volume ratio of the mESC line was 3 . 26+/−0 . 15 , which is only ∼8% higher than the theoretical value of 3 . 00 for a spheroid .', 'Due to the increased computational costs associated with an ellipsoid collision detection algorithm and the relatively low error in the surface area-to-volume ratio ( <10% ) , we proceeded by representing each cellular agent as a sphere .', 'The distribution of cell radii from the Coulter counter measurements ( Fig . 1A , B ) were used to create the population of spheres for each agent in the EB simulations .', 'These cell agents were randomly seeded into a box , which served as an initial boundary for the simulation , and then forced to aggregate using a gravitational point source into a multicellular spheroidal structure .', 'The structures of in silico and in vitro aggregates were assessed for aggregates of 250 and 1000 cells using four parameters: radius , circularity , connection count , and connection lengths .', 'Size and circularity were used to assess the entire aggregate structure and were experimentally determined through the analysis of phase contrast images , while similar measurements were obtained using projections of the in silico EBs onto a 2-dimnesional plane ( Fig . 1D ) .', 'The results indicated that the model appropriately captured the macroscopic features of the relative EB aggregates since there were no statistical differences between the model and experimental metrics ( Fig . 1E , 1F ) .', 'The connection count and connection length parameters were calculated from the spatial distribution of individual cells comprising the aggregates and serve as quantifiable metrics for assessing local micro-scale organization within EBs .', 'These parameters were assessed by individual cell labeling performed in confocal microscopy images and via computational algorithms for the in silico EBs ( Fig . 1G ) .', 'As an example , the blue box in Fig . 1G highlights a cell with an average connection length of 14 . 87+/−2 . 07 microns and connection number of 4 .', 'For in silico EBs , the aggregates were “virtually sectioned” ( at a 10 µm thickness ) to perform similar analysis on a 2D projection , and neither the average circularity nor the connection lengths differed statistically from the experimentally derived EB values ( Fig . 1H , 1I ) .', 'Overall , these results quantitatively comparing four different physical parameters indicated that the model was able to accurately create the structure of individual EBs on both the aggregate and cellular scales , providing an accurate structural framework for our subsequent analysis of spatial patterning .', 'Throughout the subsequent discussion of the results , pluripotent cells that exhibit loss of Oct4 expression are simply referred to as “differentiated” , acknowledging the caveat that Oct4− cells are not terminally differentiated .', 'As Oct4 is concomitant with loss of pluripotency , it was used to monitor the pluripotent state of the cells [49]–[52] .', 'This process has been modeled as a bi-stable transition , which causes an all or none response [52] .', 'The temporal patterns of loss of pluripotency were evaluated in 250- and 1000-cell EBs via confocal microscopy to examine Oct4 expression .', 'Starting from a homogeneous population of undifferentiated cells , spatial heterogeneity ( as defined by loss of Oct4 expression ) was observed over the course of the multiple days of evaluation .', 'In order to capture the diversity of spatial pattern heterogeneity , a classification system was developed .', 'Based on preliminary results from both the experimentally derived EBs and the model , six different categories of patterns were proposed: Oct4+ , inside-out , outside-in , connected , random , and Oct4− ( Fig . 2 ) .', 'These patterns can be loosely grouped into three larger categories: Oct4+ , transitioning , and Oct4− .', 'The outside-in , inside-out , connected , and random patterns were all considered transition patterns as they captured intermediate stages of the differentiation process .', 'Inside-out patterns are characterized by differentiation in the middle of the EB and undifferentiated cells on the outside; conversely outside-in patterns exhibit differentiation on the outside , and undifferentiated cells in the middle .', 'Connected patterns were defined as multiple distinct connected regions of cells of the same state , whereas random patterns were classified as no identifiable pattern based on a lack of connectivity .', 'In the smaller 250-cell EBs , Oct4 expression persisted for up to six days ( Fig . 3A ) .', 'Rapid loss of Oct4 was observed between days 3 and 5 ( Fig . 3C ) and the patterns associated with differentiation were classified entirely as “connected” ( Fig . 3D ) .', 'In 1000-cell EBs , differentiation patterns were assessed over a 7-day period ( Fig . 3B ) .', 'Differentiation was observed to occur at a later time than the smaller 250-cell EBs , with transition patterns occurring from days 4 to 7 ( Fig . 