1
|
Bolondi A, Law BK, Kretzmer H, Gassaloglu SI, Buschow R, Riemenschneider C, Yang D, Walther M, Veenvliet JV, Meissner A, Smith ZD, Chan MM. Reconstructing axial progenitor field dynamics in mouse stem cell-derived embryoids. Dev Cell 2024; 59:1489-1505.e14. [PMID: 38579718 PMCID: PMC11187653 DOI: 10.1016/j.devcel.2024.03.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 12/13/2023] [Accepted: 03/12/2024] [Indexed: 04/07/2024]
Abstract
Embryogenesis requires substantial coordination to translate genetic programs to the collective behavior of differentiating cells, but understanding how cellular decisions control tissue morphology remains conceptually and technically challenging. Here, we combine continuous Cas9-based molecular recording with a mouse embryonic stem cell-based model of the embryonic trunk to build single-cell phylogenies that describe the behavior of transient, multipotent neuro-mesodermal progenitors (NMPs) as they commit into neural and somitic cell types. We find that NMPs show subtle transcriptional signatures related to their recent differentiation and contribute to downstream lineages through a surprisingly broad distribution of individual fate outcomes. Although decision-making can be heavily influenced by environmental cues to induce morphological phenotypes, axial progenitors intrinsically mature over developmental time to favor the neural lineage. Using these data, we present an experimental and analytical framework for exploring the non-homeostatic dynamics of transient progenitor populations as they shape complex tissues during critical developmental windows.
Collapse
Affiliation(s)
- Adriano Bolondi
- Department of Genome Regulation, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany
| | - Benjamin K Law
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA; Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA
| | - Helene Kretzmer
- Department of Genome Regulation, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany
| | - Seher Ipek Gassaloglu
- Department of Genome Regulation, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany; Max Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany
| | - René Buschow
- Microscopy Core Facility, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany
| | | | - Dian Yang
- Department of Molecular Pharmacology and Therapeutics & Systems Biology, Columbia University, New York, NY 10032, USA
| | - Maria Walther
- Department of Genome Regulation, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany
| | - Jesse V Veenvliet
- Max Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany; Cluster of Excellence Physics of Life, Technische Universität Dresden, 01307 Dresden, Germany; Center for Systems Biology Dresden, 01307 Dresden, Germany
| | - Alexander Meissner
- Department of Genome Regulation, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany; Institute of Chemistry and Biochemistry, Freie Universität Berlin, 14195 Berlin, Germany.
| | - Zachary D Smith
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06519, USA.
| | - Michelle M Chan
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA; Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA.
| |
Collapse
|
2
|
Glass DS, Bren A, Vaisbourd E, Mayo A, Alon U. A synthetic differentiation circuit in Escherichia coli for suppressing mutant takeover. Cell 2024; 187:931-944.e12. [PMID: 38320549 PMCID: PMC10882425 DOI: 10.1016/j.cell.2024.01.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 11/27/2023] [Accepted: 01/16/2024] [Indexed: 02/08/2024]
Abstract
Differentiation is crucial for multicellularity. However, it is inherently susceptible to mutant cells that fail to differentiate. These mutants outcompete normal cells by excessive self-renewal. It remains unclear what mechanisms can resist such mutant expansion. Here, we demonstrate a solution by engineering a synthetic differentiation circuit in Escherichia coli that selects against these mutants via a biphasic fitness strategy. The circuit provides tunable production of synthetic analogs of stem, progenitor, and differentiated cells. It resists mutations by coupling differentiation to the production of an essential enzyme, thereby disadvantaging non-differentiating mutants. The circuit selected for and maintained a positive differentiation rate in long-term evolution. Surprisingly, this rate remained constant across vast changes in growth conditions. We found that transit-amplifying cells (fast-growing progenitors) underlie this environmental robustness. Our results provide insight into the stability of differentiation and demonstrate a powerful method for engineering evolutionarily stable multicellular consortia.
Collapse
Affiliation(s)
- David S Glass
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel.
| | - Anat Bren
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Elizabeth Vaisbourd
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Avi Mayo
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Uri Alon
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel.
| |
Collapse
|
3
|
Caldwell MG, Lander AD. The inherent fragility of collective proliferative control. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.23.576783. [PMID: 38328163 PMCID: PMC10849578 DOI: 10.1101/2024.01.23.576783] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
Tissues achieve and maintain their sizes through active feedback, whereby cells collectively regulate proliferation and differentiation so as to facilitate homeostasis and the ability to respond to disturbances. One of the best understood feedback mechanisms-renewal control-achieves remarkable feats of robustness in determining and maintaining desired sizes. Yet in a variety of biologically relevant situations, we show that stochastic effects should cause rare but catastrophic failures of renewal control. We define the circumstances under which this occurs and raise the possibility such events account for important non-genetic steps in the development of cancer. We further suggest that the spontaneous stochastic reversal of these events could explain cases of cancer normalization or dormancy following treatment. Indeed, we show that the kinetics of post-treatment recurrence for many cancers are often better fit by a model of stochastic re-emergence due to loss of collective proliferative control, than by deterministic models of cancer relapse.
Collapse
Affiliation(s)
- Michael G. Caldwell
- Center for Complex Biological Systems, University of California, Irvine, CA 92697-2300
| | - Arthur D. Lander
- Center for Complex Biological Systems, University of California, Irvine, CA 92697-2300
- Department of Developmental and Cell Biology, University of California, Irvine, CA 92697-2300
- Department of Biomedical Engineering, University of California, Irvine, CA 92697-2300
| |
Collapse
|
4
|
Daneshpour H, van den Bersselaar P, Chao CH, Fazzio TG, Youk H. Macroscopic quorum sensing sustains differentiating embryonic stem cells. Nat Chem Biol 2023; 19:596-606. [PMID: 36635563 PMCID: PMC10154202 DOI: 10.1038/s41589-022-01225-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 11/14/2022] [Indexed: 01/14/2023]
Abstract
Cells can secrete molecules that help each other's replication. In cell cultures, chemical signals might diffuse only within a cell colony or between colonies. A chemical signal's interaction length-how far apart interacting cells are-is often assumed to be some value without rigorous justifications because molecules' invisible paths and complex multicellular geometries pose challenges. Here we present an approach, combining mathematical models and experiments, for determining a chemical signal's interaction length. With murine embryonic stem (ES) cells as a testbed, we found that differentiating ES cells secrete FGF4, among others, to communicate over many millimeters in cell culture dishes and, thereby, form a spatially extended, macroscopic entity that grows only if its centimeter-scale population density is above a threshold value. With this 'macroscopic quorum sensing', an isolated macroscopic, but not isolated microscopic, colony can survive differentiation. Our integrated approach can determine chemical signals' interaction lengths in generic multicellular communities.
