Mesenchymal stem cells MSCs are multipotent stromal cells existing within bone marrow and other adult tissues, which are able to differentiate into different skeletal tissue such as bone, cartilage and fat. A range of transcription factors are known to be involved in the regulation of osteogenesis, with two of the more widely studied being Runx2 Cbfa1 and Osterix. Runx2 is regarded the major transcription factor controlling osteoblast commitment and differentiation.
And as with adipogenesis and osteogenesis, there is also an apparent master regulator of chondrogenesis: Sox9. Hematopoietic and endothelial cells are all originated from a common progenitor cell which is hemangioblast. During the early phases of mesoderm development, hemangioblast specification occurs and is promoted by some transcription factors expression. It has been reported that Lim-only protein LMO2 can enhance the proliferation and differentiation of hemangioblasts. In addition, stem cell leukemia SCL , a basic helix-loop-helix bHLH transcription factor, is essential for the specification and function of the hemangioblast.
SCL may be a direct target of hedgehog signaling during hemangioblast specification. The hepatic and pancreatic progenitor cells that give rise to liver and pancreas are specified and regulated by some transcription factors. As for hepatic progenitor cells, they will differentiate into hepatocytes and cholangiocytes with the regulation of TBX3. Their pluripotential character is maintained by a group of transcription factors. Among these factors, SOX plays a crucial role not only in regulating pluripotency, but also in mediating self-renewal and differentiation.
Cancer stem cells CSCs are thought to drive uncontrolled tumor growth. A lot of evidences indicate that the overexpression of these three genes occurs in human malignancies and are relevant to humor transformation, tumorigenicity, tumor metastasis. Although they both share the property of self-renewal, ESCs emphasize differentiation, whereas CSCs emphasize proliferation. Several transcription factors are related to some human diseases.
However, the reconstruction of a sequence of changes in molecular processes and development of regulatory networks using single cell data are still challenging problems in bioinformatics and systems biology. A common theme here is that co-regulators, such as Eto2 and Zfpm1, are thought to bind DNA indirectly through interactions with conventional transcription factors, such as Scl and Gata1, and by doing so convert the latter from activators to repressors.
Interestingly, in our network, these negative co-regulators are themselves activated by the conventional TFs, thus generating an abundance of incoherent feed-forward loops within the wider network. Simple negative feedback loops have previously been proposed to result in oscillatory expression of important cell fate regulators Hirata et al.wallrurischeckbo.ga/who-killed-irv.php
Transcriptional regulatory networks governing stem cell differentiation into hepatocytes in vitro
To better understand the potential for oscillatory behaviour in increasingly complex networks, future developments might need to include building more fine-grained models, such as the use of Petri nets, which can be readily adapted to move from a Boolean range of values towards discrete multi-valued expression levels Bonzanni et al. Within the context of our 11 gene HSPC network topology, several expression states that correspond to the differentiated cell types shown in Figure 3 can automatically revert to the stem cell state, suggesting a potential for spontaneous reversion of differentiated cells to the immature stem cell phenotype details in Supplementary Table S3.
A recent model of the myeloid lineage Krumsiek et al. A likely explanation for the contrast between this study and our findings may be that rather than excluding the stem cell state, we explicitly focused on regulatory interactions within HSPCs. It is likely that some of these commitment events will transmit extracellular signals to the nucleus, to modulate epigenetic processes that regulate the availability of regulatory regions for transcription factor binding.
Comprehensive exploration of the state space dictated by our experimentally validated HSPC network topology resulted in a set of 32 interconnected states, which together constitute a stable state with a gene expression pattern consistent with HSPCs. However, only a single internal state in the HSPC attractor matched expression levels of all HSPC associated genes, whereas all others expressed different subsets of genes, suggesting possible heterogeneity between discrete expression states. The heterogeneous steady-state predicted by our model might at first have been considered an artefact because of either the unavoidably partial knowledge we have about the system, or introduced by the high level of discretization used i.
However, we believe that on the contrary, our results may provide potentially important new insights into the nature of transcriptional control of stem cells and differentiation as outlined below: first, the striking correlation between gene expression profiling results from single HSPCs and the heterogeneous states predicted by our network Fig. Taken together, these observations suggest that the stem cell state is composed of a discrete set of sub-states with a substantial degree of oscillations in gene expression, which includes genes thought of as central regulators of stem cell fate.
Of note, this concept is largely consistent with the recently introduced theory of non-genetic micro-heterogeneity in multi-potential stem cell populations Huang, It might at first glance seem difficult to reconcile such oscillations and the resultant transcriptional heterogeneity with the model of multi-lineage priming. This latter concept was founded on the observation that some HSPCs display low-level co-expression of cytokine receptor genes affiliated with divergent differentiation pathways Hu et al.
