Antibody-Mediated Protein Knockdown Reveals Distal-less Functions for Eyespots and Parafocal Elements in Butterfly Wing Color Pattern Development.

One of the important genes for eyespot development in butterfly wings is Distal-less. Its function has been evaluated via several methods, including CRISPR/Cas9 genome editing. However, functional inhibition may be performed at the right time at the right place using a different method. Here, we used a novel protein delivery method for pupal wing tissues in vivo to inactivate a target protein, Distal-less, with a polyclonal anti-Distal-less antibody using the blue pansy butterfly Junonia orithya. We first demonstrated that various antibodies including the anti-Distal-less antibody were delivered to wing epithelial cells in vivo in this species. Treatment with the anti-Distal-less antibody reduced eyespot size, confirming the positive role of Distal-less in eyespot development. The treatment eliminated or deformed a parafocal element, suggesting a positive role of Distal-less in the development of the parafocal element. This result also suggested the integrity of an eyespot and its corresponding parafocal element as the border symmetry system. Taken together, these findings demonstrate that the antibody-mediated protein knockdown method is a useful tool for functional assays of proteins, such as Distal-less, expressed in pupal wing tissues, and that Distal-less functions for eyespots and parafocal elements in butterfly wing color pattern development.

Pattern Formation and Bistability in a Synthetic Intercellular Genetic Toggle.

Differentiation within multicellular organisms is a complex process that helps to establish spatial patterning and tissue formation within the body. Often, the differentiation of cells is governed by morphogens and intercellular signaling molecules that guide the fate of each cell, frequently using toggle-like regulatory components. Synthetic biologists have long sought to recapitulate patterned differentiation with engineered cellular communities, and various methods for differentiating bacteria have been invented. Here, we couple a synthetic corepressive toggle switch with intercellular signaling pathways to create a "quorum-sensing toggle". We show that this circuit not only exhibits population-wide bistability in a well-mixed liquid environment but also generates patterns of differentiation in colonies grown on agar containing an externally supplied morphogen. If coupled to other metabolic processes, circuits such as the one described here would allow for the engineering of spatially patterned, differentiated bacteria for use in biomaterials and bioelectronics.

The pentatricopeptide repeat protein DG1 promotes the transition to bilateral symmetry during Arabidopsis embryogenesis through GUN1-mediated plastid signals.

During Arabidopsis embryogenesis, the transition of the embryo's symmetry from radial to bilateral between the globular and heart stage is a crucial event, involving the formation of cotyledon primordia and concurrently the establishment of a shoot apical meristem (SAM). However, a coherent framework of how this transition is achieved remains to be elucidated. In this study, we investigated the function of DELAYED GREENING 1 (DG1) in Arabidopsis embryogenesis using a newly identified dg1-3 mutant. The absence of chloroplast-localized DG1 in the mutants led to embryos being arrested at the globular or heart stage, accompanied by an expansion of WUSCHEL (WUS) and SHOOT MERISTEMLESS (STM) expression. This finding pinpoints the essential role of DG1 in regulating the transition to bilateral symmetry. Furthermore, we showed that this regulation of DG1 may not depend on its role in plastid RNA editing. Nevertheless, we demonstrated that the DG1 function in establishing bilateral symmetry is genetically mediated by GENOMES UNCOUPLED 1 (GUN1), which represses the transition process in dg1-3 embryos. Collectively, our results reveal that DG1 functionally antagonizes GUN1 to promote the transition of the Arabidopsis embryo's symmetry from radial to bilateral and highlight the role of plastid signals in regulating pattern formation during plant embryogenesis.

Controlled Protein-Membrane Interactions Modulate Self-Organization of Min Protein Patterns.