Collapse
Affiliation(s)
- Hirad Daneshpour
- Kavli Institute of Nanoscience, Delft, The Netherlands
- Department of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Pim van den Bersselaar
- Kavli Institute of Nanoscience, Delft, The Netherlands
- Department of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Chun-Hao Chao
- Department of Molecular, Cell, and Cancer Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Thomas G Fazzio
- Department of Molecular, Cell, and Cancer Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Hyun Youk
- Department of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA.
- CIFAR Azrieli Global Scholars Program, CIFAR, Toronto, ON, Canada.
| |
Collapse
|
5
|
Rodriguez J, Iniguez A, Jena N, Tata P, Liu ZY, Lander AD, Lowengrub J, Van Etten RA. Predictive nonlinear modeling of malignant myelopoiesis and tyrosine kinase inhibitor therapy. eLife 2023; 12:e84149. [PMID: 37115622 PMCID: PMC10212564 DOI: 10.7554/elife.84149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 04/26/2023] [Indexed: 04/29/2023] Open
Abstract
Chronic myeloid leukemia (CML) is a blood cancer characterized by dysregulated production of maturing myeloid cells driven by the product of the Philadelphia chromosome, the BCR-ABL1 tyrosine kinase. Tyrosine kinase inhibitors (TKIs) have proved effective in treating CML, but there is still a cohort of patients who do not respond to TKI therapy even in the absence of mutations in the BCR-ABL1 kinase domain that mediate drug resistance. To discover novel strategies to improve TKI therapy in CML, we developed a nonlinear mathematical model of CML hematopoiesis that incorporates feedback control and lineage branching. Cell-cell interactions were constrained using an automated model selection method together with previous observations and new in vivo data from a chimeric BCR-ABL1 transgenic mouse model of CML. The resulting quantitative model captures the dynamics of normal and CML cells at various stages of the disease and exhibits variable responses to TKI treatment, consistent with those of CML patients. The model predicts that an increase in the proportion of CML stem cells in the bone marrow would decrease the tendency of the disease to respond to TKI therapy, in concordance with clinical data and confirmed experimentally in mice. The model further suggests that, under our assumed similarities between normal and leukemic cells, a key predictor of refractory response to TKI treatment is an increased maximum probability of self-renewal of normal hematopoietic stem cells. We use these insights to develop a clinical prognostic criterion to predict the efficacy of TKI treatment and design strategies to improve treatment response. The model predicts that stimulating the differentiation of leukemic stem cells while applying TKI therapy can significantly improve treatment outcomes.
Collapse
MESH Headings
- Mice
- Animals
- Tyrosine Kinase Inhibitors
- Protein Kinase Inhibitors/pharmacology
- Protein Kinase Inhibitors/therapeutic use
- Drug Resistance, Neoplasm
- Myelopoiesis
- Fusion Proteins, bcr-abl/genetics
- Fusion Proteins, bcr-abl/pharmacology
- Mice, Transgenic
- Leukemia, Myelogenous, Chronic, BCR-ABL Positive/drug therapy
- Leukemia, Myelogenous, Chronic, BCR-ABL Positive/genetics
Collapse
Affiliation(s)
- Jonathan Rodriguez
- Graduate Program in Mathematical, Computational and Systems Biology, University of California, IrvineIrvineUnited States
- Center for Complex Biological Systems, University of California, IrvineIrvineUnited States
| | - Abdon Iniguez
- Graduate Program in Mathematical, Computational and Systems Biology, University of California, IrvineIrvineUnited States
- Center for Complex Biological Systems, University of California, IrvineIrvineUnited States
| | - Nilamani Jena
- Department of Medicine, University of California, IrvineIrvineUnited States
| | - Prasanthi Tata
- Department of Medicine, University of California, IrvineIrvineUnited States
| | - Zhong-Ying Liu
- Department of Medicine, University of California, IrvineIrvineUnited States
| | - Arthur D Lander
- Center for Complex Biological Systems, University of California, IrvineIrvineUnited States
- Department of Developmental and Cell Biology, University of California, IrvineIrvineUnited States
- Chao Family Comprehensive Cancer Center, University of California, IrvineIrvineUnited States
- Department of Biomedical Engineering, University of California, IrvineIrvineUnited States
| | - John Lowengrub
- Center for Complex Biological Systems, University of California, IrvineIrvineUnited States
- Chao Family Comprehensive Cancer Center, University of California, IrvineIrvineUnited States
- Department of Biomedical Engineering, University of California, IrvineIrvineUnited States
- Department of Mathematics, University of California, IrvineIrvineUnited States
| | - Richard A Van Etten
- Center for Complex Biological Systems, University of California, IrvineIrvineUnited States
- Department of Medicine, University of California, IrvineIrvineUnited States
- Chao Family Comprehensive Cancer Center, University of California, IrvineIrvineUnited States
| |
Collapse
|
6
|
Voices carry. Nat Chem Biol 2023; 19:540-541. [PMID: 36635562 DOI: 10.1038/s41589-022-01238-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
|
7
|
Wang MX, Lander A, Lai PY. Regulatory feedback effects on tissue growth dynamics in a two-stage cell lineage model. Phys Rev E 2021; 104:034405. [PMID: 34654185 PMCID: PMC8585573 DOI: 10.1103/physreve.104.034405] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 08/30/2021] [Indexed: 11/07/2022]
Abstract
Identifying the mechanism of intercellular feedback regulation is critical for the basic understanding of tissue growth control in organisms. In this paper, we analyze a tissue growth model consisting of a single lineage of two cell types regulated by negative feedback signaling molecules that undergo spatial diffusion. By deriving the fixed points for the uniform steady states and carrying out linear stability analysis, phase diagrams are obtained analytically for arbitrary parameters of the model. Two different generic growth modes are found: blow-up growth and final-state controlled growth which are governed by the nontrivial fixed point and the trivial fixed point, respectively, and can be sensitively switched by varying the negative feedback regulation on the proliferation of the stem cells. Analytic expressions for the characteristic timescales for these two growth modes are also derived. Remarkably, the trivial and nontrivial uniform steady states can coexist and a sharp transition occurs in the bistable regime as the relevant parameters are varied. Furthermore, the bistable growth properties allows for the external control to switch between these two growth modes. In addition, the condition for an early accelerated growth followed by a retarded growth can be derived. These analytical results are further verified by numerical simulations and provide insights on the growth behavior of the tissue. Our results are also discussed in the light of possible realistic biological experiments and tissue growth control strategy. Furthermore, by external feedback control of the concentration of regulatory molecules, it is possible to achieve a desired growth mode, as demonstrated with an analysis of boosted growth, catch-up growth and the design for the target of a linear growth dynamic.
