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      A robust method for designing multistable systems by embedding bistable subsystems

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          Abstract

          Although multistability is an important dynamic property of a wide range of complex systems, it is still a challenge to develop mathematical models for realising high order multistability using realistic regulatory mechanisms. To address this issue, we propose a robust method to develop multistable mathematical models by embedding bistable models together. Using the GATA1-GATA2-PU.1 module in hematopoiesis as the test system, we first develop a tristable model based on two bistable models without any high cooperative coefficients, and then modify the tristable model based on experimentally determined mechanisms. The modified model successfully realises four stable steady states and accurately reflects a recent experimental observation showing four transcriptional states. In addition, we develop a stochastic model, and stochastic simulations successfully realise the experimental observations in single cells. These results suggest that the proposed method is a general approach to develop mathematical models for realising multistability and heterogeneity in complex systems.

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          From haematopoietic stem cells to complex differentiation landscapes.

          The development of mature blood cells from haematopoietic stem cells has long served as a model for stem-cell research, with the haematopoietic differentiation tree being widely used as a model for the maintenance of hierarchically organized tissues. Recent results and new technologies have challenged the demarcations between stem and progenitor cell populations, the timing of cell-fate choices and the contribution of stem and multipotent progenitor cells to the maintenance of steady-state blood production. These evolving views of haematopoiesis have broad implications for our understanding of the functions of adult stem cells, as well as the development of new therapies for malignant and non-malignant haematopoietic diseases.
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            Hematopoiesis: an evolving paradigm for stem cell biology.

            Establishment and maintenance of the blood system relies on self-renewing hematopoietic stem cells (HSCs) that normally reside in small numbers in the bone marrow niche of adult mammals. This Review describes the developmental origins of HSCs and the molecular mechanisms that regulate lineage-specific differentiation. Studies of hematopoiesis provide critical insights of general relevance to other areas of stem cell biology including the role of cellular interactions in development and tissue homeostasis, lineage programming and reprogramming by transcription factors, and stage- and age-specific differences in cellular phenotypes.
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              Human haematopoietic stem cell lineage commitment is a continuous process

              Blood formation is believed to occur through step-wise progression of haematopoietic stem cells (HSCs) following a tree-like hierarchy of oligo-, bi- and unipotent progenitors. However, this model is based on the analysis of predefined flow-sorted cell populations. Here we integrated flow cytometric, transcriptomic and functional data at single-cell resolution to quantitatively map early differentiation of human HSCs towards lineage commitment. During homeostasis, individual HSCs gradually acquire lineage biases along multiple directions without passing through discrete hierarchically organized progenitor populations. Instead, unilineage-restricted cells emerge directly from a “Continuum of LOw primed UnDifferentiated hematopoietic stem- and progenitor cells” (CLOUD-HSPCs). Distinct gene expression modules operate in a combinatorial manner to control stemness, early lineage priming and the subsequent progression into all major branches of haematopoiesis. These data reveal a continuous landscape of human steady state haematopoiesis downstream of HSCs and provide a basis for the understanding of hematopoietic malignancies.
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                Author and article information

                Contributors
                Tianhai.Tian@monash.edu
                Journal
                NPJ Syst Biol Appl
                NPJ Syst Biol Appl
                NPJ Systems Biology and Applications
                Nature Publishing Group UK (London )
                2056-7189
                25 March 2022
                25 March 2022
                2022
                : 8
                : 10
                Affiliations
                [1 ]GRID grid.1002.3, ISNI 0000 0004 1936 7857, School of Mathematics, , Monash University, ; Melbourne, VIC Australia
                [2 ]GRID grid.12981.33, ISNI 0000 0001 2360 039X, School of Mathematics and Statistics, , Sun Yet-Sen University, ; Guangzhou, China
                Author information
                http://orcid.org/0000-0003-2871-5473
                http://orcid.org/0000-0001-6191-0209
                Article
                220
                10.1038/s41540-022-00220-1
                8956579
                35338169
                545ee0c1-e815-497c-ab36-639cbb427891
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 14 July 2021
                : 15 February 2022
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001809, National Natural Science Foundation of China (National Science Foundation of China);
                Award ID: 11931019
                Award ID: 11775314
                Award Recipient :
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                © The Author(s) 2022

                multistability,regulatory networks
                multistability, regulatory networks

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