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Title: Computational Modeling of the Hematopoietic Erythroid-Myeloid Switch Reveals Insights into Cooperativity, Priming, and Irreversibility}
Article:
Abstract:
Hematopoietic stem cell lineage choices are decided by genetic networks that are turned ON/OFF in a switch-like manner. However, prior to lineage commitment, genes are primed at low expression levels. Understanding the underlying molecular circuitry in terms of how it governs both a primed state and, at the other extreme, a committed state is of relevance not only to hematopoiesis but also to developmental systems in general. We develop a computational model for the hematopoietic erythroid-myeloid lineage decision, which is determined by a genetic switch involving the genes PU. 1 and GATA-1. Dynamical models based upon known interactions between these master genes, such as mutual antagonism and autoregulation, fail to make the system bistable, a desired feature for robust lineage determination. We therefore suggest a new mechanism involving a cofactor that is regulated as well as recruited by one of the master genes to bind to the antagonistic partner that is necessary for bistability and hence switch-like behavior. An interesting fallout from this architecture is that suppression of the cofactor through external means can lead to a loss of cooperativity, and hence to a primed state for PU. 1 and GATA-1. The PU. 1–GATA-1 switch also interacts with another mutually antagonistic pair, –FOG-1. The latter pair inherits the state of its upstream master genes and further reinforces the decision due to several feedback loops, thereby leading to irreversible commitment. The genetic switch, which handles the erythroid-myeloid lineage decision, is an example of a network that implements both a primed and a committed state by regulating cooperativity through recruitment of cofactors. Perturbing the feedback between the master regulators and downstream targets suggests potential reprogramming strategies. The approach points to a framework for lineage commitment studies in general and could aid the search for lineage-determining genes.
Introduction:
Stem cell fates are decided upon the basis of which genes are turned ON/OFF. However, prior to commitment, it has been observed that many genes are expressed at intermediate or basal levels for the hematopoietic stem cell system[1],[2]. Such “priming” behavior for progenitors could allow for rapid deployment of transcription factors to implement particular genetic programs. In hematopoiesis there exist several lineage branch points with identified key transcription factors and external signals[3]–[5]. A particularly well studied subnetwork is that of PU. 1 and GATA-1. It governs the erythroid- myeloid lineages and demonstrates both the commitment as well as priming features[6],[7]. Both PU. 1 and GATA-1 are autoregulatory[8],[9], thereby providing stability to their levels, once expressed. PU. 1 and GATA-1 also regulate each other in a mutually antagonistic way[10]–[12], such that either of them are expressed exclusively in a fully committed state[7]. Mutual antagonism, an example being the toggle switch[13], enables the selective expression of a gene while suppressing the other. Recent investigations[14],[15] focus on this mechanism to regulate choices of expressed genes as part of the macrophage/neutrophil lineage. From forced expression studies in both cell lines and primary cells, it is evident that GATA-1 and PU. 1 are able to specify erythroid and myeloid cell fates( see[16] and references therein). It is also clear that both GATA-1 and PU. 1 cross-antagonize each other's activity. Biochemical studies suggest that in one case this occurs through the inhibition of DNA binding of cognate cis-regulatory motif while in the other case DNA binding is unaffected but the transactivation potential is inhibited[17]. Precisely how GATA-1 and PU. 1 then initiate the presumed cascade of transcriptional changes that culminate in the specification of terminally differentiated erythroid and neutrophilic cells is currently unclear and the subject of intense experimental investigation. Global chromatin immunoprecipitation studies will no doubt provide insights into the relevant target genes in both cases. In the case of GATA-1 it is however clear that the situation will be complicated by the occurrence of different GATA-1 complexes which may create both positive and negative transcriptional activity upon GATA-1 itself[18]. Such considerations may be pertinent in the context of GATA-1/FOG-1 interactions, which may either be positive or negative depending on the presence or use of additional partner proteins. How