scholarly journals Biological Action at a Distance: Correlated pattern formation in adjacent tessellation domains without communication

2021 ◽  
Author(s):  
John M Brooke ◽  
Sebastian S James ◽  
Alejandro Jiminez-Rodriguez ◽  
Stuart P Wilson
Keyword(s):  
Pattern Formation ◽  
Voronoi Tessellation ◽  
Reaction Diffusion ◽  
Biological Action ◽  
Natural Systems ◽  
General Terms ◽  
Domain Boundaries ◽  
Action At A Distance ◽  
Biological Patterns ◽  
Regular Patterns

Tessellations emerge in many natural systems, and the constituent domains often contain regular patterns, raising the intriguing possibility that pattern formation within adjacent domains might be correlated by the geometry, without the direct exchange of information between parts comprising either domain. We confirm this paradoxical effect, by simulating pattern formation via reaction-diffusion in domains whose boundary shapes tessellate, and showing that correlations between adjacent patterns are strong compared to controls that self-organise in domains with equivalent sizes but unrelated shapes. The effect holds in systems with linear and non-linear diffusive terms, and for boundary shapes derived from regular and irregular tessellations. Based on the prediction that correlations between adjacent patterns should be bimodally distributed, we develop methods for testing whether a given set of domain boundaries constrained pattern formation within those domains. We then confirm such a prediction by analysing the development of `subbarrel' patterns, which are thought to emerge via reaction-diffusion, and whose enclosing borders form a Voronoi tessellation on the surface of the rodent somatosensory cortex. In more general terms, this result demonstrates how causal links can be established between the dynamical processes through which biological patterns emerge and the constraints that shape them.

scholarly journals Characteristics of Pattern Formation and Evolution in Approximations of Physarum Transport Networks

2010 ◽  
Vol 16 (2) ◽  
pp. 127-153 ◽  
Author(s):  
Jeff Jones
Keyword(s):  
Pattern Formation ◽  
Network Connectivity ◽  
Reaction Diffusion ◽  
Model Parameters ◽  
Formation Processes ◽  
Transport Networks ◽  
Natural Systems ◽  
Periodic Arrays ◽  
Biological Pattern Formation ◽  
Formation And Evolution

Most studies of pattern formation place particular emphasis on its role in the development of complex multicellular body plans. In simpler organisms, however, pattern formation is intrinsic to growth and behavior. Inspired by one such organism, the true slime mold Physarum polycephalum, we present examples of complex emergent pattern formation and evolution formed by a population of simple particle-like agents. Using simple local behaviors based on chemotaxis, the mobile agent population spontaneously forms complex and dynamic transport networks. By adjusting simple model parameters, maps of characteristic patterning are obtained. Certain areas of the parameter mapping yield particularly complex long term behaviors, including the circular contraction of network lacunae and bifurcation of network paths to maintain network connectivity. We demonstrate the formation of irregular spots and labyrinthine and reticulated patterns by chemoattraction. Other Turing-like patterning schemes were obtained by using chemorepulsion behaviors, including the self-organization of regular periodic arrays of spots, and striped patterns. We show that complex pattern types can be produced without resorting to the hierarchical coupling of reaction-diffusion mechanisms. We also present network behaviors arising from simple pre-patterning cues, giving simple examples of how the emergent pattern formation processes evolve into networks with functional and quasi-physical properties including tensionlike effects, network minimization behavior, and repair to network damage. The results are interpreted in relation to classical theories of biological pattern formation in natural systems, and we suggest mechanisms by which emergent pattern formation processes may be used as a method for spatially represented unconventional computation.

scholarly journals HetL, HetR and PatS form a reaction-diffusion system to control pattern formation in the cyanobacterium nostoc PCC 7120

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Xiaomei Xu ◽  
Véronique Risoul ◽  
Deborah Byrne ◽  
Stéphanie Champ ◽  
Badreddine Douzi ◽  
...  
Keyword(s):  
Cell Differentiation ◽  
Pattern Formation ◽  
Long Range ◽  
Nitrogen Starvation ◽  
Reaction Diffusion ◽  
Protective Mechanism ◽  
Control Pattern ◽  
Differentiation Pattern ◽  
Biological Patterns ◽  
Pcc 7120

Local activation and long-range inhibition are mechanisms conserved in self-organizing systems leading to biological patterns. A number of them involve the production by the developing cell of an inhibitory morphogen, but how this cell becomes immune to self-inhibition is rather unknown. Under combined nitrogen starvation, the multicellular cyanobacterium Nostoc PCC 7120 develops nitrogen-fixing heterocysts with a pattern of one heterocyst every 10–12 vegetative cells. Cell differentiation is regulated by HetR which activates the synthesis of its own inhibitory morphogens, diffusion of which establishes the differentiation pattern. Here, we show that HetR interacts with HetL at the same interface as PatS, and that this interaction is necessary to suppress inhibition and to differentiate heterocysts. hetL expression is induced under nitrogen-starvation and is activated by HetR, suggesting that HetL provides immunity to the heterocyst. This protective mechanism might be conserved in other differentiating cyanobacteria as HetL homologues are spread across the phylum.

scholarly journals Developmental stochasticity and variation in floral phyllotaxis

2021 ◽  
Author(s):  
Miho Stephanie Kitazawa
Keyword(s):  
Pattern Formation ◽  
Gene Networks ◽  
Recent Progress ◽  
Phyllotactic Pattern ◽  
Floral Diversity ◽  
Core Eudicots ◽  
Common Process ◽  
The Mean ◽  
Floral Phyllotaxis ◽  
Regular Patterns