Self-organizing protein patterns are crucial for living systems, governing important cellular processes such as polarization and division. While the field of protein self-organization has reached a point where basic pattern-forming mechanisms can be reconstituted in vitro using purified proteins, understanding how cells can dynamically switch and modulate these patterns, especially when transiently needed, remains an interesting frontier. Here, we demonstrate the efficient regulation of self-organizing protein patterns through the modulation of simple biophysical membrane parameters. Our investigation focuses on the impact of membrane affinity changes on Min protein patterns at lipid membranes composed of Escherichia coli lipids or minimal lipid compositions, and we present three major results. First, we observed the emergence of a diverse array of pattern phenotypes, ranging from waves over flower-shaped patterns to snowflake-like structures. Second, we demonstrated the dependency of these patterns on the density of protein-membrane linkers. Finally, we demonstrate that the shape of snowflake-like patterns is fine-tuned by membrane charge. Our results demonstrate the significant influence of membrane linkage as a straightforward biophysical parameter governing protein pattern formation. Our research points towards a simple yet intriguing mechanism by which cells can adeptly tune and switch protein patterns on the mesoscale.

A distinct foliar pigmentation pattern formed by activator-repressor gradients upstream of an anthocyanin-activating R2R3-MYB.

The emergence of novel traits is often preceded by a potentiation phase, when all the genetic components necessary for producing the trait are assembled. However, elucidating these potentiating factors is challenging. We have previously shown that an anthocyanin-activating R2R3-MYB, STRIPY, triggers the emergence of a distinct foliar pigmentation pattern in the monkeyflower Mimulus verbenaceus. Here, using forward and reverse genetics approaches, we identify three potentiating factors that pattern STRIPY expression: MvHY5, a master regulator of light signaling that activates STRIPY and is expressed throughout the leaf, and two leaf developmental regulators, MvALOG1 and MvTCP5, that are expressed in opposing gradients along the leaf proximodistal axis and negatively regulate STRIPY. These results provide strong empirical evidence that phenotypic novelties can be potentiated through incorporation into preexisting genetic regulatory networks and highlight the importance of positional information in patterning the novel foliar stripe.

Gestational VPA exposure reduces the density of juxtapositions between TH+ axons and calretinin or calbindin expressing cells in the ventrobasal forebrain of neonatal mice.

Gestational exposure to valproic acid (VPA) is a valid rodent model of human autism spectrum disorder (ASD). VPA treatment is known to bring about specific behavioral deficits of sociability, matching similar alterations in human autism. Previous quantitative morphometric studies from our laboratory showed a marked reduction and defasciculation of the mesotelencephalic dopaminergic pathway of VPA treated mice, along with a decrease in tissue dopamine in the nucleus accumbens (NAc), but not in the caudatoputamen (CPu). In the present study, the correlative distribution of tyrosine hydroxylase positive (TH+) putative axon terminals, presynaptic to the target neurons containing calretinin (CR) or calbindin (CB), was assessed using double fluorescent immunocytochemistry and confocal laser microscopy in two dopamine recipient forebrain regions, NAc and olfactory tubercle (OT) of neonatal mice (mothers injected with VPA on ED13.5, pups investigated on PD7). Representative image stacks were volumetrically analyzed for spatial proximity and abundance of presynaptic (TH+) and postsynaptic (CR+, CB+) structures with the help of an Imaris (Bitplane) software. In VPA mice, TH/CR juxtapositions were reduced in the NAc, whereas the TH/CB juxtapositions were impoverished in OT. Volume ratios of CR+ and CB+ elements remained unchanged in NAc, whereas that of CB+ was markedly reduced in OT; here the abundance of TH+ axons was also diminished. CR and CB were found to partially colocalize with TH in the VTA and SN. In VPA exposed mice, the abundance of CR+ (but not CB+) perikarya increased both in VTA and SN, however, this upregulation was not mirrored by an increase of the number of CR+/TH+ double labeled cells. The observed reduction of total CB (but not of CB+ perikarya) in the OT of VPA exposed animals signifies a diminished probability of synaptic contacts with afferent TH+ axons, presumably by reducing the available synaptic surface. Altered dopaminergic input to ventrobasal forebrain targets during late embryonic development will likely perturb the development and consolidation of neural and synaptic architecture, resulting in lasting changes of the neuronal patterning (detected here as reduced synaptic input to dopaminoceptive interneurons) in ventrobasal forebrain regions specifically involved in motivation and reward.

