scholarly journals Self-generated oxygen gradients control collective aggregation of photosynthetic microbes

2021 ◽  
Vol 18 (185) ◽  
Author(s):  
Alexandros A. Fragkopoulos ◽  
Jérémy Vachier ◽  
Johannes Frey ◽  
Flora-Maud Le Menn ◽  
Marco G. Mazza ◽  
...  
Keyword(s):  
Energy Production ◽  
Diffusion Mechanism ◽  
Critical Density ◽  
Continuum Theory ◽  
Reaction Diffusion ◽  
Microbial Populations ◽  
Low Light ◽  
Cell Cycles ◽  
Oxygen Gradients ◽  
Cell Densities

For billions of years, photosynthetic microbes have evolved under the variable exposure to sunlight in diverse ecosystems and microhabitats all over our planet. Their abilities to dynamically respond to alterations of the luminous intensity, including phototaxis, surface association and diurnal cell cycles, are pivotal for their survival. If these strategies fail in the absence of light, the microbes can still sustain essential metabolic functionalities and motility by switching their energy production from photosynthesis to oxygen respiration. For suspensions of motile C. reinhardtii cells above a critical density, we demonstrate that this switch reversibly controls collective microbial aggregation. Aerobic respiration dominates over photosynthesis in conditions of low light, which causes the microbial motility to sensitively depend on the local availability of oxygen. For dense microbial populations in self-generated oxygen gradients, microfluidic experiments and continuum theory based on a reaction–diffusion mechanism show that oxygen-regulated motility enables the collective emergence of highly localized regions of high and low cell densities.

scholarly journals Self-generated oxygen gradients control collective aggregation of photosynthetic microbes

2021 ◽  
Author(s):  
Alexandros Fragkopoulos ◽  
Jeremy Vachier ◽  
Johannes Frey ◽  
Flora-Maud Le Menn ◽  
Marco Mazza ◽  
...  
Keyword(s):  
Diffusion Mechanism ◽  
Critical Density ◽  
Continuum Theory ◽  
Reaction Diffusion ◽  
Microbial Populations ◽  
Environmental Cues ◽  
Low Light ◽  
Cell Cycles ◽  
Oxygen Gradients ◽  
Cell Densities

Abstract For billions of years photosynthetic microbes have evolved under the variable exposure to sunlight in diverse ecosystems and microhabitats all over our planet. Their abilities to dynamically respond to alterations of the luminous intensity, including phototaxis, surface association and diurnal cell cycles, are pivotal for survival, far more than any other environmental cues. If these strategies fail in the absence of light, the microbes can still sustain essential metabolic functionalities and motility by switching their energy production from photosynthesis to oxygen respiration. For suspensions of motile microbes above a critical density we demonstrate that this switch reversibly controls collective microbial aggregation. Aerobic respiration dominates over photosynthesis in conditions of low light, which causes the microbial motility to sensitively depend on the local availability of oxygen. For dense microbial populations in self-generated oxygen gradients, microfluidic experiments and continuum theory based on a reaction-diffusion mechanism show that oxygen-regulated motility enables the collective emergence of highly localized regions of high and low cell densities.

scholarly journals Travelling colourful patterns in self-organized cellulose-based liquid crystalline structures

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Pedro E. S. Silva ◽  
Ricardo Chagas ◽  
Susete N. Fernandes ◽  
Pawel Pieranski ◽  
Robin L. B. Selinger ◽  
...  
Keyword(s):  
Simple Model ◽  
Temporal Variation ◽  
Liquid Crystalline ◽  
Diffusion Mechanism ◽  
Reaction Diffusion ◽  
Self Organization ◽  
Spatial And Temporal Variation ◽  
Living Matter ◽  
Equilibrium Conditions ◽  
Self Organized

AbstractCellulose-based systems are useful for many applications. However, the issue of self-organization under non-equilibrium conditions, which is ubiquitous in living matter, has scarcely been addressed in cellulose-based materials. Here, we show that quasi-2D preparations of a lyotropic cellulose-based cholesteric mesophase display travelling colourful patterns, which are generated by a chemical reaction-diffusion mechanism being simultaneous with the evaporation of solvents at the boundaries. These patterns involve spatial and temporal variation in the amplitude and sign of the helix´s pitch. We propose a simple model, based on a reaction-diffusion mechanism, which simulates the observed spatiotemporal colour behaviour.