3E ) .', 'The spatial patterns in the 1000-cell EBs associated with differentiation were more varied than the 250-cell EBS but also were primarily classified as “connected” ( Fig . 3F ) .', 'At each time point , pattern classification for each EB size was performed to generate temporal differentiation profiles for each time point ( Fig . 3D , 3F ) .', 'The trajectories of differentiation were calculated by assessing how the number of differentiated , undifferentiated , and transitioning patterns changed over time .', 'Although the types of patterns associated with differentiation only changed slightly with EB size ( Fig . 3D , 3F ) , the kinetics of the process did appear to change appreciably .', 'The 250-cell EBs began differentiating at ∼ day 3 and finished within one day , whereas the 1000-cell EBs started a similar process later at ∼ day 4 , and took nearly 3 days to fully exhaust Oct4 expression ( Fig . 3C , 3E ) .', 'After validating the generation of an appropriate 3D geometry of EB aggregates , rules-based modeling was performed by creating network structures , in which “nodes” represented individual cells , and “connections” represented physical interactions between adjacent cells; nodes were allowed to convey information with the macrostructure along the defined connections .', 'The goal was to determine if simple rules accurately produced the distribution of spatial patterns observed experimentally .', 'During these initial simulations the macro-structures were assumed to be static ( i . e . no proliferation , migration or apoptosis ) .', 'Cells could exist in either of two states: undifferentiated ( Oct4+ ) or differentiated ( Oct4− ) .', 'The transition between these two states was chosen as binary based on previous modeling work [52] and occurred based on different rule formulations: “random” , “positive feedback” or “competing feedback” ( Fig . 4 ) .', 'The random rule configuration represented a stochastic , basal differentiation probability ( Fig . 4A ) .', 'The positive feedback rule was based on a paradigm in which differentiated cells bias neighboring cells to differentiate ( Fig . 4B ) and was inspired by differentiation induced via direct cell-cell interactions [13] , [53] .', 'Finally , the competing feedback rule depicts a situation where differentiated cells promote subsequent differentiation of neighboring cells while undifferentiated cells inhibit this transition ( Fig . 4C ) .', 'Positive feedback in this rule was based upon the known role of soluble factors to maintain pluripotency [54] , while negative feedback comes from the differentiation induced via the cell-cell interactions discussed above [13] , [53] .', 'Representative outcomes for each of the rules are shown for 250 ( Fig . S1 ) and 1000 cells ( Fig .', '5 ) per EB .', 'The patterns represented by different rules did not differ significantly across EB sizes ( Fig . 5 and Fig . S2 ) ; however , differences in the distribution of the patterns were observed between different rule configurations .', 'The random rule transitioned through largely random patterns ( Fig . 5I , S2I ) , whereas both the positive feedback and the competing feedback exhibited an enrichment in the connected patterns ( Fig . 5F , S2F and Fig . 5C , S2C respectively ) .', 'Because the experimental EBs differentiated largely through connected patterns ( Fig . 3D , F ) based on the pattern classification , it was difficult to evaluate which rule configuration ( s ) best emulated the experimental data .', 'To ensure these results were not an artifact of the multicellular aggregate structure , resultant patterns of 250 and 1000 cell EBs were evaluated for each of the three rules ( Fig . S2 ) across numerous different simulated structures without discernible changes in outcome .', 'To glean insight into the evolution of the connected patterns , we used two quantitative metrics , undifferentiated cluster number ( UCN ) and differentiated cluster number ( DCN ) , to assess pattern formation and simulation trajectories against a normalized time ( τ ) axis .', 'Analyzing the cell phenotype transitions by the UCN and DCN metrics revealed distinct paths of pattern formation for each of the different rules .', 'The qualitative shape of the trajectories was independent of EB sizes ( Fig . S3 ) .', 'From such curves , critical points ( τ\u200a= . 2 , τ\u200a= . 4 , and τ\u200a= . 6 ) representing rapid changes or important regions across all rules were chosen and representative EB slices were displayed ( Fig . 5B , E , H ) ) .', 'Analysis of the trajectories themselves revealed insight about the types of clusters being formed in the “connected” patterns .', 'In the “positive feedback” scenario , the loss of Oct4 expression was characterized by a high number of differentiated or undifferentiated clusters , suggesting localized intercellular neighbor influences regulating phenotype transition ( Fig . 5D , Fig . S1D ) .', 'The peak in UCN at τ\u200a= . 