Consequently, HSPCs have widely been thought of as highly promiscuous with widespread co-expression rather than only expressing subsets of genes. However, in addition to demonstrating the potential for multi-lineage priming, the original article in Hu et al. Both multi-lineage priming of cytokine receptor genes and expression of HSPC affiliated transcription factors, therefore, show cellular heterogeneity consistent with oscillating expression in individual HSPCs.
Based on the results presented in this article, cellular heterogeneity of multi-lineage priming may, therefore, be hardwired into HSPC regulatory networks rather than being a consequence of low-level, non-specific gene expression noise as had been speculated previously. This in turn would suggest that characterization of the underlying mechanisms will provide novel insights into the functional role of multi-lineage priming as a key mediator of differentiation.
Regulatory Networks: Reality check for transposon enhancers | eLife
Our model also suggests the possibility of triggering cross-lineage transitions, which may be exceedingly rare in normal cells but have been observed experimentally Di Tullio et al. For example, a leukaemia may be of myeloid phenotype when a patient first presents, but of lymphoid phenotype at relapse Chucrallah et al. A better understanding of cross-lineage transition paths may, therefore, aid to develop therapies for relapsed patients, who currently have a poor prognosis. Cross-lineage transitions may also be exploited in the field of regenerative medicine, where protocols are being developed to for example make macrophages out of B-cells Bussmann et al.
The lack of explicit commitment in the mature cell types in our model, as discussed earlier in the text, is consistent with the notion that entry into a lineage may at first be reversible. This is in line with findings from a recent model of the myeloid lineage that exhibits a heterogeneous entry into mature cell type attractor states Krumsiek et al.
Transcriptional regulatory networks & blood stem cells
In many cases, the particular order of external triggers applied in our model to exit the HSPC state seems not to be critical. Similarly multiple transition paths to mature cell type states show order-independence of individual genes switched, consistent with the notion of network coalescence Tipping et al. Thus, the emerging picture seems to be that, starting from a heterogeneous HSPC stable state, external stimuli may trigger different initial responses within individual cells in a heterogeneous stem cell population, but ultimately resolve into a clearly demarcated mature cell state.
As the stem cell state space is composed of a set of regulatory states with inter-conversions between them dictated by the network topology, the question arises to what extent knowledge of network wiring may increase our ability to manipulate stem cell fate choices. In this study, we show that specific differentiation triggers can be modelled successfully and inform specific hypotheses for subsequent experimental testing.
This in turn suggests that the distribution of stem cell internal states has the potential to influence the propensity of a stem cell to choose between divergent differentiation choices. A mechanistic understanding of the underlying processes would have important scientific and clinical implications. For example, altering the levels of Gata2 has recently been shown to affect the ratio between cycling and quiescent HSPCs Tipping et al. From a translational point of view, in vitro production of specific blood cell types from HSPCs has the potential to provide safer and cheaper alternatives to blood transfusions.
However, directed differentiation in vitro remains disappointingly inefficient, suggesting that knowledge of the underlying regulatory networks is critical for the development of new protocols. Finally, treatment responses for patients carrying the same leukaemogenic mutations can be different.
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The authors would like to thank Mark Ibberson for reading the manuscript and providing helpful comments. Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide.
Sign In or Create an Account. Sign In. Advanced Search. Article Navigation. Close mobile search navigation Article Navigation. Volume Article Contents. Hard-wired heterogeneity in blood stem cells revealed using a dynamic regulatory network model Nicola Bonzanni. Oxford Academic. Google Scholar. Abhishek Garg. Anton Feenstra. Sarah Kinston. Diego Miranda-Saavedra.
Jaap Heringa. Ioannis Xenarios. Cite Citation. Permissions Icon Permissions. Abstract Motivation: Combinatorial interactions of transcription factors with cis -regulatory elements control the dynamic progression through successive cellular states and thus underpin all metazoan development. Open in new tab Download slide. Transcriptional regulation of the stem cell leukemia gene by PU.
Search ADS. Executing multicellular differentiation: quantitative predictive modelling of C. Google Preview. Hematopoietic fingerprints: an expression database of stem cells and their progeny. Computational modeling of the hematopoietic erythroid-myeloid switch reveals insights into cooperativity, priming, and irreversibility. Adult acute lymphoblastic leukemia at relapse. Cytogenetic, immunophenotypic, and molecular changes. Di Tullio. Genome-wide identification of cis-regulatory sequences controlling blood and endothelial development.
Transcription of the SCL gene in erythroid and CD34 positive primitive myeloid cells is controlled by a complex network of lineage-restricted chromatin-dependent and chromatin-independent regulatory elements. Establishing the transcriptional programme for blood: the SCL stem cell enhancer is regulated by a multiprotein complex containing Ets and GATA factors. Transcription factor-mediated lineage switching reveals plasticity in primary committed progenitor cells. Oscillatory expression of the bHLH factor Hes1 regulated by a negative feedback loop.
Multilineage gene expression precedes commitment in the hemopoietic system.
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Genetic reconstruction of a functional transcriptional regulatory network. A methodology for the structural and functional analysis of signaling and regulatory networks.
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