Reaction-Diffusion Modeling of Photopolymerization During Femtosecond Projection Two-Photon Lithography

2021 ◽  
Author(s):  
Rushil Pingali ◽  
Sourabh K. Saha
Keyword(s):  
Diffusion Mechanism ◽  
Chemical Properties ◽  
Reaction Diffusion ◽  
Element Model ◽  
Polymerization Process ◽  
Layer By Layer ◽  
Length Scales ◽  
Two Photon ◽  
Reaction Diffusion Model ◽  
Direct Laser

Abstract Two-photon lithography (TPL) is a polymerization-based direct laser writing process that is capable of fabricating arbitrarily complex three-dimensional (3D) structures with submicron features. Traditional TPL techniques have limited scalability due to the slow point-by-point serial writing scheme. The femtosecond projection TPL (FP-TPL) technique increases printing rate by a thousand times by enabling layer-by-layer parallelization. However, parallelization alters the time and the length scales of the underlying polymerization process. It is therefore challenging to apply the models of serial TPL to accurately predict process outcome during FP-TPL. To solve this problem, we have generated a finite element model of the polymerization process on the time and length scales relevant to FP-TPL. The model is based on the reaction-diffusion mechanism that underlies polymerization. We have applied this model to predict the geometry of nanowires printed under a variety of conditions and compared these predictions against empirical data. Our model accurately predicts the nanowire widths. However, accuracy of aspect ratio prediction is hindered by uncertain values of the chemical properties of the photopolymer. Nevertheless, our results demonstrate that the reaction-diffusion model can accurately capture the effect of controllable parameters on FP-TPL process outcome and can therefore be used for process control and optimization.

scholarly journals Reaction Diffusion and Chemotaxis for Decentralized Gathering on FPGAs

2009 ◽  
Vol 2009 ◽  
pp. 1-15 ◽  
Author(s):  
Bernard Girau ◽  
César Torres-Huitzil ◽  
Nikolaos Vlassopoulos ◽  
José Hugo Barrón-Zambrano
Keyword(s):  
Large Scale ◽  
Complex Dynamics ◽  
Diffusion Mechanism ◽  
Reaction Diffusion ◽  
Fpga Implementation ◽  
Cellular Slime Mold ◽  
Reaction Diffusion Model ◽  
Cellular Slime ◽  
Computational Resources ◽  
Embedded Implementation

We consider here the feasibility of gathering multiple computational resources by means of decentralized and simple local rules. We study such decentralized gathering by means of a stochastic model inspired from biology: the aggregation of theDictyostelium discoideumcellular slime mold. The environment transmits information according to a reaction-diffusion mechanism and the agents move by following excitation fronts. Despite its simplicity this model exhibits interesting properties of self-organization and robustness to obstacles. We first describe the FPGA implementation of the environment alone, to perform large scale and rapid simulations of the complex dynamics of this reaction-diffusion model. Then we describe the FPGA implementation of the environment together with the agents, to study the major challenges that must be solved when designing a fast embedded implementation of the decentralized gathering model. We analyze the results according to the different goals of these hardware implementations.

scholarly journals Rubisco proton production can drive the elevation of CO2 within condensates and carboxysomes

2020 ◽  
Author(s):  
Benedict M. Long ◽  
Britta Förster ◽  
Sacha B. Pulsford ◽  
G. Dean Price ◽  
Murray R. Badger
Keyword(s):  
Reaction Diffusion ◽  
Compartment Model ◽  
Low Light ◽  
Bisphosphate Carboxylase ◽  
Proton Production ◽  
Logical Sequence ◽  
Photosynthetic Carbon ◽  
Internal Ph ◽  
Novel Concept ◽  
Improved Function

ABSTRACTMembraneless organelles containing the enzyme Ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) are a common feature of organisms utilizing CO2 concentrating mechanisms (CCMs) to enhance photosynthetic carbon acquisition. In cyanobacteria and proteobacteria, the Rubisco condensate is encapsulated in a proteinaceous shell, collectively termed a carboxysome, while some algae and hornworts have evolved Rubisco condensates known as pyrenoids. In both cases, CO2 fixation is enhanced compared with the free enzyme. Previous mathematical models have attributed the improved function of carboxysomes to the generation of elevated CO2 within the organelle via a co-localized carbonic anhydrase (CA), and inwardly diffusing HCO3- which has accumulated in the cytoplasm via dedicated transporters. Here we present a novel concept in which we consider the net of two protons produced in every Rubisco carboxylase reaction. We evaluate this in a reaction-diffusion, compartment model to investigate functional advantages these protons may provide Rubisco condensates and carboxysomes, prior to the evolution of HCO3- accumulation. Our model highlights that diffusional resistance to reaction species within a condensate allows Rubisco-derived protons to drive the conversion of HCO3- to CO2 via co-localized CA, enhancing both condensate [CO2] and Rubisco rate. Protonation of Rubisco substrate (RuBP) and product (PGA) plays an important role in modulating internal pH and CO2 generation. Application of the model to putative evolutionary ancestors, prior to contemporary cellular HCO3- accumulation, revealed photosynthetic enhancements along a logical sequence of advancements, via Rubisco condensation, to fully-formed carboxysomes. Our model suggests that evolution of Rubisco condensation could be favored under low CO2 and low light environments.

