Collective chemotaxis in a Voronoi model for confluent clusters

Collective chemotaxis, where single cells cannot climb a biochemical signaling gradient but clusters of cells can, has been observed in different biological contexts, including confluent tissues where there are no gaps or overlaps between cells. Although particle-based models have been developed that predict important features of collective chemotaxis, the mechanisms in those models depend on particle overlaps, and so it remains unclear if they can explain behavior in confluent systems. Here, we develop an open-source code that couples a 2D Voronoi simulation for confluent cell mechanics to a dynamic chemical signal that can diffuse, advect, and/or degrade, and use the code to study potential mechanisms for collective chemotaxis in cellular monolayers. We first study the impact of advection on collective chemotaxis, and delineate a regime where advective terms are important. Next, we investigate two possible chemotactic mechanisms, contact inhibition of locomotion and heterotypic interfacial tension, and demonstrate that both can drive collective chemotaxis in certain parameter regimes. We further demonstrate that the scaling behavior of cluster motion is well-captured by simple analytic theories.

Antennal and palpal sensilla of three predatory Lispe species (Diptera: Muscidae): an ultrastructural investigation

Antennae and maxillary palps are the most important chemical reception organs of flies. So far, the morphology of antennae and maxillary palps of flies of most feeding habits have been well described, except for that of relatively rare aquatic predatory species. This study describes sensilla on antennae and maxillary palps of three aquatic predatory Lispe species: Lispe longicollis, L. orientalis and L. pygmaea. Types, distribution, and density of sensilla are characterised via light and scanning electron microscopy. One type of mechanoreceptors is found on antennal scape. Mechanoreceptors (two subtypes) and one single pedicellar button (in L. pygmaea) are located on antennal pedicel. Four types of sensilla are discovered on antennal postpedicel: trichoid sensilla, basiconic sensilla (three subtypes), coeloconic sensilla and clavate sensilla. A unique character of these Lispe species is that the coeloconic sensilla are distributed sparsely on antennal postpedicel. Mechanoreceptors and basiconic sensilla are observed on the surface of maxillary palps in all three species. We demonstrated clear sexual dimorphism of the maxillary palps in some of the Lispe species, unlike most other Muscidae species, are larger in males than females. This, along with their courtship dance behaviour, suggest their function as both chemical signal receiver and visual signal conveyer, which is among the few records of a chemical reception organ act as a signal conveyer in insects.

Generation of fate patterns via intercellular forces

Studies of fate patterning during development typically emphasize cell-cell communication via diffusible signals. Recent experiments on monolayer stem cell colonies, however, suggest that mechanical forces between cells may also play a role. These findings inspire a model of mechanical patterning: fate affects cell contractility, and pressure in the cell layer biases fate. Cells at the colony boundary, more contractile than cells at the center, seed a pattern that propagates via force transmission. In agreement with previous observations, our model implies that the width of the outer fate domain depends only weakly on colony diameter. We further predict and confirm experimentally that this same width varies non-monotonically with substrate stiffness. This finding supports the idea that mechanical stress can mediate patterning in a manner similar to a morphogen; we argue that a similar dependence on substrate stiffness can be achieved by a chemical signal only if strong constraints on the signaling pathway's mechanobiology are met.

Symbiotic bacteria mediate volatile chemical signal synthesis in a large solitary mammal species

Mammalian chemosignals—or scent marks—are characterized by astounding chemical diversity, reflecting both complex biochemical pathways that produce them and rich information exchange with conspecifics. The microbiome of scent glands was thought to play prominent role in the chemical signal synthesis, with diverse microbiota metabolizing glandular products to produce odorants that may be used as chemosignals. Here, we use gas chromatography–mass spectrometry and metagenomic shotgun sequencing to explore this phenomenon in the anogenital gland secretions (AGS) of the giant panda (Ailuropoda melanoleuca). We find that this gland contains a diverse community of fermentative bacteria with enzymes that support metabolic pathways (e.g., lipid degradation) for the productions of volatile odorants specialized for chemical communication. We found quantitative and qualitative differences in the microbiota between AGS and digestive tract, a finding which was mirrored by differences among chemical compounds that could be used for olfactory communication. Volatile chemical compounds were more diverse and abundant in AGS than fecal samples, and our evidence suggests that metabolic pathways have been specialized for the synthesis of chemosignals for communication. The panda’s microbiome is rich with genes coding for enzymes that participate in the fermentation pathways producing chemical compounds commonly deployed in mammalian chemosignals. These findings illuminate the poorly understood phenomena involved in the role of symbiotic bacteria in the production of chemosignals.