Collapse
Affiliation(s)
- Mao-Xiang Wang
- School of Science, Nanjing University of Science and Technology, Nanjing 210094, China
- Department of Developmental and Cell Biology, University of California, Irvine, Irvine, California 92697, USA
- Center for Complex Biological Systems, University of California, Irvine, Irvine, California 92697, USA
| | - Arthur Lander
- Department of Developmental and Cell Biology, University of California, Irvine, Irvine, California 92697, USA
- Center for Complex Biological Systems, University of California, Irvine, Irvine, California 92697, USA
| | - Pik-Yin Lai
- Department of Physics and Center for Complex Systems, National Central University, Chungli District, Taoyuan City, Taiwan 320, Republic of China
| |
Collapse
|
8
|
Biological feedback control-Respect the loops. Cell Syst 2021; 12:477-487. [PMID: 34139160 DOI: 10.1016/j.cels.2021.05.004] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2021] [Accepted: 05/07/2021] [Indexed: 11/21/2022]
Abstract
We, and all organisms, are an evolutionary masterpiece of multiscale feedback control. Feedback loops enable our cells to grow and then stop at the right size, to divide and self-repair, and to respond with agility to their changing environment. Individual cells engage in long range extracellular feedback with other cells, ensuring continued homeostasis of our tissues and organs. Many long ranging feedback loops regulate vital physiological variables. Here, I will argue that focused efforts to understand the properties and constraints of biological feedback control networks should be central to the quest of understanding life. I will also propose many pressing challenges in this field and review conceptual frameworks that might be consequential for addressing them.
Collapse
|
9
|
Lenne PF, Munro E, Heemskerk I, Warmflash A, Bocanegra-Moreno L, Kishi K, Kicheva A, Long Y, Fruleux A, Boudaoud A, Saunders TE, Caldarelli P, Michaut A, Gros J, Maroudas-Sacks Y, Keren K, Hannezo E, Gartner ZJ, Stormo B, Gladfelter A, Rodrigues A, Shyer A, Minc N, Maître JL, Di Talia S, Khamaisi B, Sprinzak D, Tlili S. Roadmap for the multiscale coupling of biochemical and mechanical signals during development. Phys Biol 2021; 18. [PMID: 33276350 PMCID: PMC8380410 DOI: 10.1088/1478-3975/abd0db] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Accepted: 12/04/2020] [Indexed: 12/12/2022]
Abstract
The way in which interactions between mechanics and biochemistry lead to the emergence of complex cell and tissue organization is an old question that has recently attracted renewed interest from biologists, physicists, mathematicians and computer scientists. Rapid advances in optical physics, microscopy and computational image analysis have greatly enhanced our ability to observe and quantify spatiotemporal patterns of signalling, force generation, deformation, and flow in living cells and tissues. Powerful new tools for genetic, biophysical and optogenetic manipulation are allowing us to perturb the underlying machinery that generates these patterns in increasingly sophisticated ways. Rapid advances in theory and computing have made it possible to construct predictive models that describe how cell and tissue organization and dynamics emerge from the local coupling of biochemistry and mechanics. Together, these advances have opened up a wealth of new opportunities to explore how mechanochemical patterning shapes organismal development. In this roadmap, we present a series of forward-looking case studies on mechanochemical patterning in development, written by scientists working at the interface between the physical and biological sciences, and covering a wide range of spatial and temporal scales, organisms, and modes of development. Together, these contributions highlight the many ways in which the dynamic coupling of mechanics and biochemistry shapes biological dynamics: from mechanoenzymes that sense force to tune their activity and motor output, to collectives of cells in tissues that flow and redistribute biochemical signals during development.
Collapse
Affiliation(s)
- Pierre-François Lenne
- Aix-Marseille University, CNRS, IBDM, Turing Center for Living Systems, Marseille, France
| | - Edwin Munro
- Department of Molecular Genetics and Cell Biology, University of Chicago, Chicago, IL 60637, United States of America
| | - Idse Heemskerk
- Department of Cell & Developmental Biology, University of Michigan Medical School, Ann Arbor, MI 48109, United States of America
| | - Aryeh Warmflash
- Department of Biosciences and Bioengineering, Rice University, Houston, TX, 77005, United States of America
| | | | - Kasumi Kishi
- IST Austria, Am Campus 1, 3400 Klosterneuburg, Austria
| | - Anna Kicheva
- IST Austria, Am Campus 1, 3400 Klosterneuburg, Austria
| | - Yuchen Long
- Reproduction et Dévelopement des Plantes, Université de Lyon, École normale supérieure de Lyon, Université Claude Bernard Lyon 1, INRAe, CNRS, 69364 Lyon Cedex 07, France
| | - Antoine Fruleux
- Reproduction et Dévelopement des Plantes, Université de Lyon, École normale supérieure de Lyon, Université Claude Bernard Lyon 1, INRAe, CNRS, 69364 Lyon Cedex 07, France.,LadHyX, CNRS, Ecole polytechnique, Institut Polytechnique de Paris, 91128 Palaiseau Cedex, France
| | - Arezki Boudaoud
- Reproduction et Dévelopement des Plantes, Université de Lyon, École normale supérieure de Lyon, Université Claude Bernard Lyon 1, INRAe, CNRS, 69364 Lyon Cedex 07, France.,LadHyX, CNRS, Ecole polytechnique, Institut Polytechnique de Paris, 91128 Palaiseau Cedex, France
| | - Timothy E Saunders
- Mechanobiology Institute, National University of Singapore, 117411, Singapore
| | - Paolo Caldarelli
- Cellule Pasteur UPMC, Sorbonne Université, rue du Dr Roux, 75015 Paris, France.,Department of Developmental and Stem Cell Biology Institut Pasteur, 75724 Paris, Cedex 15, France.,CNRS UMR3738, 75015 Paris, France
| | - Arthur Michaut
- Department of Developmental and Stem Cell Biology Institut Pasteur, 75724 Paris, Cedex 15, France.,CNRS UMR3738, 75015 Paris, France
| | - Jerome Gros
- Department of Developmental and Stem Cell Biology Institut Pasteur, 75724 Paris, Cedex 15, France.,CNRS UMR3738, 75015 Paris, France
| | - Yonit Maroudas-Sacks
- Department of Physics, Technion-Israel Institute of Technology, Haifa 32000, Israel
| | - Kinneret Keren
- Department of Physics, Technion-Israel Institute of Technology, Haifa 32000, Israel.,Network Biology Research Laboratories and The Russell Berrie Nanotechnology Institute, Technion-Israel Institute of Technology, Haifa 32000, Israel
| | - Edouard Hannezo
- Institute of Science and Technology Austria, Am Campus 1, 3400 Klosterneuburg, Austria
| | - Zev J Gartner
- Department of Pharmaceutical Chemistry, University of California, San Francisco, 600 16th St. Box 2280, San Francisco, CA 94158, United States of America
| | - Benjamin Stormo
- Department of Biology, University of North Carolina-Chapel Hill, Chapel Hill, NC 27599 United States of America
