How to Build a Biological Oscillator

2019 ◽  
pp. 97-113
Author(s):  
Uri Alon
2014 ◽  
Vol 10 (5) ◽  
pp. e1003622 ◽  
Author(s):  
Umeshkanta S. Thounaojam ◽  
Jianxia Cui ◽  
Sharon E. Norman ◽  
Robert J. Butera ◽  
Carmen C. Canavier

2020 ◽  
Author(s):  
Miha Moškon ◽  
Žiga Pušnik ◽  
Lidija Magdevska ◽  
Nikolaj Zimic ◽  
Miha Mraz

AbstractBasic synthetic information processing structures, such as logic gates, oscillators and flip-flops, have already been implemented in living organisms. Current implementations of these structures are, however, hardly scalable and are yet to be extended to more complex processing structures that would constitute a biological computer.Herein, we make a step forward towards the construction of a biological computer. We describe a model-based computational design of a biological processor, composed of an instruction memory containing a biological program, a program counter that is used to address this memory and a biological oscillator that triggers the execution of the next instruction in the memory. The described processor uses transcription and translation resources of the host cell to perform its operations and is able to sequentially execute a set of instructions written within the so-called instruction memory implemented with non-volatile DNA sequences. The addressing of the instruction memory is achieved with a biological implementation of the Johnson counter, which increases its state after an instruction is executed. We additionally describe the implementation of a biological compiler that compiles a sequence of human-readable instructions into ordinary differential equations-based models. These models can be used to simulate the dynamics of the proposed processor.The proposed implementation presents the first programmable biological processor that exploits cellular resources to execute the specified instructions. We demonstrate the application of the proposed processor on a set of simple yet scalable biological programs. Biological descriptions of these programs can be written manually or can be generated automatically with the employment of the provided compiler.


1984 ◽  
Vol 246 (6) ◽  
pp. R847-R853 ◽  
Author(s):  
W. O. Friesen ◽  
G. D. Block

Biological oscillators are amenable to qualitative analysis even before they have been described exhaustively in quantitative terms. Qualitative analysis can identify the elements essential for generating the oscillations and can enhance our understanding of underlying oscillator mechanisms. Two essential elements of a biological oscillator are 1) an inhibitory feedback loop, which includes one or more oscillating variables, and 2) a source of delay in this feedback loop, which allows an oscillating variable to overshoot a steady-state value before the feedback inhibition is fully effective. The analysis of the patterns of interactions and delays observed in biological oscillators is simplified by the translation of variables, interactions, and delays into schematic representations. To illustrate how such translations can be implemented, three biological oscillators are described schematically: 1) the glycolytic oscillator, 2) the bursting of the molluscan neuron, R15, and 3) the oscillations underlying smooth muscle contractions.


1983 ◽  
Vol 103 (1) ◽  
pp. 113-132 ◽  
Author(s):  
T. Pham Dinh ◽  
J. Demongeot ◽  
P. Baconnier ◽  
G. Benchetrit

2017 ◽  
Author(s):  
María I. Calvo-Sánchez ◽  
Elisa Carrasco ◽  
Sandra Fernández-Martos ◽  
Gema Moreno ◽  
Carmelo Bernabeu ◽  
...  

ABSTRACTThe hair follicle is a biological oscillator that alternates growth, regression and rest phases driven by the sequential activation of the proliferation/differentiation programs of resident stem cell populations. The activation of hair follicle stem cell niches and subsequent entry into the growing phase is mainly regulated by Wnt/β-catenin signalling, while regression and resting phases are mainly regulated by Tgf-β/Bmp/Smad activity. A major question still unresolved is the nature of the molecular switch that dictates the coordinated transition between both signalling pathways. Here we have focused on the role of Endoglin (Eng), a key coreceptor for members of the Tgf-β/Bmp family of growth factors.Using an Eng haploinsufficient mouse model we report that Eng is required to maintain a correct follicle cycling pattern and for an adequate stimulation of hair follicle stem cell niches. We further report that β-catenin binds to the Eng promoter depending on Bmp signalling. Moreover, we show that β-catenin interacts with Smad4 in a Bmp/Eng dependent context and both proteins act synergistically to activate Eng promoter transcription. These observations point to the existence of a growth/rest switching mechanism in the hair follicle that is based on an Eng-dependent feedback crosstalk between Wnt/β-catenin and Bmp/Smad signals.


Sign in / Sign up

Export Citation Format

Share Document