6 was characterized by a large number of isolated pockets of undifferentiated cells .', 'In contrast , the “competing feedback” rule peaked through a high number of differentiated clusters , but never amassed a high undifferentiated cluster number ( Fig . 5G , Fig . S1G ) which matched the larger isolated and persistent clusters of Oct4 positive cells experimentally observed in both the 250- and 1000-cell EBs .', 'Taken together , these data indicate that the “competing feedback” rule matched the patterns observed biologically with the highest fidelity for the different size EBs examined .', 'Furthermore , the trajectory analysis provided novel information about the evolution of certain patterns .', 'For example , random differentiation can be characterized by a high initial spike in the DCN as this signifies the emergence of several small clusters of differentiated cells ( Fig . 5A , Fig . S1A ) , and the duration of this spike represents how long the random patterns persist throughout the duration of the model .', 'If the UCN remains fairly low , the pattern transitions into a connected phenotype , again evidenced by the low number of undifferentiated clusters of cells ( Fig . 5B , Fig . S1B ) .', 'When the UCN remains at 1 , this signifies either an inside-out , or outside-in pattern .', 'However , if the UCN transitions towards a high value , this signifies that the differentiation is still largely governed by random patterns ( Fig . 5A , Fig . S1A ) .', 'Overall , these metrics provide quantitative metrics for assessing the types of patterns formed , and the evolution of these patterns over time .', 'One limitation of the model , however , was that the kinetics of pattern formation could not explain the differences in kinetics experimentally observed between different EB sizes ( Fig . 3D , F ) .', 'This suggested that although a static size aggregate modeling approach was sufficient for predicting the prevalence of different spatial pattern classifications , it did not fully capture the kinetics of experimental Oct4 loss .', 'In order to further investigate the kinetics of the pattern transitions , we modified our modeling framework to include cell division and embryoid body growth .', 'We hypothesized that dynamic processes , such as cell division and growth of the EB aggregate , influence spatial patterns of Oct4 expression loss .', 'To investigate the effect of cell division on this loss of pluripotency transition , a revised model which could simulate growing EB structures was created in which the Oct4+ cells divided at a faster rate than the Oct4− cells .', 'With this approach , cells were modeled as rigid spheres while cell-cell connections were represented by springs which helped maintain the overall macro-structure of the aggregate ( Fig . 6A ) .', 'We observed experimentally that the size of differentiating ESCs did not change appreciably with time , which reduced complexity from the model description ( Fig . 6B ) .', 'The first step was to determine an estimated cellular division rate for Oct4+ and Oct− cells .', 'This was accomplished using experimental growth data approximated from the size of the embryoid bodies ( Fig . 6C ) , yielding a rate of ∼18 hours for division of our stem cells and ∼51 hours for division of the differentiated cells which is consistent with the literature [55] .', 'Using these division rates , we applied the rules we derived in the former static model to the new dynamic model .', 'As an internal control , we ran division simulations with no rules to monitor any bias introduced by the model ( Fig . S4 ) and found that the cells grew in an exponential manner ( Fig . S4A ) , while the density of the aggregates remained constant ( Fig . S4C ) .', 'Furthermore , the average connection number and connection lengths of the network remained constant with time ( Fig . S4 E ) .', 'Connection length remained constant as a function of the aggregate radius , whereas the connection number decreased on the outer layer of the aggregate , as was expected ( Fig . S4E ) .', 'Taken together these results suggest that structurally no bias was introduced into the model by introducing cell division .', 'Next we examined the spatial patterns formed under the various rule configurations during enlargement of the EB over a 5–7 day period , with the pattern trajectories now normalized by the cell number to account for cell growth .', 'Trajectories simulated over the 6 day culture period indicated consistent pattern distributions and their evolution over time ( Fig . 6E–F ) .', 'While few differences were observed in the trajectories as a function of EB size , the cumulative variance in the UCN and DCN metrics was greater for the 250 cell EBs ( Fig . 