On a dynamic reaction-diffusion mechanism: The spatial patterning of teeth primordia in the alligator

It is now well established both theoretically and, more recently, experimentally, that steady-state spatial chemical concentration patterns can be formed by a number of specific reaction–diffusion systems. Reaction–diffusion models have been widely applied to biological pattern formation problems. Here we propose a model mechanism for the initiation and spatial positioning of teeth primordia in the alligator, Alligator mississippiensis, which, from a reaction–diffusion theory, introduces, among other things, a new element, namely the effect of domain growth on dynamic spatial pattern formation. Detailed embryological studies by Westergaard and Ferguson (B. Westergaard and M. W. J. Ferguson, J. Zool. Lond., 1986, 210, 575; 1987, 212, 191; Am. J. Anatomy, 1990, 187, 393) show that jaw growth plays a crucial role in the developmental patterning of the tooth initiation process. Based on biological data we develop a reaction–diffusion mechanism, which crucially includes domain growth. The model can reproduce the spatial pattern development of the first seven teeth primordia in the lower half jaw of A. mississippiensis. The results for the precise spatio temporal sequence compare well with detailed developmental experiments

On a model mechanism for the spatial patterning of teeth primordia in the Alligator

We propose a model mechanism for the initiation and spatial positioning of teeth primordia in the alligator,Alligator mississippiensis. Detailed embryological studies by Westergaard & Ferguson (1986, 1987, 1990) show that jaw growth plays a crucial role in the developmental patterning of the tooth initiation process. Based on biological data we develop a reaction-diffusion mechanism, which crucially includes domain growth. The model can reproduce the spatial pattern development of the first seven teeth primordia in the lower half jaw ofA. mississippiensis. The results for the precise spatio-temporal sequence compare well with detailed developmental experiments

Title: will be set by the publisher Editors: will be set by the publisher EAS Publications Series, Vol.?, 2009 THE BEST SITE ON EARTH?

Abstract. We compare the merits of potential observatory sites on the Antarctic Plateau, in regard to the boundary layer, cloud cover, free atmosphere seeing, aurorae, airglow, and precipitable water vapour. We find that (a) all Antarctic sites are likely compromised for optical work by airglow and aurorae; (b) Dome A is the best existing site in almost all respects; (c) there is an even better site (‘Ridge A’) 150kms SW of Dome A; (d) Dome F is a remarkably good site except for aurorae; (e) Dome C probably has the least cloud cover of any of the sites, and might be able to use a predicted ‘OH hole ’ in the Spring. The Antarctic plateau probably contains the best astronomical sites on Earth, but none of the existing bases were situated with astronomy in mind. In Saunders et al.(2009), we use published data and models, and unpublished meteorological and other information, to try to compare the merits of the potential sites. Here, we summarise only the new findings and conclusions. We include boundary layer thickness, cloud cover, auroral emission, airglow, precipitable water vapour, an

Fast fluorescence microscopy for imaging the dynamics of embryonic development

Live imaging has gained a pivotal role in developmental biology since it increasingly allows real-time observation of cell behavior in intact organisms. Microscopes that can capture the dynamics of ever-faster biological events, fluorescent markers optimal for in vivo imaging, and, finally, adapted reconstruction and analysis programs to complete data flow all contribute to this success. Focusing on temporal resolution, we discuss how fast imaging can be achieved with minimal prejudice to spatial resolution, photon count, or to reliably and automatically analyze images. In particular, we show how integrated approaches to imaging that combine bright fluorescent probes, fast microscopes, and custom post-processing techniques can address the kinetics of biological systems at multiple scales. Finally, we discuss remaining challenges and opportunities for further advances in this field

Computational modelling of cell chain migration reveals mechanisms that sustain follow-the-leader behaviour