| | - Amy Gladfelter
- Department of Biology, University of North Carolina-Chapel Hill, Chapel Hill, NC 27599 United States of America
| | - Alan Rodrigues
- Laboratory of Morphogenesis, The Rockefeller University, 1230 York Avenue, New York, NY 10065, United States of America
| | - Amy Shyer
- Laboratory of Morphogenesis, The Rockefeller University, 1230 York Avenue, New York, NY 10065, United States of America
| | - Nicolas Minc
- Institut Jacques Monod, Université de Paris, CNRS UMR7592, 15 rue Hélène Brion, 75205 Paris Cedex 13, France
| | - Jean-Léon Maître
- Institut Curie, PSL Research University, Sorbonne Université, CNRS UMR3215, INSERM U934, Paris, France
| | - Stefano Di Talia
- Department of Cell Biology, Duke University Medical Center, Durham NC 27710, United States of America
| | - Bassma Khamaisi
- School of Neurobiology, Biochemistry and Biophysics, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 6997801, Israel
| | - David Sprinzak
- School of Neurobiology, Biochemistry and Biophysics, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 6997801, Israel
| | - Sham Tlili
- Aix-Marseille University, CNRS, IBDM, Turing Center for Living Systems, Marseille, France
| |
Collapse
|
10
|
Lomeli LM, Iniguez A, Tata P, Jena N, Liu ZY, Van Etten R, Lander AD, Shahbaba B, Lowengrub JS, Minin VN. Optimal experimental design for mathematical models of haematopoiesis. J R Soc Interface 2021; 18:20200729. [PMID: 33499768 PMCID: PMC7879761 DOI: 10.1098/rsif.2020.0729] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Accepted: 01/04/2021] [Indexed: 11/12/2022] Open
Abstract
The haematopoietic system has a highly regulated and complex structure in which cells are organized to successfully create and maintain new blood cells. It is known that feedback regulation is crucial to tightly control this system, but the specific mechanisms by which control is exerted are not completely understood. In this work, we aim to uncover the underlying mechanisms in haematopoiesis by conducting perturbation experiments, where animal subjects are exposed to an external agent in order to observe the system response and evolution. We have developed a novel Bayesian hierarchical framework for optimal design of perturbation experiments and proper analysis of the data collected. We use a deterministic model that accounts for feedback and feedforward regulation on cell division rates and self-renewal probabilities. A significant obstacle is that the experimental data are not longitudinal, rather each data point corresponds to a different animal. We overcome this difficulty by modelling the unobserved cellular levels as latent variables. We then use principles of Bayesian experimental design to optimally distribute time points at which the haematopoietic cells are quantified. We evaluate our approach using synthetic and real experimental data and show that an optimal design can lead to better estimates of model parameters.
Collapse
Affiliation(s)
- Luis Martinez Lomeli
- Center for Complex Biological Systems, University of California Irvine, Irvine, CA, USA
| | - Abdon Iniguez
- Center for Complex Biological Systems, University of California Irvine, Irvine, CA, USA
| | - Prasanthi Tata
- Division of Hematology/Oncology, University of California Irvine, Irvine, CA, USA
| | - Nilamani Jena
- Division of Hematology/Oncology, University of California Irvine, Irvine, CA, USA
| | - Zhong-Ying Liu
- Division of Hematology/Oncology, University of California Irvine, Irvine, CA, USA
| | - Richard Van Etten
- Center for Complex Biological Systems, University of California Irvine, Irvine, CA, USA
- Division of Hematology/Oncology, University of California Irvine, Irvine, CA, USA
- Department of Biological Chemistry, University of California Irvine, Irvine, CA, USA
- Center for Cancer Systems Biology, University of California Irvine, Irvine, CA, USA
- Chao Family Comprehensive Cancer Center, University of California Irvine, Irvine, CA, USA
| | - Arthur D. Lander
- Center for Complex Biological Systems, University of California Irvine, Irvine, CA, USA
- Center for Cancer Systems Biology, University of California Irvine, Irvine, CA, USA
- Chao Family Comprehensive Cancer Center, University of California Irvine, Irvine, CA, USA
- Department of Developmental and Cell Biology, University of California Irvine, Irvine, CA, USA
- Department of Biomedical Engineering, University of California Irvine, Irvine, CA, USA
| | - Babak Shahbaba
- Center for Complex Biological Systems, University of California Irvine, Irvine, CA, USA
- Center for Cancer Systems Biology, University of California Irvine, Irvine, CA, USA
- Department of Statistics, University of California Irvine, Irvine, CA, USA
| | - John S. Lowengrub
- Center for Complex Biological Systems, University of California Irvine, Irvine, CA, USA
- Center for Cancer Systems Biology, University of California Irvine, Irvine, CA, USA
- Chao Family Comprehensive Cancer Center, University of California Irvine, Irvine, CA, USA
- Department of Biomedical Engineering, University of California Irvine, Irvine, CA, USA
- Department of Mathematics, University of California Irvine, Irvine, CA, USA
| | - Vladimir N. Minin
- Center for Complex Biological Systems, University of California Irvine, Irvine, CA, USA
- Center for Cancer Systems Biology, University of California Irvine, Irvine, CA, USA
- Department of Statistics, University of California Irvine, Irvine, CA, USA
| |
Collapse
|
11
|
Ruiz-Vega R, Chen CF, Razzak E, Vasudeva P, Krasieva TB, Shiu J, Caldwell MG, Yan H, Lowengrub J, Ganesan AK, Lander AD. Dynamics of nevus development implicate cell cooperation in the growth arrest of transformed melanocytes. eLife 2020; 9:e61026. [PMID: 33047672 PMCID: PMC7553774 DOI: 10.7554/elife.61026] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Accepted: 09/11/2020] [Indexed: 12/13/2022] Open
Abstract
Mutational activation of the BRAF proto-oncogene in melanocytes reliably produces benign nevi (pigmented 'moles'), yet the same change is the most common driver mutation in melanoma. The reason nevi stop growing, and do not progress to melanoma, is widely attributed to a cell-autonomous process of 'oncogene-induced senescence'. Using a mouse model of Braf-driven nevus formation, analyzing both proliferative dynamics and single-cell gene expression, we found no evidence that nevus cells are senescent, either compared with other skin cells, or other melanocytes. We also found that nevus size distributions could not be fit by any simple cell-autonomous model of growth arrest, yet were easily fit by models based on collective cell behavior, for example in which arresting cells release an arrest-promoting factor. We suggest that nevus growth arrest is more likely related to the cell interactions that mediate size control in normal tissues, than to any cell-autonomous, 'oncogene-induced' program of senescence.