A minimalist model for coevolving supply and drainage networks

Numerous complex systems, both natural and artificial, are characterized by the presence of intertwined supply and/or drainage networks. Here, we present a minimalist model of such coevolving networks in a spatially continuous domain, where the obtained networks can be interpreted as a part of either the counter-flowing drainage or co-flowing supply and drainage mechanisms. The model consists of three coupled, nonlinear partial differential equations that describe spatial density patterns of input and output materials by modifying a mediating scalar field, on which supply and drainage networks are carved. In the two-dimensional case, the scalar field can be viewed as the elevation of a hypothetical landscape, of which supply and drainage networks are ridges and valleys, respectively. In the three-dimensional case, the scalar field serves the role of a chemical signal, according to which vascularization of the supply and drainage networks occurs above a critical ‘erosion’ strength. The steady-state solutions are presented as a function of non-dimensional channelization indices for both materials. The spatial patterns of the emerging networks are classified within the branched and congested extreme regimes, within which the resulting networks are characterized based on the absolute as well as the relative values of two non-dimensional indices.

Recent Progress in Quantitatively Monitoring Vesicular Neurotransmitter Release and Storage With Micro/Nanoelectrodes

Exocytosis is one of the essential steps for chemical signal transmission between neurons. In this process, vesicles dock and fuse with the plasma membrane and release the stored neurotransmitters through fusion pores into the extracellular space, and all of these steps are governed with various molecules, such as proteins, ions, and even lipids. Quantitatively monitoring vesicular neurotransmitter release in exocytosis and initial neurotransmitter storage in individual vesicles is significant for the study of chemical signal transmission of the central nervous system (CNS) and neurological diseases. Electrochemistry with micro/nanoelectrodes exhibits great spatial–temporal resolution and high sensitivity. It can be used to examine the exocytotic kinetics from the aspect of neurotransmitters and quantify the neurotransmitter storage in individual vesicles. In this review, we first introduce the recent advances of single-cell amperometry (SCA) and the nanoscale interface between two immiscible electrolyte solutions (nanoITIES), which can monitor the quantity and release the kinetics of electrochemically and non-electrochemically active neurotransmitters, respectively. Then, the development and application of the vesicle impact electrochemical cytometry (VIEC) and intracellular vesicle impact electrochemical cytometry (IVIEC) and their combination with other advanced techniques can further explain the mechanism of neurotransmitter storage in vesicles before exocytosis. It has been proved that these electrochemical techniques have great potential in the field of neuroscience.

A kinetic chemotaxis model with internal states and temporal sensing

<p style='text-indent:20px;'>By employing the Fourier transform to derive key <i>a priori</i> estimates for the temporal gradient of the chemical signal, we establish the existence of global solutions and hydrodynamic limit of a chemotactic kinetic model with internal states and temporal gradient in one dimension, which is a system of two transport equations coupled to a parabolic equation proposed in [<xref ref-type="bibr" rid="b4">4</xref>].</p>

Neural network approach to data-driven estimation of chemotactic sensitivity in the Keller-Segel model

<abstract><p>We consider the mathematical model of chemotaxis introduced by Patlak, Keller, and Segel. Aggregation and progression waves are present everywhere in the population dynamics of chemotactic cells. Aggregation originates from the chemotaxis of mobile cells, where cells are attracted to migrate to higher concentrations of the chemical signal region produced by themselves. The neural net can be used to find the approximate solution of the PDE. We proved that the error, the difference between the actual value and the predicted value, is bound to a constant multiple of the loss we are learning. Also, the Neural Net approximation can be easily applied to the inverse problem. It was confirmed that even when the coefficient of the PDE equation was unknown, prediction with high accuracy was achieved.</p></abstract>

Strong intracellular signal inactivation produces sharper and more robust signaling from cell membrane to nucleus

For a chemical signal to propagate across a cell, it must navigate a tortuous environment involving a variety of organelle barriers. In this work we study mathematical models for a basic chemical signal, the arrival times at the nuclear membrane of proteins that are activated at the cell membrane and diffuse throughout the cytosol. Organelle surfaces within human B cells are reconstructed from soft X-ray tomographic images, and modeled as reflecting barriers to the molecules’ diffusion. We show that signal inactivation sharpens signals, reducing variability in the arrival time at the nuclear membrane. Inactivation can also compensate for an observed slowdown in signal propagation induced by the presence of organelle barriers, leading to arrival times at the nuclear membrane that are comparable to models in which the cytosol is treated as an open, empty region. In the limit of strong signal inactivation this is achieved by filtering out molecules that traverse non-geodesic paths.