these interactions, which have been documented in fully committed erythroid cells, play out at earlier stages of differentiation at the time of commitment decisions involving PU. 1 and GATA-1 is at the moment not clear. From a dynamical point of view, a biological network, such as the PU. 1–GATA-1 genetic switch, which is responsible in determining two different lineages, would be expected to exhibit bistability. In general switch-like behavior can give rise to phenotypic diversity[19],[20], by allowing different states to be sampled. An ultrasensitive[21] switch-like behavior on the other hand lacks built-in memory of the system, and hence is not as robust to fluctuations in the input signal. In[22],[23], bistability, has been shown to occur in mammalian gene networks. Bistability, which is seen to arise from positive feedback in systems[24]–[27], has been explored in several circuits[13],[28],[29], and has also been discussed mathematically[30]. The PU. 1–GATA-1 system, which displays switch behavior[31], has encouraged the development of two computational models which describe the effects of autoregulation and mutual antagonism on the dynamics of the transcriptional network[32],[33]. In[32], the authors discuss multistability and priming properties in terms of autoregulatory, cross-inhibitory and cross activation interactions. They show that priming might occur when either both PU. 1 and GATA-1 are expressed at very low levels, or, alternatively, at intermediate expression of both genes with stronger cross activation strengths. In[33], using a combination of mathematical modeling and experimental data, it is shown how the PU. 1–GATA-1 network encodes the possibility of priming. Assuming that PU. 1 and GATA-1 repress each other's expression, the only possible states of the system are either PU. 1 at a high level and GATA-1 at a low level, and vice versa, or an unstable “progenitor” state at which both PU. 1 and GATA-1 are expressed at intermediate levels. The authors showed that autoregulation at both PU. 1 and GATA-1 confer stability to the progenitor state. Although both models[32],[33] successfully describe the switch-like, priming properties of the network, they assume cooperativity in bindings( Hill coefficients ≥2) between the transcription factors and the genes for bistability to occur. However, recent experiments[12] suggest that mutual regulation of PU. 1 and GATA-1 seems to occur through the binding of a PU. 1-GATA-1 heterodimer to the PU. 1 and GATA-1 genes, with little or no evidence of regulation due to higher order multimers, of PU. 1–GATA-1. Furthermore, there is no evidence that the autoregulation at both PU. 1 and GATA-1 occurs through the binding of dimers. As we will demonstrate in our model, which is based upon these experimental facts, the nature of the bindings plays an important role—simple heterodimeric repressive bindings between PU. 1 and GATA-1 and monomeric autoregulatory bindings do not suffice for bistability( see Text S1 and Figure S1). As a consequence, an additional mechanism must be involved to make this mutually antagonistic pair function as a bistable switch. Several cofactors of PU. 1 and GATA-1 are known to bind on their target genes( see e. g.[3]–[5] and references therein). We therefore propose the existence of an additional gene X, which is regulated by one of the mutually antagonistic partners, and furthermore is recruited by it, to bind to the other, as a repressor. This mechanism provides the necessary feedback required for bistable behavior. On the other hand, suppression of X( see Figure 1A), leads to a loss of the cooperativity and hence switch-like state, and therefore leads to a primed state. Hematopoiesis is a hierarchically structured process with a series of progenitors or intermediates which serve as semi-stable and restricted states for future lineage decisions. This organization implies that network information must be handed over from one cell type to another in a way that maintains prior settings and precludes reversibility. Here we have examined the principles of how hand-over and irreversibility might be achieved in the context of the pair of transcription factors and FOG-1. These factors, which are responsible for eosinophil lineage commitment, are located downstream of GATA-1–PU. 1 and are themselves mutually antagonistic[7],[34]. As we will discuss later, the –FOG-1 pair first inherits the state of its master genes, PU. 1 and GATA-1, and then further reinforces the decision, by feeding back positively. The positive feedback leads to irreversible commitment. Understanding details of this mechanism therefore provides insights into how the commitment can be reprogrammed.
