scholarly journals Dynamic morphoskeletons in development

2019 ◽  
Author(s):  
Mattia Serra ◽  
Sebastian Streichan ◽  
L. Mahadevan
Keyword(s):  
Developmental Biology ◽  
Chicken Embryo ◽  
Measurement Errors ◽  
Primitive Streak ◽  
Velocity Data ◽  
Coordinated Motion ◽  
Geometric Framework ◽  
Tissue Organization ◽  
Cell Velocity ◽  
Eulerian Methods

Morphogenetic flows in developmental biology are characterized by the coordinated motion of thousands of cells that organize into tissues, naturally raising the question of how this collective organization arises. Using only the Lagrangian kinematics of tissue deformation, which naturally integrates local and global mechanisms along cell paths, we can identifying the Dynamic Morphoskeletons (DM) behind morphogenesis, i.e., the evolving centerpieces of multi-cellular trajectory patterns. The DM is model and parameter-free, frame-invariant, robust to measurement errors, and can be computed from unfiltered cell velocity data. It reveals the spatial attractors and repellers of the embryo, objects that cannot be identified by simple trajectory inspection or Eulerian methods that are local and typically frame-dependent. Computing the DM underlying primitive streak formation in chicken embryo and early gastrulation in the whole fly embryo, we find that the DM captures the early footprint of known morphogenetic features, and reveals new ones, providing a geometric framework to analyze tissue organization.

scholarly journals Dynamic morphoskeletons in development

2020 ◽  
Vol 117 (21) ◽  
pp. 11444-11449 ◽  
Author(s):  
Mattia Serra ◽  
Sebastian Streichan ◽  
Manli Chuai ◽  
Cornelis J. Weijer ◽  
L. Mahadevan
Keyword(s):  
Developmental Biology ◽  
Measurement Errors ◽  
Tissue Deformation ◽  
Velocity Data ◽  
Wild Type ◽  
Coordinated Motion ◽  
Cell Velocity ◽  
Eulerian Methods

Morphogenetic flows in developmental biology are characterized by the coordinated motion of thousands of cells that organize into tissues, naturally raising the question of how this collective organization arises. Using only the kinematics of tissue deformation, which naturally integrates local and global mechanisms along cell paths, we identify the dynamic morphoskeletons behind morphogenesis, i.e., the evolving centerpieces of multicellular trajectory patterns. These features are model- and parameter-free, frame-invariant, and robust to measurement errors and can be computed from unfiltered cell-velocity data. We reveal the spatial attractors and repellers of the embryo by quantifying its Lagrangian deformation, information that is inaccessible to simple trajectory inspection or Eulerian methods that are local and typically frame-dependent. Computing these dynamic morphoskeletons in wild-type and mutant chick and fly embryos, we find that they capture the early footprint of known morphogenetic features, reveal new ones, and quantitatively distinguish between different phenotypes.

scholarly journals Engineering life in synthetic systems

Development ◽  
2021 ◽  
Vol 148 (14) ◽  
Author(s):  
David Oriola ◽  
Francesca M. Spagnoli
Keyword(s):  
Developmental Biology ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Tissue Architecture ◽  
Gene Circuits ◽  
Tissue Organization ◽  
The World ◽  
Gene Regulatory ◽  
Synthetic Approaches ◽  
Evolutionary And Developmental Biology

ABSTRACT The second EMBO-EMBL Symposium ‘Synthetic Morphogenesis: From Gene Circuits to Tissue Architecture’ was held virtually in March 2021, with participants from all over the world joining from the comfort of their sofas to discuss synthetic morphogenesis at large. Leading scientists from a range of disciplines, including developmental biology, physics, chemistry and computer science, covered a gamut of topics from the principles of cell and tissue organization, patterning and gene regulatory networks, to synthetic approaches for exploring evolutionary and developmental biology principles. Here, we describe some of the high points.

scholarly journals Dynamics of primitive streak regression controls the fate of neuro-mesodermal progenitors in the chicken embryo

2020 ◽  
Author(s):  
Charlene Guillot ◽  
Arthur Michaut ◽  
Brian Rabe ◽  
Olivier Pourquié
Keyword(s):  
Chicken Embryo ◽  
Single Cells ◽  
Primitive Streak ◽  
Clonal Analysis ◽  
Lineage Tracing ◽  
The Body ◽  
Paraxial Mesoderm ◽  
Axis Formation ◽  
Vertebrate Development ◽  
Tail Bud