Follow-the-leader chain migration is a striking cell migratory behaviour observed during vertebrate development, adult neurogenesis and cancer metastasis. Although cell–cell contact and extracellular matrix (ECM) cues have been proposed to promote this phenomenon, mechanisms that underlie chain migration persistence remain unclear. Here, we developed a quantitative agent-based modelling framework to test mechanistic hypotheses of chain migration persistence. We defined chain migration and its persistence based on evidence from the highly migratory neural crest model system, where cells within a chain extend and retract filopodia in short-lived cell contacts and move together as a collective. In our agent-based simulations, we began with a set of agents arranged as a chain and systematically probed the influence of model parameters to identify factors critical to the maintenance of the chain migration pattern. We discovered that chain migration persistence requires a high degree of directional bias in both lead and follower cells towards the target. Chain migration persistence was also promoted when lead cells maintained cell contact with followers, but not vice-versa. Finally, providing a path of least resistance in the ECM was not sufficient alone to drive chain persistence. Our results indicate that chain migration persistence depends on the interplay of directional cell movement and biased cell–cell contact

VEGF signals induce trailblazer cell identity that drives neural crest migration

Embryonic neural crest cells travel in discrete streams to precise locations throughout the head and body. We previously showed that cranial neural crest cells respond chemotactically to vascular endothelial growth factor (VEGF) and that cells within the migratory front have distinct behaviors and gene expression. We proposed a cell-induced gradient model in which lead neural crest cells read out directional information from a chemoattractant profile and instruct trailers to follow. In this study, we show that migrating chick neural crest cells do not display distinct lead and trailer gene expression profiles in culture. However, exposure to VEGF in vitro results in the upregulation of a small subset of genes associated with an in vivo lead cell signature. Timed addition and removal of VEGF in culture reveals the changes in neural crest cell gene expression are rapid. A computational model incorporating an integrate-and-switch mechanism between cellular phenotypes predicts migration efficiency is influenced by the timescale of cell behavior switching. To test the model hypothesis that neural crest cellular phenotypes respond to changes in the VEGF chemoattractant profile, we presented ectopic sources of VEGF to the trailer neural crest cell subpopulation and show diverted cell trajectories and stream alterations consistent with model predictions. Gene profiling of trailer cells that diverted and encountered VEGF revealed upregulation of a subset of ‘lead’ genes. Injection of neuropilin1 (Np1)-Fc into the trailer subpopulation or electroporation of VEGF morpholino to reduce VEGF signaling failed to alter trailer neural crest cell trajectories, suggesting trailers do not require VEGF to maintain coordinated migration. These results indicate that VEGF is one of the signals that establishes lead cell identity and its chemoattractant profile is critical to neural crest cell migration

Modelling the spatial patterning of the primordia in the lower jaw of alligator mississippiensis

We propose a model mechanism for the initiation and spatial positioning of teeth primordia in the alligator, Alligator mississippiensis. Detailed embryological studies12–14 have shown that jaw growth plays a crucial role in the developmental patterning of the tooth initiation process. The development of the spatial pattern occurs on a timescale comparable to jaw growth. Based on biological data we develop a dynamic patterning mechanism, which crucially includes domain growth. The mechanism can reproduce the spatial pattern development of the first seven teeth primordia in the lower jaw of A. mississippiensis. The results for the precise spatio-temporal sequence compare well with experiment

Aberrant behaviours of reaction diffusion self-organisation models on growing domains in the presence of gene expression time delays