Collapse
Affiliation(s)
- Rolando Ruiz-Vega
- Center for Complex Biological Systems, University of California, IrvineIrvineUnited States
- Department of Developmental and Cell Biology, University of California, IrvineIrvineUnited States
| | - Chi-Fen Chen
- Department of Dermatology, University of California, IrvineIrvineUnited States
| | - Emaad Razzak
- Center for Complex Biological Systems, University of California, IrvineIrvineUnited States
| | - Priya Vasudeva
- Department of Dermatology, University of California, IrvineIrvineUnited States
| | - Tatiana B Krasieva
- Beckman Laser Institute, University of California, IrvineIrvineUnited States
| | - Jessica Shiu
- Department of Dermatology, University of California, IrvineIrvineUnited States
| | - Michael G Caldwell
- Center for Complex Biological Systems, University of California, IrvineIrvineUnited States
| | - Huaming Yan
- Department of Mathematics, University of California, IrvineIrvineUnited States
| | - John Lowengrub
- Center for Complex Biological Systems, University of California, IrvineIrvineUnited States
- Department of Mathematics, University of California, IrvineIrvineUnited States
| | - Anand K Ganesan
- Center for Complex Biological Systems, University of California, IrvineIrvineUnited States
- Department of Dermatology, University of California, IrvineIrvineUnited States
| | - Arthur D Lander
- Center for Complex Biological Systems, University of California, IrvineIrvineUnited States
- Department of Developmental and Cell Biology, University of California, IrvineIrvineUnited States
- Department of Biological Chemistry, University of California, IrvineIrvineUnited States
| |
Collapse
|
12
|
Wang Y, Lo WC, Chou CS. Modelling stem cell ageing: a multi-compartment continuum approach. ROYAL SOCIETY OPEN SCIENCE 2020; 7:191848. [PMID: 32269805 PMCID: PMC7137970 DOI: 10.1098/rsos.191848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Accepted: 02/10/2020] [Indexed: 06/11/2023]
Abstract
Stem cells are important to generate all specialized tissues at an early life stage, and in some systems, they also have repair functions to replenish the adult tissues. Repeated cell divisions lead to the accumulation of molecular damage in stem cells, which are commonly recognized as drivers of ageing. In this paper, a novel model is proposed to integrate stem cell proliferation and differentiation with damage accumulation in the stem cell ageing process. A system of two structured PDEs is used to model the population densities of stem cells (including all multiple progenitors) and terminally differentiated (TD) cells. In this system, cell cycle progression and damage accumulation are modelled by continuous dynamics, and damage segregation between daughter cells is considered at each division. Analysis and numerical simulations are conducted to study the steady-state populations and stem cell damage distributions under different damage segregation strategies. Our simulations suggest that equal distribution of the damaging substance between stem cells in a symmetric renewal and less damage retention in stem cells in the asymmetric division are favourable strategies, which reduce the death rate of the stem cells and increase the TD cell populations. Moreover, asymmetric damage segregation in stem cells leads to less concentrated damage distribution in the stem cell population, which may be more robust to the stochastic changes in the damage. The feedback regulation from stem cells can reduce oscillations and population overshoot in the process, and improve the fitness of stem cells by increasing the percentage of cells with less damage in the stem cell population.
Collapse
Affiliation(s)
- Yanli Wang
- Department of Mathematics, The Ohio State University, Columbus, OH, USA
| | - Wing-Cheong Lo
- Department of Mathematics, City University of Hong Kong, Hong Kong, People’s Republic of China
| | - Ching-Shin Chou
- Department of Mathematics, The Ohio State University, Columbus, OH, USA
| |
Collapse
|
13
|
Modi S, Singh A. Controlling organism size by regulating constituent cell numbers. PROCEEDINGS OF THE ... IEEE CONFERENCE ON DECISION & CONTROL. IEEE CONFERENCE ON DECISION & CONTROL 2019; 2018:2685-2690. [PMID: 30886453 DOI: 10.1109/cdc.2018.8619546] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
How living cells employ counting mechanisms to regulate their numbers or density is a long-standing problem in developmental biology that ties directly with organism or tissue size. Diverse cells types have been shown to regulate their numbers via secretion of factors in the extracellular space. These factors act as a proxy for the number of cells and function to reduce cellular proliferation rates creating a negative feedback. It is desirable that the production rate of such factors be kept as low as possible to minimize energy costs and detection by predators. Here we formulate a stochastic model of cell proliferation with feedback control via a secreted extracellular factor. Our results show that while low levels of feedback minimizes random fluctuations in cell numbers around a given set point, high levels of feedback amplify Poisson fluctuations in secreted-factor copy numbers. This trade-off results in an optimal feedback strength, and sets a fundamental limit to noise suppression in cell numbers with short-lived factors providing more efficient noise buffering. We further expand the model to consider external disturbances in key physiological parameters, such as, proliferation and factor synthesis rates. Intriguingly, while negative feedback effectively mitigates disturbances in the proliferation rate, it amplifies disturbances in the synthesis rate. In summary, these results provide unique insights into the functioning of feedback-based counting mechanisms, and apply to organisms ranging from unicellular prokaryotes and eukaryotes to human cells.
