Cell lineage branching as a strategy for proliferative control

Buzi, Gentian; Lander, Arthur D.; Khammash, Mustafa

doi:10.1186/s12915-015-0122-8

Cited by 37 publications

(57 citation statements)

References 53 publications

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“…The molecule y increases the differentiation rate of the stem cells and thus limits their expansion rate. This type of feedback has been demonstrated for many tissues, such as blood, skin, skeletal muscle, olfactory epithelium, bone, hair, and more (Lander et al, 2009;Buzi et al, 2015). In many of these tissues, the secreted molecule belongs to the TGF-b family (Lander et al, 2009).…”

Section: Evolutionary Stable Strategies In Tissues With Stem Cellsmentioning

confidence: 97%

Biphasic response as a mechanism against mutant takeover in tissue homeostasis circuits

Karin

2017

Molecular Systems Biology

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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.

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Section: Evolutionary Stable Strategies In Tissues With Stem Cellsmentioning

confidence: 97%

Biphasic response as a mechanism against mutant takeover in tissue homeostasis circuits

Karin

2017

Molecular Systems Biology

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“…In other tissues, members of the TGF-b gene family, which have known roles in cell differentiation [98] and brain development [99], function as the signal molecule. TGF-b signals are only effective across small spatial scales suggesting local feedback operates at a tissue-specific rather than whole organ level [96]. It is an intriguing hypothesis that modification of such signals would allow local control and variation in cell proliferation, facilitating mosaic evolution.…”

Section: (E) Developmental Models Of Mosaic Evolutionmentioning

confidence: 99%

“…For example, mechanisms of local control of proliferation may be necessary to produce mosaic patterns of evolution. Recently, Buzi et al [96] demonstrated the potential for descendent cells to regulate the duration of proliferative division in their own progenitor pools through 'integral feedback' mediated by secreted molecules. Under this model, the strength of an inhibitive signal on cell division increases as descendent cells accumulate until it causes a cessation of proliferation.…”

Section: (E) Developmental Models Of Mosaic Evolutionmentioning

confidence: 99%

Brain evolution and development: adaptation, allometry and constraint

2016

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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. How brains evolve: the importance of scaling relationshipsThe components of any adaptive complex by definition undergo coordinated evolution. Brains, bodies and individual brain components therefore exhibit distinctive patterns of correlated evolution. But what do these patterns tell us about the roles of adaptation and constraint in shaping phenotypes? In particular, how and to what extent do constraints imposed by shared developmental programmes dictate allometric relationships between components, limiting their response to selection? These questions have shaped two key debates central to how we view brain evolution: the functional relevance of brain size and the adaptive potential of brain structure [1][2][3]. These debates hinge on whether observed patterns of scaling relationships, between brain and body size or different brain components, are the product of selection to maintain functional correspondence or constraints imposed by shared developmental programmes. Crucially, however, a sound understanding of the significance of scaling relationships in brain evolution has been limited by a lack of data on the genetic and developmental mechanisms that regulate brain size and structure. Here we discuss how recent discoveries about the genetic control of neural development shed new light on the issue.(a) Brain: body coevolution and the importance of size

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“…1B. Closely related control mechanisms have also been considered in [34 ] in the context of fold-change detection and in [35 ] in the context of stem cell differentiation even though, in the latter case, the model is considered at a cellular level rather than at a molecular level.…”

Section: Resultsmentioning

confidence: 98%

Design of a Synthetic Integral Feedback Circuit: Dynamic Analysis and DNA Implementation

2016

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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.

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Cell lineage branching as a strategy for proliferative control

Cited by 37 publications

References 53 publications

Biphasic response as a mechanism against mutant takeover in tissue homeostasis circuits

Biphasic response as a mechanism against mutant takeover in tissue homeostasis circuits

Brain evolution and development: adaptation, allometry and constraint

Design of a Synthetic Integral Feedback Circuit: Dynamic Analysis and DNA Implementation

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