Turing’s pattern formation mechanism exhibits sensitivity to the details of the initial conditions suggesting that, in isolation, it cannot robustly generate pattern within noisy biological environments. Nonetheless, secondary aspects of developmental self-organisation, such as a growing domain, have been shown to ameliorate this aberrant model behaviour. Furthermore, while in-situ hybridisation reveals the presence of gene expression in developmental processes, the influence of such dynamics on Turing’s model has received limited attention. Here, we novelly focus on the Gierer–Meinhardt reaction diffusion system considering delays due the time taken for gene expression, while incorporating a number of different domain growth profiles to further explore the influence and interplay of domain growth and gene expression on Turing’s mechanism. We find extensive pathological model behaviour, exhibiting one or more of the following: temporal oscillations with no spatial structure, a failure of the Turing instability and an extreme sensitivity to the initial conditions, the growth profile and the duration of gene expression. This deviant behaviour is even more severe than observed in previous studies of Schnakenberg kinetics on exponentially growing domains in the presence of gene expression (Gaffney and Monk in Bull. Math. Biol. 68:99–130, 2006). Our results emphasise that gene expression dynamics induce unrealistic behaviour in Turing’s model for multiple choices of kinetics and thus such aberrant modelling predictions are likely to be generic. They also highlight that domain growth can no longer ameliorate the excessive sensitivity of Turing’s mechanism in the presence of gene expression time delays. The above, extensive, pathologies suggest that, in the presence of gene expression, Turing’s mechanism would generally require a novel and extensive secondary mechanism to control reaction diffusion patterning

Large format heterodyne arrays for observing far-infrared lines with SOFIA

In the wavelength regime between 60 and 300 microns there are a number of atomic and molecular emission lines that are key diagnostic probes of the interstellar medium. These include transitions of [CII], [NII], [OI], HD, H_2D^+, OH, CO, and H_2O, some of which are among the brightest global and local far-infrared lines in the Galaxy. In Giant Molecular Clouds (GMCs), evolved star envelopes, and planetary nebulae, these emission lines can be extended over many arc minutes and possess complicated, often self absorbed, line profiles. High spectral resolution (R > 10^5) observations of these lines at sub-arcminute angular resolution are crucial to understanding the complicated interplay between the interstellar medium and the stars that form from it. This feedback is central to all theories of galactic evolution. Large format heterodyne array receivers can provide the spectral resolution and spatial coverage to probe these lines over extended regions. The advent of large format (~100 pixel) spectroscopic imaging cameras in the far-infrared (FIR) will fundamentally change the way astronomy is performed in this important wavelength regime. While the possibility of such instruments has been discussed for more than two decades, only recently have advances in mixer and local oscillator technology, device fabrication, micromachining, and digital signal processing made the construction of such instruments tractable. These technologies can be implemented to construct a sensitive, flexible, heterodyne array facility instrument for SOFIA. The instrument concept for StratoSTAR: Stratospheric Submm/THz Array Receiver includes a common user mounting, control system, IF processor, spectrometer, and cryogenic system. The cryogenic system will be designed to accept a frontend insert. The frontend insert and associated local oscillator system/relay optics would be provided by individual user groups and reflect their scientific interests. Rapid technology development in this field makes SOFIA the ideal platform to operate such a modular, continuously evolving instrument

Multi-Cellular Logistics of Collective Cell Migration

During development, the formation of biological networks (such as organs and neuronal networks) is controlled by multicellular transportation phenomena based on cell migration. In multi-cellular systems, cellular locomotion is restricted by physical interactions with other cells in a crowded space, similar to passengers pushing others out of their way on a packed train. The motion of individual cells is intrinsically stochastic and may be viewed as a type of random walk. However, this walk takes place in a noisy environment because the cell interacts with its randomly moving neighbors. Despite this randomness and complexity, development is highly orchestrated and precisely regulated, following genetic (and even epigenetic) blueprints. Although individual cell migration has long been studied, the manner in which stochasticity affects multi-cellular transportation within the precisely controlled process of development remains largely unknown. To explore the general principles underlying multicellular migration, we focus on the migration of neural crest cells, which migrate collectively and form streams. We introduce a mechanical model of multi-cellular migration. Simulations based on the model show that the migration mode depends on the relative strengths of the noise from migratory and non-migratory cells. Strong noise from migratory cells and weak noise from surrounding cells causes “collective migration,” whereas strong noise from non-migratory cells causes “dispersive migration.” Moreover, our theoretical analyses reveal that migratory cells attract each other over long distances, even without direct mechanical contacts. This effective interaction depends on the stochasticity of the migratory and non-migratory cells. On the basis of these findings, we propose that stochastic behavior at the single-cell level works effectively and precisely to achieve collective migration in multi-cellular systems