AbstractIn classical descriptions of vertebrate development, the segregation of the three embryonic germ layers is completed by the end of gastrulation. Body formation then proceeds in a head to tail fashion by progressive deposition of lineage committed progenitors during regression of the Primitive Streak (PS) and tail bud (Pasteels, 1937b; Stern, 2004). Identification of Neuro-Mesodermal Progenitors (NMPs) contributing to both musculo-skeletal precursors (paraxial mesoderm) and spinal cord during axis formation by retrospective clonal analysis challenged these notions (Henrique et al., 2015; Tzouanacou et al., 2009). However, in amniotes such as mouse and chicken, the precise identity and localization of these cells has remained unclear despite a wealth of fate mapping analyses of the PS region. Here, we use lineage tracing in the chicken embryo to show that single cells located in the SOX2/T positive anterior PS region contribute to both neural and mesodermal lineages in the trunk and tail, but only express this bipotential fate with some delay. We demonstrate that posterior to anterior gradients of convergence speed and ingression along the PS gradually lead to exhaustion of all mesodermal precursor territories except for NMPs where limited ingression and increased proliferation maintain and amplify this pool of axial progenitors. As a result, most of the remaining mesodermal precursors from the PS in the tail bud are bipotential NMPs. Together, our results provide a novel understanding of the contribution of the PS and tail bud to the formation of the body of amniote embryos.

scholarly journals Dynamics of primitive streak regression controls the fate of neuromesodermal progenitors in the chicken embryo

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Charlene Guillot ◽  
Yannis Djeffal ◽  
Arthur Michaut ◽  
Brian Rabe ◽  
Olivier Pourquié
Keyword(s):  
Single Cell ◽  
Cell Population ◽  
Chicken Embryo ◽  
Primitive Streak ◽  
Lineage Tracing ◽  
The Body ◽  
Paraxial Mesoderm ◽  
Axis Formation ◽  
Tail Bud ◽  
Transcriptomic Signature

In classical descriptions of vertebrate development, the segregation of the three embryonic germ layers completes by the end of gastrulation. Body formation then proceeds in a head to tail fashion by progressive deposition of lineage-committed progenitors during regression of the primitive streak (PS) and tail bud (TB). The identification by retrospective clonal analysis of a population of neuromesodermal progenitors (NMPs) contributing to both musculoskeletal precursors (paraxial mesoderm) and spinal cord during axis formation challenged these notions. However, classical fate mapping studies of the PS region in amniotes have so far failed to provide direct evidence for such bipotential cells at the single-cell level. Here, using lineage tracing and single-cell RNA sequencing in the chicken embryo, we identify a resident cell population of the anterior PS epiblast, which contributes to neural and mesodermal lineages in trunk and tail. These cells initially behave as monopotent progenitors as classically described and only acquire a bipotential fate later, in more posterior regions. We show that NMPs exhibit a conserved transcriptomic signature during axis elongation but lose their epithelial characteristicsin the TB. Posterior to anterior gradients of convergence speed and ingression along the PS lead to asymmetric exhaustion of PS mesodermal precursor territories. Through limited ingression and increased proliferation, NMPs are maintained and amplified as a cell population which constitute the main progenitors in the TB. Together, our studies provide a novel understanding of the PS and TB contribution through the NMPs to the formation of the body of amniote embryos.

Cytoplasmic Tubules in Cells Infected with Laryngotracheitis Virus

1969 ◽  
Vol 27 ◽  
pp. 376-377
Author(s):  
A. M. Watrach
Keyword(s):  
Tissue Culture ◽  
Small Proportion ◽  
Chicken Embryo ◽  
Culture Cells ◽  
Tissue Culture Cells ◽  
Morphologic Characteristics ◽  
Infectious Laryngotracheitis ◽  
Laryngotracheitis Virus ◽  
In Cells

During a study of the development of infectious laryngotracheitis (LT) virus in tissue culture cells, unusual tubular formations were found in the cytoplasm of a small proportion of the affected cells. It is the purpose of this report to describe the morphologic characteristics of the tubules and to discuss their possible association with the development of virus.The source and maintenance of the strain of LT virus have been described. Prior to this study, the virus was passed several times in chicken embryo kidney (CEK) tissue culture cells.