Adsorption on a Spherical Colloidal Particle from a Mixture of Nanoparticles with Competing Interactions.

Adsorption of nanoparticles on a spherical colloidal particle is studied by molecular dynamics simulations. We consider a generic model for a mixture of nanoparticles with energetically favored self-assembly into alternating layers of the two components. When both components are attracted to the colloidal particle, the adsorbed nanoparticles self-assemble either into alternating parallel tori and clusters at the two poles of the colloidal particle, or into alternating spirals wrapped around the spherical surface. The long-lived metastable states obtained in simulations follow from the spherical shape of the adsorbing surface and the requirement that the neighboring chains of the nanoparticles are composed of different components. A geometrical construction leading to all such patterns is presented. When the second component particles are repelled from the colloidal particle and the attraction of the first component is strong, the attracted particles form a monolayer at the surface of the colloidal particle that screens the repulsion of the second component. The subsequent adsorbed alternating spherical layers of the two components form together a thick shell. This structure leads to the adsorption that is larger than in the case of the same attraction of the two components to the colloidal particle.

Instabilities and self-organization in spatiotemporal epidemic dynamics driven by nonlinearity and noise.

Theoretical analysis of epidemic dynamics has attracted significant attention in the aftermath of the COVID-19 pandemic. In this article, we study dynamic instabilities in a spatiotemporal compartmental epidemic model represented by a stochastic system of coupled partial differential equations (SPDE). Saturation effects in infection spread-anchored in physical considerations-lead to strong nonlinearities in the SPDE. Our goal is to study the onset of dynamic, Turing-type instabilities, and the concomitant emergence of steady-state patterns under the interplay between three critical model parameters-the saturation parameter, the noise intensity, and the transmission rate. Employing a second-order perturbation analysis to investigate stability, we uncover both diffusion-driven and noise-induced instabilities and corresponding self-organized distinct patterns of infection spread in the steady state. We also analyze the effects of the saturation parameter and the transmission rate on the instabilities and the pattern formation. In summary, our results indicate that the nuanced interplay between the three parameters considered has a profound effect on the emergence of dynamical instabilities and therefore on pattern formation in the steady state. Moreover, due to the central role played by the Turing phenomenon in pattern formation in a variety of biological dynamic systems, the results are expected to have broader significance beyond epidemic dynamics.

Unveiling Hidden Hyperuniformity: Radial Turing Pattern Formation of Marangoni-Driven SiO2 Nanoparticles on Liquid Metal Surface.

Mastering the self-organization of nanoparticle morphologies is pivotal in soft matter physics and film growth. Silicon dioxide (SiO2) nanoparticles are an archetypical model of nanomotor in soft matter. Here, the emphasis is on the self-organizing behavior of SiO2 nanoparticles under extreme conditions. It is unveiled that manipulating the states of the metal substrate profoundly dictates the motion characteristics of SiO2 nanoparticles. This manipulation triggers the emergence of intricate morphologies and distinctive patterns. Employing a reaction-diffusion model, the fundamental roles played by Brownian motion and Marangoni-driven motion in shaping fractal structures and radial Turing patterns are demonstrated, respectively. Notably, these radial Turing patterns showcase hyperuniform order, challenging conventional notions of film morphology. These discoveries pave the way for crafting non-equilibrium morphological materials, poised with the potential for self-healing, adaptability, and innovative applications.

The molecular and cellular choreography of early mammalian lung development.

