A Mathematical Framework for Understanding Four-Dimensional Heterogeneous Differentiation of $$\hbox {CD4}^{+}$$ CD4 + T Cells

Hong, Tian; Oguz, Cihan; Tyson, John J.

doi:10.1007/s11538-015-0076-6

Cited by 18 publications

(19 citation statements)

References 49 publications

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“…Multiple intermediate cell states may arise from complex gene regulatory networks with interconnected positive feedback loops [12] [13]. It is conceivable that the formation of more intermediate cells would require more complex gene regulatory networks, which in turn need some other strategies and/or more energy to control.…”

Section: Discussionmentioning

confidence: 99%

“…In this case, the parent vector x is replaced by the offspring vector u in the next generation. The DE algorithm was previously shown to be efficient in optimizing models for biological systems [13]. With this algorithm, we iteratively searched for a newer set of parameter values that provided a better cost to the objective function Φ( x ) than the previous set until the cost converged to the most optimal value.…”

Section: Mathematical Models and Stochastic Simulation Of Multiplementioning

confidence: 99%

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Controlling stochasticity in epithelial-mesenchymal transition through multiple intermediate cellular states

Ta¹,

Nie²,

Hong³

2016

DCDS-B

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Epithelial-mesenchymal transition (EMT) is an instance of cellular plasticity that plays critical roles in development, regeneration and cancer progression. Recent studies indicate that the transition between epithelial and mesenchymal states is a multi-step and reversible process in which several intermediate phenotypes might coexist. These intermediate states correspond to various forms of stem-like cells in the EMT system, but the function of the multi-step transition or the multiple stem cell phenotypes is unclear. Here, we use mathematical models to show that multiple intermediate phenotypes in the EMT system help to attenuate the overall fluctuations of the cell population in terms of phenotypic compositions, thereby stabilizing a heterogeneous cell population in the EMT spectrum. We found that the ability of the system to attenuate noise on the intermediate states depends on the number of intermediate states, indicating the stem-cell population is more stable when it has more sub-states. Our study reveals a novel advantage of multiple intermediate EMT phenotypes in terms of systems design, and it sheds light on the general design principle of heterogeneous stem cell population.

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Section: Discussionmentioning

confidence: 99%

Section: Mathematical Models and Stochastic Simulation Of Multiplementioning

confidence: 99%

Controlling stochasticity in epithelial-mesenchymal transition through multiple intermediate cellular states

Ta¹,

Nie²,

Hong³

2016

DCDS-B

Self Cite

View full text Add to dashboard Cite

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“…The advantage of such metrics is that the scoring is robust to the change of individual genes. However, performing clustering on cells based on low-dimensional scores has the disadvantage of missing useful information in high-dimensional gene expression space, which has even greater potentials to reveal multiple attractors (77). This can be seen in part in the scores of E and M gene subclusters, in that the initial increase in E score during the time course appears to be driven by a specific subset of epithelial genes with distinct regulation by EMT factors.…”

Section: Discussionmentioning

confidence: 99%

Integrative Transcriptomic Analysis Reveals a Multiphasic Epithelial–Mesenchymal Spectrum in Cancer and Non-tumorigenic Cells