Radiolaria: validating the Turing theory

2017 ◽  
Author(s):  
Bernard Richards
Keyword(s):  
Diffusion Mechanism ◽  
Three Dimensional ◽  
Reaction Diffusion ◽  
Two Dimensions ◽  
Three Dimensions ◽  
Black And White ◽  
Alan Turing ◽  
School Sports ◽  
The University ◽  
University Of Manchester

In his 1952 paper ‘The chemical basis of morphogenesis’ Turing postulated his now famous Morphogenesis Equation. He claimed that his theory would explain why plants and animals took the shapes they did. When I joined him, Turing suggested that I might solve his equation in three dimensions, a new problem. After many manipulations using rather sophisticated mathematics and one of the first factory-produced computers in the UK, I derived a series of solutions to Turing’s equation. I showed that these solutions explained the shapes of specimens of the marine creatures known as Radiolaria, and that they corresponded very closely to the actual spiny shapes of real radiolarians. My work provided further evidence for Turing’s theory of morphogenesis, and in particular for his belief that the external shapes exhibited by Radiolaria can be explained by his reaction–diffusion mechanism. While working in the Computing Machine Laboratory at the University of Manchester in the early 1950s, Alan Turing reignited the interests he had had in both botany and biology from his early youth. During his school-days he was more interested in the structure of the flowers on the school sports field than in the games played there (see Fig. 1.3). It is known that during the Second World War he discussed the problem of phyllotaxis (the arrangement of leaves and florets in plants), and then at Manchester he had some conversations with Claude Wardlaw, the Professor of Botany in the University. Turing was keen to take forward the work that D’Arcy Thompson had published in On Growth and Form in 1917. In his now-famous paper of 1952 Turing solved his own ‘Equation of Morphogenesis’ in two dimensions, and demonstrated a solution that could explain the ‘dappling’—the black-and-white patterns—on cows. The next step was for me to solve Turing’s equation in three dimensions. The two-dimensional case concerns only surface features of organisms, such as dappling, spots, and stripes, whereas the three-dimensional version concerns the overall shape of an organism. In 1953 I joined Turing as a research student in the University of Manchester, and he set me the task of solving his equation in three dimensions. A remarkable journey of collaboration began. Turing chatted to me in a very friendly fashion.

Pyrolysis behaviors dominated by the reaction–diffusion mechanism in the fluorine-free metal–organic decomposition process

2020 ◽  
Vol 8 (48) ◽  
pp. 17417-17428
Author(s):  
Jiangtao Shi ◽  
Yue Zhao ◽  
Yue Wu ◽  
Jingyuan Chu ◽  
Xiao Tang ◽  
...  
Keyword(s):  
Diffusion Model ◽  
Diffusion Mechanism ◽  
Reaction Diffusion ◽  
Decomposition Process ◽  
One Dimensional ◽  
Reaction Diffusion Model ◽  
Metal Organic ◽  
Free Metal ◽  
Organic Decomposition

In this work, pyrolysis behaviors dominated by the reaction–diffusion mechanism were investigated. And one-dimensional reaction–diffusion model is proposed.

scholarly journals Modelling Bacteria-Inspired Dynamics with Networks of Interacting Chemicals

Life ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. 63
Author(s):  
Tamás Bánsági ◽  
Annette F. Taylor
Keyword(s):  
Critical Density ◽  
Reaction Network ◽  
External Solution ◽  
Vital Role ◽  
Cellular Systems ◽  
Dependent Behavior ◽  
Cell Processes ◽  
Dynamical Features ◽  
Cell Densities