Discussion:
We have devised a simple model for the PU. 1-GATA-1 genetic switch which, in addition to known interactions, involves a feedforward mechanism through a connector gene X. This mechanism provides the required cooperativity resulting in a bistable switch. In addition, if X is suppressed the cooperativity of the system is lost, and it becomes possible to have both PU. 1 and GATA-1 at reasonably expressed levels—the primed state. The network components therefore regulate cooperativity, which can be affected by external signals. It is interesting to note that, a similar regulatory scheme, in which a connector gene( X) bridges the master regulators, through a feedforward structure[38],[39] and where these master regulators interact directly with each other and are autoregulatory, has in fact been identified in human hepatocytes[40]. Hence, future work could explore computational models, to query such similar architectures. The second issue is how irreversibility of the erythroid-myeloid lineage switch can be achieved through feedback from other lineage components, namely FOG-1–. The switch-like behavior exhibited by the PU. 1–GATA-1 network is first ‘inherited’ by the downstream mutually antagonistic pair FOG-1– as GATA-1 communicates this decision to FOG-1. Then the positive feedback from into PU. 1 further supports this decision, which leads to an irreversible commitment. In addition, autoregulation of further strengthens this positive feedback. Lineage decisions communicated to downstream genes, which in turn feed back to its master regulators, provides an attractive mechanism for robust commitment from a design principle perspective—unless the downstream program is not fully implemented, the master switch is not irreversibly ON. The system can be reprogrammed by reducing the feedback from GATA-1 downstream to FOG-1, or by the upstream activation of to PU. 1. This reduces the strength of the positive feedback of PU. 1 on itself and hence the genetic switch can be made reversible. As discussed in[6], specific combinations of transcription factors give rise to distinct lineages in the hematopoietic system. This is achieved in the present model due to the interaction of the inherent positive and negative feedbacks which give rise to stable dynamical states. Hence, GATA-1 and FOG-1 give rise to erythroid/megakaryocytic lineage, PU. 1 and C/EBP give rise to the myeloid lineage. Our model can also allow for intermediate levels of GATA-1 and high levels of, which specifies eosinophils. This can be achieved through reduced feedback from into PU. 1, allowing to reach high levels of autoregulation, and exciting GATA-1 through the external signal A. Also, in support of our model is the observation of the reprogramming of B-cells into myeloid lineages by over-expressing[41],[42]. Referring to Figure 3, when is ON, PU. 1 is induced. Identification of the X gene should be possible through loss-of-function studies of the PU. 1–GATA-1 system. Combining ChIP-chip with gene expression experiments[43] for PU. 1 and GATA-1 would be crucial. Specifically, with the particular scheme that we model, in the erythroid lineage, X is fully expressed, whereas in the myeloid lineage, X is shut down. It would seem obvious that a strong candidate for the X gene could be none other than FOG-1, since GATA-1 and FOG-1, together regulate several downstream targets[7]. However, as discussed in the previous section, a model with FOG-1 as the X gene, even though allowing the system to be bistable, may make the primed state more difficult to achieve. Mutual antagonism among pairs of genes has been suggested as a general mechanism for lineage commitment[5],[7]. In addition there are several examples[6],[14] where upstream pairs of antagonistic master genes prime and regulate downstream genes which are also antagonistic. For instance, EKLF–Fli-1[4],[5], inherits the PU. 1/GATA-1 decision, and further regulates the erythroid lineage. Using our current model as an illustration, we hypothesize that lineage commitment in an architecture which consists of layers of antagonistic pairs of genes connected such that the lower levels reinforce the upper level decisions, results in positive feedback, giving robust lineage commitment. One issue not addressed here are the effects of noise. Stochasticity in gene expression has now been both theoretically as well as experimentally explored and been shown to be due to both intrinsic as well as extrinsic factors[44]–[46]. Recent investigations have also explored stochasticity in genetic switches[47],[48], which show the effects of switching dynamics due to molecule number fluctuations. One of our future goals is to investigate the effects of noise on the irreversibility of the PU. 1-GATA-1 switch.
An important question in developmental biology is how different lineage choices are regulated at the genetic level . Robust lineage decisions are implemented by genetic switches , whereby one set of master genes are ON and another set are OFF , leading to a specific expression pattern of genes for a particular lineage . We develop a computational model to illustrate these principles as applied to the hematopoietic erythroid-myeloid lineage choice , where two master regulator genes , PU . 1 and GATA-1 , function as a genetic switch . The model , which is based upon known interactions , suggests missing interactions between the master genes , which we hypothesize , so as to reproduce the desired dynamics . Furthermore , there exist feedback interactions between the master genes and their downstream targets . When these are included in the model , the dynamics imply that the feedback is responsible for irreversible commitment . Our results suggest the search for missing interactions between the master genes in terms of a coregulated cofactor . The second important result of the model is that reprogramming irreversible cell fate may be possible by perturbing feedback regulation between the master genes and their downstream targets . Hence , dynamical modeling provides prediction of novel mechanisms and also strategies for reprogramming the fates of cells .