6G ) , suggesting a more heterogeneous population of differentiated cells .', 'At later time points ( >Day', '5 ) the positive feedback rule generated clusters of undifferentiated cells predominantly on the outer edges of the EB .', 'In contrast , the competing feedback rule produced larger clusters of undifferentiated cells localized towards the center of the EB .', 'The trajectories of these growth simulations matched the general shape of the trajectories for the static simulations ( Fig . S3 ) , with a notable exception of the random rule .', 'Analysis of the percentage of undifferentiated trajectories revealed that over half the cells remained undifferentiated at the seven day time point , which may explain the absence of the DCN to UCN transition observed in the previous static model simulations .', 'The motivation behind modeling a dynamic EB structure was to more closely recapitulate the emergent morphogenic processes occurring over the transitional 5–7 day period and to investigate whether the inclusion of cell division and EB enlargement influenced the rate of emergent spatial patterns ( Fig . 6H ) .', 'In the case of the random and competing feedback rules , no observable difference in the percentage of differentiated cells appeared , however the positive feedback rule resulted in the percentage of undifferentiated cells being lower in the 1000 cell versus 250 cell EBs , likely due to the total number of cells present .', 'Taken together these results suggest that differential cell division does not significantly influence the formation or evolution of phenotype patterns over time and the pattern formation process is dominated by the regulatory mechanisms encoded in the probabilistic rules .'], ['Differentiation is a complex biological process involving the coordinated regulation of multiple genes by intrinsic and extrinsic factors .', 'Rather than attempt to model the intricate network of genetic circuitry , signaling mechanisms , and environmental cues , we approached the loss of pluripotency from a simplified perspective designed to elucidate the most basic principles dictating pattern formation in a spherical multicellular system .', 'We developed a modeling framework capable of recapitulating the physical properties of embryoid bodies for multiple sizes and under conditions of cell division and aggregate growth .', 'This framework allowed us to simulate how different probabilistic rules were manifest in the emergence of spatial patterns and to examine the evolution of these patterns over time .', 'Through comparison of the simulated pattern trajectories with the pattern classification developed for our experimental data , we determined that all possible pattern classes - as well as a similar distribution within these classes - are possible with the agent rules employed .', 'Furthermore , from both static and dynamic frameworks , our simulations indicate that aggregate structure , size , and growth are physical features that do not dictate the distribution of spatial patterns or their trajectories as a function of time .', 'Differentiation is classically thought of as a binary transition from the undifferentiated pluripotent stem cell state to differentiated phenotypes in embryoid body ( EB ) models [5] , [31] , [46] .', 'Models of stem cell differentiation often consider these events on a population basis [56] or at an intracellular signaling level [57] .', 'Here we have shown that the transition from Oct4+ to Oct4− states produces dynamic , spatially heterogeneous patterns in a continuous manner .', 'These results indicate that modeling embryonic stem cell ( ESC ) fate decisions as a stochastic , binary process is sufficient to predict the dominant emergent spatial patterns of loss of pluripotency .', 'Additionally , 250- and 1000-cell EBs undergo loss of pluripotency through the same intermediate patterns which suggests that the macro processes governing this early stem cell transition ( while occurring at slightly different rates ) are largely independent of size .', 'In addition , comparing static structures and cell division models revealed that spatial transition patterns and their evolution are not significantly affected by cell growth .', 'Our modeling approach created in silico aggregates with similar properties to in vitro EBs .', 'The spring-based constraint representing cellular adhesions was able to accurately capture the evolution of the aggregate architecture .', 'Additionally , the high-level rules described here were able to reproduce the emergence of a variety of spatial patterns , all of which could be observed experimentally in EBs .', 'Both modeled and experimental EBs demonstrated enrichment in connected patterns of cells .', 'Quantification of model simulation outputs by differentiated and undifferentiated cluster number ( DCN and UCN ) allowed visual representation of the time evolution of connected patterns in 3D multicellular aggregate systems .', 'The use of the UCN and DCN metrics provided information about not only the types of connected patterns formed , but also the transitions between the different types of spatial patterns .', 'A combination of analyses using these metrics and manual pattern identification indicated that the “competing feedback” rule scheme that accounted for opposing influences of neighboring pluripotent and differentiated cells produced a distribution of spatial patterns that most closely resembled the