AbstractFloral phyllotaxis is a relatively robust phenotype; trimerous and pentamerous arrangements are widely observed in monocots and core eudicots. Conversely, it also shows variability in some angiosperm clades such as ‘ANA’ grade (Amborellales, Nymphaeales, and Austrobaileyales), magnoliids, and Ranunculales. Regardless of the phylogenetic relationship, however, phyllotactic pattern formation appears to be a common process. What are the causes of the variability in floral phyllotaxis and how has the variation of floral phyllotaxis contributed to floral diversity? In this review, I summarize recent progress in studies on two related fields to develop answers to these questions. First, it is known that molecular and cellular stochasticity are inevitably found in biological systems, including plant development. Organisms deal with molecular stochasticity in several ways, such as dampening noise through gene networks or maintaining function through cellular redundancy. Recent studies on molecular and cellular stochasticity suggest that stochasticity is not always detrimental to plants and that it is also essential in development. Second, studies on vegetative and inflorescence phyllotaxis have shown that plants often exhibit variability and flexibility in phenotypes. Three types of phyllotaxis variations are observed, namely, fluctuation around the mean, transition between regular patterns, and a transient irregular organ arrangement called permutation. Computer models have demonstrated that stochasticity in the phyllotactic pattern formation plays a role in pattern transitions and irregularities. Variations are also found in the number and positioning of floral organs, although it is not known whether such variations provide any functional advantages. Two ways of diversification may be involved in angiosperm floral evolution: precise regulation of organ position and identity that leads to further specialization of organs and organ redundancy that leads to flexibility in floral phyllotaxis.

Role of Nuclei in Liesegang Pattern Formation: Insights from Experiment and Reaction-Diffusion Simulation

2018 ◽  
Vol 122 (6) ◽  
pp. 3669-3676 ◽  
Author(s):  
Masaki Itatani ◽  
Qing Fang ◽  
Kei Unoura ◽  
Hideki Nabika
Keyword(s):  
Pattern Formation ◽  
Reaction Diffusion ◽  
Diffusion Simulation

‘Generic’ physical mechanisms of morphogenesis and pattern formation

Development ◽  
1990 ◽  
Vol 110 (1) ◽  
pp. 1-18 ◽  
Author(s):  
S.A. Newman ◽  
W.D. Comper
Keyword(s):  
Pattern Formation ◽  
Reaction Diffusion ◽  
Physical Mechanisms ◽  
Extracellular Matrix Components ◽  
Genetic Mechanisms ◽  
Chemical Waves ◽  
Phylogenetic Lineages ◽  
Living Tissues ◽  
Highly Evolved

The role of ‘generic’ physical mechanisms in morphogenesis and pattern formation of tissues is considered. Generic mechanisms are defined as those physical processes that are broadly applicable to living and non-living systems, such as adhesion, surface tension and gravitational effects, viscosity, phase separation, convection and reaction-diffusion coupling. They are contrasted with ‘genetic’ mechanisms, a term reserved for highly evolved, machine-like, biomolecular processes. Generic mechanisms acting upon living tissues are capable of giving rise to morphogenetic rearrangements of cytoplasmic, tissue and extracellular matrix components, sometimes leading to ‘microfingers’, and to chemical waves or stripes. We suggest that many morphogenetic and patterning effects are the inevitable outcome of recognized physical properties of tissues, and that generic physical mechanisms that act on these properties are complementary to, and interdependent with genetic mechanisms. We also suggest that major morphological reorganizations in phylogenetic lineages may arise by the action of generic physical mechanisms on developing embryos. Subsequent evolution of genetic mechanisms could stabilize and refine developmental outcomes originally guided by generic effects.

scholarly journals Synchrony and pattern formation of coupled genetic oscillators on a chip of artificial cells

2017 ◽  
Vol 114 (44) ◽  
pp. 11609-11614 ◽  
Author(s):  
Alexandra M. Tayar ◽  
Eyal Karzbrun ◽  
Vincent Noireaux ◽  
Roy H. Bar-Ziv
Keyword(s):  
Pattern Formation ◽  
Large Scale ◽  
Reaction Diffusion ◽  
Biochemical Networks ◽  
Artificial Cells ◽  
Diffusion Dynamics ◽  
Oscillatory Reactions ◽  
Potential Applications ◽  
On Chip ◽  
Genetic Oscillators

Understanding how biochemical networks lead to large-scale nonequilibrium self-organization and pattern formation in life is a major challenge, with important implications for the design of programmable synthetic systems. Here, we assembled cell-free genetic oscillators in a spatially distributed system of on-chip DNA compartments as artificial cells, and measured reaction–diffusion dynamics at the single-cell level up to the multicell scale. Using a cell-free gene network we programmed molecular interactions that control the frequency of oscillations, population variability, and dynamical stability. We observed frequency entrainment, synchronized oscillatory reactions and pattern formation in space, as manifestation of collective behavior. The transition to synchrony occurs as the local coupling between compartments strengthens. Spatiotemporal oscillations are induced either by a concentration gradient of a diffusible signal, or by spontaneous symmetry breaking close to a transition from oscillatory to nonoscillatory dynamics. This work offers design principles for programmable biochemical reactions with potential applications to autonomous sensing, distributed computing, and biomedical diagnostics.

scholarly journals An in vitro–in silico interface platform for spatiotemporal analysis of pattern formation in collective epithelial cells

2016 ◽  
Vol 8 (8) ◽  
pp. 861-868 ◽  
Author(s):  
M. Hagiwara
Keyword(s):  
Cell Culture ◽  
Pattern Formation ◽  
Epithelial Cells ◽  
In Silico ◽  
Reaction Diffusion ◽  
Spatiotemporal Analysis ◽  
Bronchial Epithelial ◽  
Reaction Diffusion Model ◽  
2D Pattern

The mechanisms of 2D pattern formation in bronchial epithelial cells were dynamically analyzed by controlled cell culture and a reaction-diffusion model.

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