Mammalian lung development starts from a specific cluster of endodermal cells situated within the ventral foregut region. With the orchestrating of delicate choreography of transcription factors, signaling pathways, and cell-cell communications, the endodermal diverticulum extends into the surrounding mesenchyme, and builds the cellular and structural basis of the complex respiratory system. This review provides a comprehensive overview of the current molecular insights of mammalian lung development, with a particular focus on the early stage of lung cell fate differentiation and spatial patterning. Furthermore, we explore the implications of several congenital respiratory diseases and the relevance to early organogenesis. Finally, we summarize the unprecedented knowledge concerning lung cell compositions, regulatory networks as well as the promising prospect for gaining an unbiased understanding of lung development and lung malformations through state-of-the-art single-cell omics.

Entropy Production in Reaction-Diffusion Systems Confined in Narrow Channels.

This work analyzes the effect of wall geometry when a reaction-diffusion system is confined to a narrow channel. In particular, we study the entropy production density in the reversible Gray-Scott system. Using an effective diffusion equation that considers modifications by the channel characteristics, we find that the entropy density changes its value but not its qualitative behavior, which helps explore the structure-formation space.

Chronobiology of Viscum album L.: a time series of daily metabolomic fingerprints spanning 27 years.

Introduction: European mistletoe (Viscum album L.) has been gaining increasing interest in the field of oncology as a clinically relevant adjunctive treatment in many forms of cancer. In the field of phytopharmacology, harvesting time is pivotal. In the last century, a form of metabolomic fingerprinting based on pattern formation was proposed as a way to determine optimal harvesting times to ensure high quality of mistletoe as raw material for pharmaceutical use. In order to further evaluate the information obtained with this metabolomic fingerprinting method, we analysed a large time series of previously undigitised daily mistletoe chromatograms dating back to the 1950s. Methods: These chromatograms were scanned and evaluated using computerized image analysis, resulting in 12 descriptors for each individual chromatogram. We performed a statistical analysis of the data obtained, investigating statistical distributions, cross-correlations and time self-correlations. Results: The analysed dataset spanning about 27 years, contains 19,037 evaluable chromatograms in daily resolution. Based on the distribution and cross-correlation analyses, the 12 descriptors could be clustered into six independent groups describing different aspects of the chromatograms. One descriptor was found to mirror the annual rhythm being well correlated with temperature and a phase shift of 10 days. The time self-correlation analysis showed that most other descriptors had a characteristic self-correlation of ∼50 days, which points to further infradian rhythms (i.e., more than 24 h). Discussion: To our knowledge, this dataset is the largest of its type. The combination of this form of metabolomic fingerprinting with the proposed computer analysis seems to be a promising tool to characterise biological variations of mistletoe. Additional research is underway to further analyse the different rhythms present in this dataset.

Emergence of non-trivial solutions from trivial solutions in reaction-diffusion equations for pattern formation.

Reaction-diffusion equations serve as fundamental tools in describing pattern formation in biology. In these models, nonuniform steady states often represent stationary spatial patterns. Notably, these steady states are not unique, and unveiling them mathematically presents challenges. In this paper, we introduce a framework based on bifurcation theory to address pattern formation problems, specifically examining whether nonuniform steady states can bifurcate from trivial ones. Furthermore, we employ linear stability analysis to investigate the stability of the trivial steady-state solutions. We apply the method to two classic reaction-diffusion models: the Schnakenberg model and the Gray-Scott model. For both models, our approach effectively reveals many nonuniform steady states and assesses the stability of the trivial solution. Numerical computations are also presented to validate the solution structures for these models.

Chemical composition from photos: Dried solution drops reveal a morphogenetic tree.