One approach to understanding how life-like properties emerge involves building synthetic cellular systems that mimic certain dynamical features of living cells such as bacteria. Here, we developed a model of a reaction network in a cellular system inspired by the ability of bacteria to form a biofilm in response to increasing cell density. Our aim was to determine the role of chemical feedback in the dynamics. The feedback was applied through the enzymatic rate dependence on pH, as pH is an important parameter that controls the rates of processes in cells. We found that a switch in pH can be used to drive base-catalyzed gelation or precipitation of a substance in the external solution. A critical density of cells was required for gelation that was essentially independent of the pH-driven feedback. However, the cell pH reached a higher maximum as a result of the appearance of pH oscillations with feedback. Thus, we conclude that while feedback may not play a vital role in some density-dependent behavior in cellular systems, it nevertheless can be exploited to activate internally regulated cell processes at low cell densities.

scholarly journals Cell Cycle Regulation by Light inProchlorococcus Strains

2001 ◽  
Vol 67 (2) ◽  
pp. 782-790 ◽  
Author(s):  
Stéphan Jacquet ◽  
Frédéric Partensky ◽  
Dominique Marie ◽  
Raffaella Casotti ◽  
Daniel Vaulot
Keyword(s):  
Cell Cycle ◽  
High Irradiance ◽  
S Phase ◽  
Low Light ◽  
Close Coupling ◽  
Cell Cycles ◽  
Flow Cytometric ◽  
Initiation Of Dna Replication ◽  
Cell Cycling ◽  
Cycle Regulation

ABSTRACT The effect of light on the synchronization of cell cycling was investigated in several strains of the oceanic photosynthetic prokaryote Prochlorococcus using flow cytometry. When exposed to a light-dark (L-D) cycle with an irradiance of 25 μmol of quanta · m−2 s−1, the low-light-adapted strain SS 120 appeared to be better synchronized than the high-light-adapted strain PCC 9511. Submitting L-D-entrained populations to shifts (advances or delays) in the timing of the “light on” signal translated to corresponding shifts in the initiation of the S phase, suggesting that this signal is a key parameter for the synchronization of population cell cycles. Cultures that were shifted from an L-D cycle to continuous irradiance showed persistent diel oscillations of flow-cytometric signals (light scatter and chlorophyll fluorescence) but with significantly reduced amplitudes and a phase shift. Complete darkness arrested most of the cells in the G1 phase of the cell cycle, indicating that light is required to trigger the initiation of DNA replication and cell division. However, some cells also arrested in the S phase, suggesting that cell cycle controls in Prochlorococcus spp. are not as strict as in marine Synechococcus spp. ShiftingProchlorococcus cells from low to high irradiance translated quasi-instantaneously into an increase of cells in both the S and G2 phases of the cell cycle and then into faster growth, whereas the inverse shift induced rapid slowing of the population growth rate. These data suggest a close coupling between irradiance levels and cell cycling in Prochlorococcus spp.

Turing's model and branching tip growth: relation of time and spatial scales in morphogenesis, with application to Micrasterias

1987 ◽  
Vol 65 (7) ◽  
pp. 1308-1319 ◽  
Author(s):  
Thurston C. Lacalli ◽  
Lionel G. Harrison
Keyword(s):  
Diffusion Theory ◽  
Spatial Scales ◽  
Diffusion Mechanism ◽  
Effective Diffusivity ◽  
Reaction Diffusion ◽  
Time And Space ◽  
Branch Formation ◽  
Simplifying Assumptions ◽  
Growth Activity ◽  
Probable Site

Morphogenesis following cell division in Micrasterias rotata is by outgrowth and repeated branching of a series of semicell lobes. Though successive branching events are qualitatively similar, they display changes in time and space scales, and these can be quantitated with the aid of autoradiographic patterns of labelled wall precursors that appear late in morphogenesis but which seem to represent its history. This enables us to consider branching as the conversion of a single centre of growth activity into two and to attempt to locate these centres precisely, in terms of both position and time of establishment. Temporal and spatial scales both decrease, by 75%, through a sequence of five branching events, in linear functional relationship to each other. This correlation points toward kinetic control of morphogenesis, i.e., the involvement of something like a reaction–diffusion mechanism. We analyse this possibility in terms of available reaction–diffusion theory to show how, after various simplifying assumptions, and if the time and space scales of branch formation are known, an effective diffusivity, [Formula: see text], for the patterning mechanism can be estimated. For M. rotata we obtain orders of magnitude: [Formula: see text], with an upper limit on the diffusivity of the faster diffusing of the two morphogenetic substances in the mechanism of ca. 1 × 10−7 cm2/s. These values implicate the cell membrane as the most probable site of pattern formation.

Sign in / Sign up

Export Citation Format

Share Document