Collapse
Affiliation(s)
- Saurabh Modi
- Department of Biomedical Engineering, University of Delaware, Newark, DE USA 19716.
| | - Abhyudai Singh
- Department of Electrical and Computer Engineering, Biomedical Engineering, Mathematical Sciences, Center for Bioinformatics and Computational Biology, University of Delaware, Newark, DE USA 19716.
| |
Collapse
|
14
|
MacLean AL, Hong T, Nie Q. Exploring intermediate cell states through the lens of single cells. CURRENT OPINION IN SYSTEMS BIOLOGY 2018; 9:32-41. [PMID: 30450444 PMCID: PMC6238957 DOI: 10.1016/j.coisb.2018.02.009] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
As our catalog of cell states expands, appropriate characterization of these states and the transitions between them is crucial. Here we discuss the roles of intermediate cell states (ICSs) in this growing collection. We begin with definitions and discuss evidence for the existence of ICSs and their relevance in various tissues. We then provide a list of possible functions for ICSs with examples. Finally, we describe means by which ICSs and their functional roles can be identified from single-cell data or predicted from models.
Collapse
Affiliation(s)
- Adam L. MacLean
- Department of Mathematics and Center for Complex Biological Systems, University of California, Irvine, CA 92697, United States
| | - Tian Hong
- Department of Biochemistry & Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37966, United States
| | - Qing Nie
- Department of Mathematics and Center for Complex Biological Systems, University of California, Irvine, CA 92697, United States,Department of Developmental and Cell Biology, University of California, Irvine, CA 92697, United States
| |
Collapse
|
15
|
Renardy M, Jilkine A, Shahriyari L, Chou CS. Control of cell fraction and population recovery during tissue regeneration in stem cell lineages. J Theor Biol 2018; 445:33-50. [PMID: 29470992 DOI: 10.1016/j.jtbi.2018.02.017] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2017] [Revised: 01/24/2018] [Accepted: 02/19/2018] [Indexed: 12/20/2022]
Abstract
Multicellular tissues are continually turning over, and homeostasis is maintained through regulated proliferation and differentiation of stem cells and progenitors. Following tissue injury, a dramatic increase in cell proliferation is commonly observed, resulting in rapid restoration of tissue size. This regulation is thought to occur via multiple feedback loops acting on cell self-renewal or differentiation. Models of ordinary differential equations have been widely used to study the cell lineage system. Prior modeling studies have suggested that loss of homeostasis and initiation of tumorigenesis can be contributed to the loss of control of these processes, and the rate of symmetric versus asymmetric division of the stem cells may also be altered. While most of the previous works focused on analysis of stability, existence and uniqueness of steady states of multistage cell lineage models, in this work we attempt to understand the cell lineage model from a different perspective. We compare three variants of hierarchical stem cell lineage tissue models with different combinations of negative feedbacks and use sensitivity analysis to examine the possible strategies for the cells to achieve certain performance objectives. Our results suggest that multiple negative feedback loops must be present in the stem cell lineage to keep the fractions of stem cells to differentiated cells in the total population as robust as possible to variations in cell division parameters, and to minimize the time for tissue recovery in a non-oscillatory manner.
Collapse
Affiliation(s)
- Marissa Renardy
- Department of Mathematics, Ohio State University, Columbus, OH, USA
| | - Alexandra Jilkine
- Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, IN, USA
| | - Leili Shahriyari
- Mathematical Biosciences Institute, Ohio State University, Columbus, OH, USA
| | - Ching-Shan Chou
- Department of Mathematics, Ohio State University, Columbus, OH, USA; Mathematical Biosciences Institute, Ohio State University, Columbus, OH, USA.
| |
Collapse
|
16
|
Montgomery SH, Mundy NI, Barton RA. Brain evolution and development: adaptation, allometry and constraint. Proc Biol Sci 2017; 283:rspb.2016.0433. [PMID: 27629025 DOI: 10.1098/rspb.2016.0433] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2016] [Accepted: 08/19/2016] [Indexed: 01/08/2023] Open
Abstract
Phenotypic traits are products of two processes: evolution and development. But how do these processes combine to produce integrated phenotypes? Comparative studies identify consistent patterns of covariation, or allometries, between brain and body size, and between brain components, indicating the presence of significant constraints limiting independent evolution of separate parts. These constraints are poorly understood, but in principle could be either developmental or functional. The developmental constraints hypothesis suggests that individual components (brain and body size, or individual brain components) tend to evolve together because natural selection operates on relatively simple developmental mechanisms that affect the growth of all parts in a concerted manner. The functional constraints hypothesis suggests that correlated change reflects the action of selection on distributed functional systems connecting the different sub-components, predicting more complex patterns of mosaic change at the level of the functional systems and more complex genetic and developmental mechanisms. These hypotheses are not mutually exclusive but make different predictions. We review recent genetic and neurodevelopmental evidence, concluding that functional rather than developmental constraints are the main cause of the observed patterns.
Collapse
Affiliation(s)
- Stephen H Montgomery
- Department of Genetics, Evolution and Environment, University College London, Gower Street, London WC1E 6BT, UK
| | - Nicholas I Mundy
- Department of Zoology, University of Cambridge, St Andrews Street, Cambridge CB2 3EJ, UK
| | - Robert A Barton
- Evolutionary Anthropology Research Group, Durham University, Dawson Building, South Road, Durham DH1 3LE, UK
| |
Collapse
|
17
|
Kicheva A, Rivron NC. Creating to understand - developmental biology meets engineering in Paris. Development 2017; 144:733-736. [PMID: 28246208 DOI: 10.1242/dev.144915] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
In November 2016, developmental biologists, synthetic biologists and engineers gathered in Paris for a meeting called 'Engineering the embryo'. The participants shared an interest in exploring how synthetic systems can reveal new principles of embryonic development, and how the in vitro manipulation and modeling of development using stem cells can be used to integrate ideas and expertise from physics, developmental biology and tissue engineering. As we review here, the conference pinpointed some of the challenges arising at the intersection of these fields, along with great enthusiasm for finding new approaches and collaborations.
Collapse
Affiliation(s)
- Anna Kicheva
- Institute of Science and Technology IST Austria, Klosterneuburg 3400, Austria
| | - Nicolas C Rivron
- MERLN Institute for Technology-Inspired Regenerative Medicine, Maastricht University, Maastricht 6200 MD, The Netherlands .,Hubrecht Institute for Developmental Biology and Stem Cell Research, Utrecht 3584 CT, The Netherlands
| |
Collapse
|
18
|
Karin O, Alon U. Biphasic response as a mechanism against mutant takeover in tissue homeostasis circuits. Mol Syst Biol 2017; 13:933. [PMID: 28652282 PMCID: PMC5488663 DOI: 10.15252/msb.20177599] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Tissues use feedback circuits in which cells send signals to each other to control their growth and survival. We show that such feedback circuits are inherently unstable to mutants that misread the signal level: Mutants have a growth advantage to take over the tissue, and cannot be eliminated by known cell-intrinsic mechanisms. To resolve this, we propose that tissues have biphasic responses in and the signal is toxic at both high and low levels, such as glucotoxicity of beta cells, excitotoxicity in neurons, and toxicity of growth factors to T cells. This gives most of these mutants a frequency-dependent selective disadvantage, which leads to their elimination. However, the biphasic mechanisms create a new unstable fixed point in the feedback circuit beyond which runaway processes can occur, leading to risk of diseases such as diabetes and neurodegenerative disease. Hence, glucotoxicity, which is a dangerous cause of diabetes, may have a protective anti-mutant effect. Biphasic responses in tissues may provide an evolutionary stable strategy that avoids invasion by commonly occurring mutants, but at the same time cause vulnerability to disease.