Under nonequilibrium conditions, inorganic systems can produce a wealth of life-like shapes and patterns which, compared to well-formed crystalline materials, remain widely unexplored. A seemingly simple example is the formation of salt deposits during the evaporation of sessile droplets. These evaporites show great variations in their specific patterns including single rings, creep, small crystals, fractals, and featureless disks. We have explored the patterns of 42 different salts at otherwise constant conditions. Based on 7,500 images, we show that distinct pattern families can be identified and that some salts (e.g., Na2SO4 and NH4NO3) are bifurcated creating two distinct motifs. Family affiliations cannot be predicted a priori from composition alone but rather emerge from the complex interplay of evaporation, crystallization, thermodynamics, capillarity, and fluid flow. Nonetheless, chemical composition can be predicted from the deposit pattern with surprisingly high accuracy even if the set of reference images is small. These findings suggest possible applications including smartphone-based analyses and lightweight tools for space missions.

Ring-shaped colloidal patterns on saline water films.

HYPOTHESIS: Electrostatically stabilised colloidal particles destabilise when brought into contact with cations causing the particles to aggregate in clusters. When a drop with stabilised colloidal partices is deposited on a liquid film containing cations the delicate balance between the fluid-mechanical and physicochemical properties of the system governs the spreading dynamics and formation of colloidal particle clusters. EXPERIMENTS: High-speed imaging and digital holographic microscopy were used to characterise the spreading process. FINDINGS: We reveal that a spreading colloidal drop evolves into a ring-shaped pattern after it is deposited on a thin saline water film. Clustered colloidal particles aggregate into larger trapezoidally-shaped 'supraclusters'. Using a simple model we show that the trapezoidal shape of the supraclusters is determined by the transition from inertial spreading dynamics to Marangoni flow. These results may be of interest to applications such as wet-on-wet inkjet printing, where particle destabilisation and hydrodynamic flow coexist.

Geo-evolutionary feedbacks: integrating rapid evolution and landscape change.

We develop a conceptual framework for geo-evolutionary feedbacks which describes the mutual interplay between landscape change and the evolution of traits of organisms residing on the landscape, with an emphasis on contemporary timeframes. Geo-evolutionary feedbacks can be realized via the direct evolution of geomorphic engineering traits or can be mediated by the evolution of trait variation that affects the population size and distribution of the specific geomorphic engineering organisms involved. Organisms that modify their local environments provide the basis for patch-scale geo-evolutionary feedbacks, whereas spatial self-organization provides a mechanism for geo-evolutionary feedbacks at the landscape scale. Understanding these likely prevalent geo-evolutionary feedbacks, that occur at timescales similar to anthropogenic climate change, will be essential to better predict landscape adaptive capacity and change.

Interspecific dispersal constraints suppress pattern formation in metacommunities.

Decisions to disperse from a habitat stand out among organismal behaviours as pivotal drivers of ecosystem dynamics across scales. Encounters with other species are an important component of adaptive decision-making in dispersal, resulting in widespread behaviours like tracking resources or avoiding consumers in space. Despite this, metacommunity models often treat dispersal as a function of intraspecific density alone. We show, focusing initially on three-species network motifs, that interspecific dispersal rules generally drive a transition in metacommunities from homogeneous steady states to self-organized heterogeneous spatial patterns. However, when ecologically realistic constraints reflecting adaptive behaviours are imposed-prey tracking and predator avoidance-a pronounced homogenizing effect emerges where spatial pattern formation is suppressed. We demonstrate this effect for each motif by computing master stability functions that separate the contributions of local and spatial interactions to pattern formation. We extend this result to species-rich food webs using a random matrix approach, where we find that eventually, webs become large enough to override the homogenizing effect of adaptive dispersal behaviours, leading once again to predominately pattern-forming dynamics. Our results emphasize the critical role of interspecific dispersal rules in shaping spatial patterns across landscapes, highlighting the need to incorporate adaptive behavioural constraints in efforts to link local species interactions and metacommunity structure. This article is part of the theme issue 'Diversity-dependence of dispersal: interspecific interactions determine spatial dynamics'.

Novel techniques to analyze dynamical properties of quantum chaos with peculiar evidence of hybrid systems confinement.