et al. 2020

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Epithelial-mesenchymal transition (EMT), the conversion between rigid epithelial cells and motile mesenchymal cells, is a reversible cellular process involved in tumorigenesis, metastasis, and chemoresistance. Numerous studies have found that several types of tumor cells show a high degree of cell-to-cell heterogeneity in terms of their gene expression signatures and cellular phenotypes related to EMT. Recently, the prevalence and importance of partial or intermediate EMT states have been reported. It is unclear, however, whether there is a general pattern of cancer cell distribution in terms of the overall expression of epithelial-related genes and mesenchymal-related genes, and how this distribution is related to EMT process in normal cells. In this study, we performed integrative transcriptomic analysis that combines cancer cell transcriptomes, time course data of EMT in non-tumorigenic epithelial cells, and epithelial cells with perturbations of key EMT factors. Our statistical analysis shows that cancer cells are widely distributed in the EMT spectrum, and the majority of these cells can be described by an EMT path that connects the epithelial and the mesenchymal states via a hybrid expression region in which both epithelial genes and mesenchymal genes are highly expressed overall. We found that key patterns of this EMT path are observed in EMT progression in non-tumorigenic cells and that transcription factor ZEB1 plays a key role in defining this EMT path via diverse gene regulatory circuits connecting to epithelial genes. We performed Gene Set Variation Analysis to show that the cancer cells at hybrid EMT states also possess hybrid cellular phenotypes with both high migratory and high proliferative potentials. Our results reveal critical patterns of cancer cells in the EMT spectrum and their relationship to the EMT process in normal cells, and provide insights into the mechanistic basis of cancer cell heterogeneity and plasticity.

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“…Multiple runs of optimization using differential evolution algorithm was used, and 500 converged parameter sets for each circuit were used for comparison. This optimization method was previously used for finding optimum parameter sets and for comparing the performances of regulatory circuits [58,101,102].…”

Section: Methodsmentioning

confidence: 99%

An enriched network motif family regulates multistep cell fate transitions with restricted reversibility

Bailey

et al. 2018

Preprint

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Multistep cell fate transitions with stepwise changes of transcriptional profiles are common to many developmental, regenerative and pathological processes. The multiple intermediate cell lineage states can serve as differentiation checkpoints or branching points for channeling cells to more than one lineages. However, mechanisms underlying these transitions remain elusive. Here, we explored gene regulatory circuits that can generate multiple intermediate cellular states with stepwise modulations of transcription factors. With unbiased searching in the network topology space, we found a motif family containing a large set of networks can give rise to four attractors with the stepwise regulations of transcription factors, which limit the reversibility of three consecutive steps of the lineage transition. We found that there is an enrichment of these motifs in a transcriptional network controlling the early T cell development, and a mathematical model based on this network recapitulates multistep transitions in the early T cell lineage commitment. By calculating the energy landscape and minimum action paths for the T cell model, we quantified the stochastic dynamics of the critical factors in response to the differentiation signal with fluctuations. These results are in good agreement with experimental observations and they suggest the stable characteristics of the intermediate states in the T cell differentiation. These dynamical features may help to direct the cells to correct lineages during development. Our findings provide general design principles for multistep cell linage transitions and new insights into the early T cell development. The network motifs containing a large family of topologies can be useful for analyzing diverse biological systems with multistep transitions. Author summary The functions of cells are dynamically controlled in many biological processes including development, regeneration and disease progression. Cell fate transition, or the switch of cellular functions, often involves multiple steps. The intermediate stages of the transition provide the biological systems with the opportunities to regulate the transitions in a precise manner. These transitions are controlled by key regulatory genes of which the expression shows stepwise patterns, but how the interactions of these genes can determine the multistep processes were unclear. Here, we present a comprehensive analysis on the design principles of gene circuits that govern multistep cell fate transition. We found a large network family with common structural features that can generate systems with the ability to control three consecutive steps of the transition. We found that this type of networks is enriched in a gene circuit controlling the development of T lymphocyte, a crucial type of immune cells. We performed mathematical modeling using this gene circuit and we recapitulated the stepwise and irreversible loss of stem cell properties of the developing T lymphocytes. Our findings can be useful to analyze a wide range of ge...

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A Mathematical Framework for Understanding Four-Dimensional Heterogeneous Differentiation of $$\hbox {CD4}^{+}$$ CD4 + T Cells

Cited by 18 publications

References 49 publications

Controlling stochasticity in epithelial-mesenchymal transition through multiple intermediate cellular states

Controlling stochasticity in epithelial-mesenchymal transition through multiple intermediate cellular states

Integrative Transcriptomic Analysis Reveals a Multiphasic Epithelial–Mesenchymal Spectrum in Cancer and Non-tumorigenic Cells

An enriched network motif family regulates multistep cell fate transitions with restricted reversibility

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