Collapse
Affiliation(s)
- Omer Karin
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Uri Alon
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| |
Collapse
|
19
|
MacLean AL, Lo Celso C, Stumpf MP. Concise Review: Stem Cell Population Biology: Insights from Hematopoiesis. Stem Cells 2016; 35:80-88. [DOI: 10.1002/stem.2508] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2016] [Revised: 07/19/2016] [Accepted: 08/21/2016] [Indexed: 01/01/2023]
Affiliation(s)
- Adam L. MacLean
- Department of Life Sciences; Imperial College London; South Kensington Campus London United Kingdom
| | - Cristina Lo Celso
- Department of Life Sciences; Imperial College London; South Kensington Campus London United Kingdom
| | - Michael P.H. Stumpf
- Department of Life Sciences; Imperial College London; South Kensington Campus London United Kingdom
| |
Collapse
|
20
|
Briat C, Zechner C, Khammash M. Design of a Synthetic Integral Feedback Circuit: Dynamic Analysis and DNA Implementation. ACS Synth Biol 2016; 5:1108-1116. [PMID: 27345033 DOI: 10.1021/acssynbio.6b00014] [Citation(s) in RCA: 73] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
The design and implementation of regulation motifs ensuring robust perfect adaptation are challenging problems in synthetic biology. Indeed, the design of high-yield robust metabolic pathways producing, for instance, drug precursors and biofuels, could be easily imagined to rely on such a control strategy in order to optimize production levels and reduce production costs, despite the presence of environmental disturbance and model uncertainty. We propose here a motif that ensures tracking and robust perfect adaptation for the controlled reaction network through integral feedback. Its metabolic load on the host is fully tunable and can be made arbitrarily close to the constitutive limit, the universal minimal metabolic load of all possible controllers. A DNA implementation of the controller network is finally provided. Computer simulations using realistic parameters demonstrate the good agreement between the DNA implementation and the ideal controller dynamics.
Collapse
Affiliation(s)
- Corentin Briat
- Department of Biosystems
Science and Engineering, ETH Zürich, Basel, Switzerland
| | - Christoph Zechner
- Department of Biosystems
Science and Engineering, ETH Zürich, Basel, Switzerland
| | - Mustafa Khammash
- Department of Biosystems
Science and Engineering, ETH Zürich, Basel, Switzerland
| |
Collapse
|
21
|
Pir P, Le Novère N. Mathematical Models of Pluripotent Stem Cells: At the Dawn of Predictive Regenerative Medicine. Methods Mol Biol 2016; 1386:331-50. [PMID: 26677190 DOI: 10.1007/978-1-4939-3283-2_15] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Regenerative medicine, ranging from stem cell therapy to organ regeneration, is promising to revolutionize treatments of diseases and aging. These approaches require a perfect understanding of cell reprogramming and differentiation. Predictive modeling of cellular systems has the potential to provide insights about the dynamics of cellular processes, and guide their control. Moreover in many cases, it provides alternative to experimental tests, difficult to perform for practical or ethical reasons. The variety and accuracy of biological processes represented in mathematical models grew in-line with the discovery of underlying molecular mechanisms. High-throughput data generation led to the development of models based on data analysis, as an alternative to more established modeling based on prior mechanistic knowledge. In this chapter, we give an overview of existing mathematical models of pluripotency and cell fate, to illustrate the variety of methods and questions. We conclude that current approaches are yet to overcome a number of limitations: Most of the computational models have so far focused solely on understanding the regulation of pluripotency, and the differentiation of selected cell lineages. In addition, models generally interrogate only a few biological processes. However, a better understanding of the reprogramming process leading to ESCs and iPSCs is required to improve stem-cell therapies. One also needs to understand the links between signaling, metabolism, regulation of gene expression, and the epigenetics machinery.
Collapse
Affiliation(s)
- Pınar Pir
- Babraham Institute, Babraham Research Campus, Cambridge, CB22 3AT, UK.
| | - Nicolas Le Novère
- Babraham Institute, Babraham Research Campus, Cambridge, CB22 3AT, UK.
| |
Collapse
|
22
|
Implementation Considerations, Not Topological Differences, Are the Main Determinants of Noise Suppression Properties in Feedback and Incoherent Feedforward Circuits. PLoS Comput Biol 2016; 12:e1004958. [PMID: 27257684 PMCID: PMC4892630 DOI: 10.1371/journal.pcbi.1004958] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2015] [Accepted: 05/04/2016] [Indexed: 12/03/2022] Open
Abstract
Biological systems use a variety of mechanisms to deal with the uncertain nature of their external and internal environments. Two of the most common motifs employed for this purpose are the incoherent feedforward (IFF) and feedback (FB) topologies. Many theoretical and experimental studies suggest that these circuits play very different roles in providing robustness to uncertainty in the cellular environment. Here, we use a control theoretic approach to analyze two common FB and IFF architectures that make use of an intermediary species to achieve regulation. We show the equivalence of both circuits topologies in suppressing static cell-to-cell variations. While both circuits can suppress variations due to input noise, they are ineffective in suppressing inherent chemical reaction stochasticity. Indeed, these circuits realize comparable improvements limited to a modest 25% variance reduction in best case scenarios. Such limitations are attributed to the use of intermediary species in regulation, and as such, they persist even for circuit architectures that combine both IFF and FB features. Intriguingly, while the FB circuits are better suited in dealing with dynamic input variability, the most significant difference between the two topologies lies not in the structural features of the circuits, but in their practical implementation considerations. Essential to the survival of biological organisms is their ability to decipher and respond accordingly to stress scenarios presented by a changing and often unpredictable environment. Cellular noise, present due to the inherently random nature of both the external and internal environments, can obfuscate and corrupt the information found in the environmental cues, thus necessitating the development of mechanisms capable of repressing the noise and recovering the true information. Understanding these noise suppressing mechanisms is an important step toward the general understanding of adaptation and survival in biology. Here we present ideas that have broad implications for the understanding of the role and prevalence of two such mechanisms: the feedback and incoherent feedforward motifs. Using computational and analytical tools commonly employed in engineering applications, we characterize the performance and limitations of these two motifs, as well as establish their equivalence in dealing this several types of noise. We show that the effectiveness and preference of one motif over the other lies mostly in the practical implementation details and not in their structural properties.