Recent results demonstrate the dynamical peculiarities of the quantum chaos within the hybrid systems by chaotic parameters and probe the pattern formation under the influence of condensation. The complex dynamic behavior of the considered systems was determined with numerical simulation and presented an efficient technique that studied fractional systems comprising chaos-coherence fractions. The findings divulge the peculiar association between the coherence structure and the correlations at finite relative momenta. Thus the present study helps to explore the partially chaos hybrid systems in order to stimulate the experimental applications of nonlinear phenomena. The coherent-chaotic parameters can be measured by examining the chaos peculiarities that possess explicit relations with the condensations to demonstrate the environs of the physical systems. We investigate the influence of the multiplicities, chaos, momentum and temperature of the nonlinear system on the coherent-chaotic normalized correlations. The chaotic parameters are suppressed considerably with the coherence fraction and it appears numerically zero at maximum condensation and one at ideal chaos emissions. We procure that the meaningful parameters decrease significantly with the multiplicity of the nonlinear systems and increase with the momentum in the specified regimes. The identical multiplicity leads to contemplating the coherence and thus the normalized chaotic parameters within its spectacular influences exhibit significance worth contemplating in earnest. The findings underscore the significance of cogitating correlations in deciphering the nonlinear system characteristics and bestowing extraordinary perceptiveness into the convoluted essence of complex systems. The contemplated methodology can be applied to evaluating and analyzing the nonlinear systems and such an innovative approach computes the problems of celestial mechanics, heartbeats and chemical reactions in engineering and medical fields.

Evolution of Cooperation in Spatio-Temporal Evolutionary Games with Public Goods Feedback.

In biology, evolutionary game-theoretical models often arise in which players' strategies impact the state of the environment, driving feedback between strategy and the surroundings. In this case, cooperative interactions can be applied to studying ecological systems, animal or microorganism populations, and cells producing or actively extracting a growth resource from their environment. We consider the framework of eco-evolutionary game theory with replicator dynamics and growth-limiting public goods extracted by population members from some external source. It is known that the two sub-populations of cooperators and defectors can develop spatio-temporal patterns that enable long-term coexistence in the shared environment. To investigate this phenomenon and unveil the mechanisms that sustain cooperation, we analyze two eco-evolutionary models: a well-mixed environment and a heterogeneous model with spatial diffusion. In the latter, we integrate spatial diffusion into replicator dynamics. Our findings reveal rich strategy dynamics, including bistability and bifurcations, in the temporal system and spatial stability, as well as Turing instability, Turing-Hopf bifurcations, and chaos in the diffusion system. The results indicate that effective mechanisms to promote cooperation include increasing the player density, decreasing the relative timescale, controlling the density of initial cooperators, improving the diffusion rate of the public goods, lowering the diffusion rate of the cooperators, and enhancing the payoffs to the cooperators. We provide the conditions for the existence, stability, and occurrence of bifurcations in both systems. Our analysis can be applied to dynamic phenomena in fields as diverse as human decision-making, microorganism growth factors secretion, and group hunting.

From signalling to form: the coordination of neural tube patterning.

The development of the vertebrate spinal cord involves the formation of the neural tube and the generation of multiple distinct cell types. The process starts during gastrulation, combining axial elongation with specification of neural cells and the formation of the neuroepithelium. Tissue movements produce the neural tube which is then exposed to signals that provide patterning information to neural progenitors. The intracellular response to these signals, via a gene regulatory network, governs the spatial and temporal differentiation of progenitors into specific cell types, facilitating the assembly of functional neuronal circuits. The interplay between the gene regulatory network, cell movement, and tissue mechanics generates the conserved neural tube pattern observed across species. In this review we offer an overview of the molecular and cellular processes governing the formation and patterning of the neural tube, highlighting how the remarkable complexity and precision of vertebrate nervous system arises. We argue that a multidisciplinary and multiscale understanding of the neural tube development, paired with the study of species-specific strategies, will be crucial to tackle the open questions.