experimentally observed spatial patterns for both 250- and 1000-cell EBs .', 'This was observed in both the static and dynamic division models , and could be hypothetically represented biologically as a combination of cell-cell signaling and the complex interplay of local soluble factors and other chemical gradients that influence pluripotent cell fate decisions .', '[17] , [53] , [58] , [59] .', 'However , this is only one possible explanation for a coarse-grained description , and a variety of other signaling pathways and molecules are likely involved in regulating this transition .', 'Interestingly , none of the rules were able to explain the observed emergent patterns if cells were not allowed to also spontaneously differentiate at a low rate random rate .', 'Although for the positive feedback rule this follows directly from the construction of the probability equations , the formation of strongly connected patterns was also not observed in the competing feedback rule without the inclusion of this low stochastic rate ( data not shown ) , suggesting this random rate is important to capture the experimentally observed transition patterns .', 'The static structure model predicted small differences in the Oct4 expression kinetics of EBs with different cell seeding numbers should exist; however , the slight changes observed did not capture the full extent of the variation present in the experimental results .', 'The inclusion of cell division ( with a faster division rate for pluripotent cells ) was also not able to explain the difference in the kinetics of this process .', 'These results indicate that additional factors in the changing culture environment may modulate the kinetics of Oct4 loss in a size-dependent manner; hydrodynamic effects [60] , diffusion limitations and/or local chemical gradients may need to be taken into account for changing aggregates sizes [32] , [61] in order to reproduce the experimentally observed differences in differentiation kinetics .', 'It is also possible that the rules chosen are not descriptive of our system with a fine enough resolution , thus explaining the ability to explain pattern formation characteristics but not kinetics .', 'Furthermore , we constructed the model such that all cells have the same strength when affecting other cells , which assumes that cells convey the same amount of information regardless of the amount of cell connections or the amount of shared cell area , an assumption that may need to be refined as more detailed information about the nature of intercellular communication is included .', 'Future developments will account for cell migration , local versus distal cell-cell communication and diffusion within the EB to investigate how these traits affect the physical microenvironment .', 'The top-down modeling approach described in this study provides new insight into the spatial pattern development associated with differentiation of ESCs in 3D EB structures .', 'Surprisingly , without explicitly modeling diffusion gradients or specific signal transduction mechanisms , features of temporal and spatial regulation were elucidated .', "Transitions in cell phenotype can be modeled as a flow of information between cells that is largely based on stochastic fate changes that are influenced by the cells' surrounding environment .", 'The model was able to identify a simple rule paradigm that is biologically relevant and consistent with the current knowledge of stem cell regulatory processes [17] , [53] , [58] , [59] .', 'A comparison of static and division models indicated that the proposed rule schemes are not significantly affected by cell division .', 'Consequently , the proposed modeling technique developed thus far has demonstrated validity for exploring the propensity of various spatial patterns observed in EBs during the differentiation process .', 'This model can readily be extended to investigate what factors influence differentiation into different germ layers , and eventually used to predict optimal niche and microenvironment organization for efficient stem cell maintenance and differentiation .'], ['A murine embryonic stem cell line ( D3 ) transfected with an Oct4-GFP construct were used ( phOCT3-EGFP1; provided by Wei Cui , Ph . D . , Imperial College , London , UK ) .', 'For this particular experiment these cells were used after several passages and splits , and thus did not show robust GFP activity under confocal or flow cytometry; thus immunostaining was necessary to visualize Oct4 expression .', "These cells were cultured in monolayer on 100 mm tissue culture plates coated with 0 . 67% gelatin in Dulbecco's modified Eagle's medium ( DMEM ) supplemented with 15% fetal bovine serum ( FBS ) ( Hyclone , Logan , UT ) , 2 mM L-glutamine ( Mediatech ) , 100 U/ml penicillin , 100 ug/ml streptomyocin , and 0 . 25 ug/ml amphotericin ( Mediatech ) , 1× MEM nonessential amino acis solcuiotn ( Mediatech ) , 0 . 