Collapse
|
23
|
Abstract
In his splendid article "Can a biologist fix a radio?--or, what I learned while studying apoptosis," Y. Lazebnik argues that when one uses the right tools, similarity between a biological system, like a signal transduction pathway, and an engineered system, like a radio, may not seem so superficial. Here I advance this idea by focusing on the notion of robustness as a unifying lens through which to view complexity in biological and engineered systems. I show that electronic amplifiers and gene expression circuits share remarkable similarities in their dynamics and robustness properties. I explore robustness features and limitations in biology and engineering and highlight the role of negative feedback in shaping both.
Collapse
Affiliation(s)
- Mustafa Khammash
- Department of Biosystems Science and Engineering, ETH Zürich, Switzerland.
| |
Collapse
|
24
|
Mangel M, Bonsall MB, Aboobaker A. Feedback control in planarian stem cell systems. BMC SYSTEMS BIOLOGY 2016; 10:17. [PMID: 26873593 PMCID: PMC4752765 DOI: 10.1186/s12918-016-0261-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/17/2015] [Accepted: 01/29/2016] [Indexed: 01/10/2023]
Abstract
Background In planarian flatworms, the mechanisms underlying the activity of collectively pluripotent adult stem cells (neoblasts) and their descendants can now be studied from the level of the individual gene to the entire animal. Flatworms maintain startling developmental plasticity and regenerative capacity in response to variable nutrient conditions or injury. We develop a model for cell dynamics in such animals, assuming that fully differentiated cells exert feedback control on neoblast activity. Results Our model predicts a number of whole organism level and general cell biological and behaviours, some of which have been empirically observed or inferred in planarians and others that have not. As previously observed empirically we find: 1) a curvilinear relationship between external food and planarian steady state size; 2) the fraction of neoblasts in the steady state is constant regardless of planarian size; 3) a burst of controlled apoptosis during regeneration after amputation as the number of differentiated cells are adjusted towards their homeostatic/steady state level. In addition our model describes the following properties that can inform and be tested by future experiments: 4) the strength of feedback control from differentiated cells to neoblasts (i.e. the activity of the signalling system) and from neoblasts on themselves in relation to absolute number depends upon the level of food in the environment; 5) planarians adjust size when food level reduces initially through increased apoptosis and then through a reduction in neoblast self-renewal activity; 6) following wounding or excision of differentiated cells, different time scales characterize both recovery of size and the two feedback functions; 7) the temporal pattern of feedback controls differs noticeably during recovery from a removal or neoblasts or a removal of differentiated cells; 8) the signaling strength for apoptosis of differentiated cells depends upon both the absolute and relative deviations of the number of differentiated cells from their homeostatic level; and 9) planaria prioritize resource use for cell divisions. Conclusions We offer the first analytical framework for organizing experiments on planarian flatworm stem cell dynamics in a form that allows models to be compared with quantitative cell data based on underlying molecular mechanisms and thus facilitate the interplay between empirical studies and modeling. This framework is the foundation for studying cell migration during wound repair, the determination of homeostatic levels of differentiated cells by natural selection, and stochastic effects. Electronic supplementary material The online version of this article (doi:10.1186/s12918-016-0261-8) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
- Marc Mangel
- Department of Applied Mathematics and Statistics, University of California, Santa Cruz, 95064, CA, USA. .,Department of Biology, University of Bergen, Bergen, 9020, Norway.
| | | | - Aziz Aboobaker
- Department of Zoology, University of Oxford, Oxford, UK.
| |
Collapse
|
25
|
MacLean AL, Kirk PDW, Stumpf MPH. Cellular population dynamics control the robustness of the stem cell niche. Biol Open 2015; 4:1420-6. [PMID: 26453624 PMCID: PMC4728354 DOI: 10.1242/bio.013714] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
Within populations of cells, fate decisions are controlled by an indeterminate combination of cell-intrinsic and cell-extrinsic factors. In the case of stem cells, the stem cell niche is believed to maintain ‘stemness’ through communication and interactions between the stem cells and one or more other cell-types that contribute to the niche conditions. To investigate the robustness of cell fate decisions in the stem cell hierarchy and the role that the niche plays, we introduce simple mathematical models of stem and progenitor cells, their progeny and their interplay in the niche. These models capture the fundamental processes of proliferation and differentiation and allow us to consider alternative possibilities regarding how niche-mediated signalling feedback regulates the niche dynamics. Generalised stability analysis of these stem cell niche systems enables us to describe the stability properties of each model. We find that although the number of feasible states depends on the model, their probabilities of stability in general do not: stem cell–niche models are stable across a wide range of parameters. We demonstrate that niche-mediated feedback increases the number of stable steady states, and show how distinct cell states have distinct branching characteristics. The ecological feedback and interactions mediated by the stem cell niche thus lend (surprisingly) high levels of robustness to the stem and progenitor cell population dynamics. Furthermore, cell–cell interactions are sufficient for populations of stem cells and their progeny to achieve stability and maintain homeostasis. We show that the robustness of the niche – and hence of the stem cell pool in the niche – depends only weakly, if at all, on the complexity of the niche make-up: simple as well as complicated niche systems are capable of supporting robust and stable stem cell dynamics. Summary: Stem cell niche dynamics are very robust to external and physiological perturbations because proliferation and differentiation are naturally balanced and controlled by the reliance on a shared niche environment.
Collapse
Affiliation(s)
- Adam L MacLean
- Theoretical Systems Biology, Department of Life Sciences, Imperial College London, London SW7 2AZ, UK
| | - Paul D W Kirk
- MRC Biostatistics Unit, Cambridge Institute of Public Health, Cambridge CB2 0SR, UK
| | - Michael P H Stumpf
- Theoretical Systems Biology, Department of Life Sciences, Imperial College London, London SW7 2AZ, UK
| |
Collapse
|
26
|
Abstract
How organs grow to be the right size for the animal is one of the central mysteries of biology. In a paper in BMC Biology, Khammash et al. propose a mechanism for escaping from the deficiencies of feedback control of growth as a mechanism. See research article: http://dx.doi.org/10.1186/s12915-015-0122-8
Collapse
|