1 mM 2-mercaptoethanol ( FisherChecmical , Fairlawn , NJ ) , and 103 U/ml leukemia inhibitory factor ( LIF ) ( Chemicon Internation , Temecula , CA ) .", 'Cells were passaged every 2–3 days prior to reaching 70% confluence .', 'Undifferentiated embryonic stem cells were dissociated from monolayer culture using 0 . 05% trypsin-EDTA solution ( Mediatech ) to obtain a single cell suspension and added to AggreWells ( Stem Cell Technologies ) [62] six well plate inserts to form six thousand EBs of either 250 ( 1 . 5 million cells/ml ) and 1000 ( 6 million cells/ml ) cell per EB .', 'EBs were allowed to form in the wells for 20 hours , at which point they were removed and transferred into a rotary culture at 60 RPM [63] .', 'EBs were re-fed every 2 days , and 75% of the spent medium was replaced with fresh medium at each exchange .', 'EBs were cultured in this manner for the entire 7 day culture period .', 'EBs were harvested at various time points and fixed for 45 minutes in 10% formalin .', 'EBs were imaged using bright field microscopy via a 4× objective on an EVOS microscope .', 'Three representative images were taken for each sample .', 'Images were analyzed by using threshold , watershed , and image particle detection operations in Im
['Introduction', 'Results', 'Discussion', 'Materials and Methods']
['Pluripotent embryonic stem cells ( ESCs ) have the unique ability to differentiate into cells from all germ lineages , making them a potentially robust cell source for regenerative medicine therapies , but difficulties in predicting and controlling ESC differentiation currently limit the development of therapies and applications from such cells .', 'A common approach to induce the differentiation of ESCs in vitro is via the formation of multicellular aggregates known as embryoid bodies ( EBs ) , yet cell fate specification within EBs is generally considered an ill-defined and poorly controlled process .', 'Thus , the objective of this study was to use rules-based cellular modeling to provide insight into which processes influence initial cell fate transitions in 3-dimensional microenvironments .', 'Mouse embryonic stem cells ( D3 cell line ) were differentiated to examine the temporal and spatial patterns associated with loss of pluripotency as measured through Oct4 expression .', 'Global properties of the multicellular aggregates were accurately recapitulated by a physics-based aggregation simulation when compared to experimentally measured physical parameters of EBs .', 'Oct4 expression patterns were analyzed by confocal microscopy over time and compared to simulated trajectories of EB patterns .', 'The simulations demonstrated that loss of Oct4 can be modeled as a binary process , and that associated patterns can be explained by a set of simple rules that combine baseline stochasticity with intercellular communication .', 'Competing influences between Oct4+ and Oct4− neighbors result in the observed patterns of pluripotency loss within EBs , establishing the utility of rules-based modeling for hypothesis generation of underlying ESC differentiation processes .', 'Importantly , the results indicate that the rules dominate the emergence of patterns independent of EB structure , size , or cell division .', 'In combination with strategies to engineer cellular microenvironments , this type of modeling approach is a powerful tool to predict stem cell behavior under a number of culture conditions that emulate characteristics of 3D stem cell niches .']
['Pluripotent embryonic stem cells can differentiate into all cell types making up the adult body; however , this process occurs in a complex three dimensional environment with many different parameters present that are capable of influencing cell fate decisions .', 'A model that can accurately predict the strengths of factors influencing cell fate would allow examination of spatial and temporal patterns of cell phenotype .', 'For this study , we focused on the earliest fate transition that occurs in 3D clusters of embryonic stem cells by monitoring the presence of a transcription factor ( Oct4 ) associated with stem cell pluripotency .', 'After experimentally classifying patterns that arise en route to a fully differentiated aggregate in vitro , we constructed a computational model to deduce how stem cells integrate cues from their surrounding environment to give rise spatial patterns .', 'We used a rules-based modeling approach in which information exchanged by cells with their nearest neighbors regulated cell fate decisions .', 'This parsimonious model captured the spatial dynamics of early cell lineage commitment in a 3D multicellular structure .', 'In combination with strategies to modulate cellular environments , our model provides a flexible tool for elucidating the extra- and intercellular interactions regulating spatially organized differentiation of stem cells in 3D .']
['developmental biology', 'computer science', 'molecular cell biology', 'computer modeling', 'stem cells', 'cell biology', 'embryonic stem cells', 'cellular types', 'biology', 'computational biology', 'stem cell lines', 'cell differentiation']