The 1-MeV Electron Microscope Installation at the University of Colorado

1973 ◽  
Vol 31 ◽  
pp. 8-9 ◽  
Author(s):  
Mircea Fotino
Keyword(s):  
Electron Microscopy ◽  
Developmental Biology ◽  
Transmission Electron Microscopy ◽  
Electron Microscope ◽  
National Institutes Of Health ◽  
Experimental Program ◽  
University Of Colorado ◽  
Transmission Electron ◽  
The University ◽  
Research Resources

A new 1-MeV transmission electron microscope (Model JEM-1000) was installed at the Department of Molecular, Cellular and Developmental Biology of the University of Colorado in Boulder during the summer and fall of 1972 under the sponsorship of the Division of Research Resources of the National Institutes of Health. The installation was completed in October, 1972. It is installed primarily for the study of biological materials without many of the limitations hitherto unavoidable in standard transmission electron microscopy. Only the technical characteristics of the installation are briefly reviewed here. A more detailed discussion of the experimental program under way is being published elsewhere.

Going Beyond 3-D Imaging: Automated 3-D Montaged image Analysis of Cytological Specimens

1996 ◽  
Vol 54 ◽  
pp. 282-283
Author(s):  
Badrinath Roysam ◽  
Hakan Ancin ◽  
Douglas E. Becker ◽  
Robert W. Mackin ◽  
Matthew M. Chestnut ◽  
...  
Keyword(s):  
Image Analysis ◽  
Structural Changes ◽  
Sampling Methods ◽  
Spatial Clustering ◽  
Three Dimensional ◽  
Field Of View ◽  
Cell Counting ◽  
Depth Of Field ◽  
Tissue Cell ◽  
Tissue Organization

This paper summarizes recent advances made by this group in the automated three-dimensional (3-D) image analysis of cytological specimens that are much thicker than the depth of field, and much wider than the field of view of the microscope. The imaging of thick samples is motivated by the need to sample large volumes of tissue rapidly, make more accurate measurements than possible with 2-D sampling, and also to perform analysis in a manner that preserves the relative locations and 3-D structures of the cells. The motivation to study specimens much wider than the field of view arises when measurements and insights at the tissue, rather than the cell level are needed.The term “analysis” indicates a activities ranging from cell counting, neuron tracing, cell morphometry, measurement of tracers, through characterization of large populations of cells with regard to higher-level tissue organization by detecting patterns such as 3-D spatial clustering, the presence of subpopulations, and their relationships to each other. Of even more interest are changes in these parameters as a function of development, and as a reaction to external stimuli. There is a widespread need to measure structural changes in tissue caused by toxins, physiologic states, biochemicals, aging, development, and electrochemical or physical stimuli. These agents could affect the number of cells per unit volume of tissue, cell volume and shape, and cause structural changes in individual cells, inter-connections, or subtle changes in higher-level tissue architecture. It is important to process large intact volumes of tissue to achieve adequate sampling and sensitivity to subtle changes. It is desirable to perform such studies rapidly, with utmost automation, and at minimal cost. Automated 3-D image analysis methods offer unique advantages and opportunities, without making simplifying assumptions of tissue uniformity, unlike random sampling methods such as stereology.12 Although stereological methods are known to be statistically unbiased, they may not be statistically efficient. Another disadvantage of sampling methods is the lack of full visual confirmation - an attractive feature of image analysis based methods.

Precise on-line Measurement of Lattice Vectors

1990 ◽  
Vol 48 (1) ◽  
pp. 530-531
Author(s):  
W.J. de Ruijter ◽  
Sharma Renu
Keyword(s):  
Electron Microscope ◽  
Measurement Errors ◽  
Dynamic Range ◽  
Structural Information ◽  
Statistical Parameter ◽  
Systematic Errors ◽  
Geometric Distortion ◽  
Crystal Silicon ◽  
Camera System ◽  
On Line

Established methods for measurement of lattice spacings and angles of crystalline materials include x-ray diffraction, microdiffraction and HREM imaging. Structural information from HREM images is normally obtained off-line with the traveling table microscope or by the optical diffractogram technique. We present a new method for precise measurement of lattice vectors from HREM images using an on-line computer connected to the electron microscope. It has already been established that an image of crystalline material can be represented by a finite number of sinusoids. The amplitude and the phase of these sinusoids are affected by the microscope transfer characteristics, which are strongly influenced by the settings of defocus, astigmatism and beam alignment. However, the frequency of each sinusoid is solely a function of overall magnification and periodicities present in the specimen. After proper calibration of the overall magnification, lattice vectors can be measured unambiguously from HREM images.Measurement of lattice vectors is a statistical parameter estimation problem which is similar to amplitude, phase and frequency estimation of sinusoids in 1-dimensional signals as encountered, for example, in radar, sonar and telecommunications. It is important to properly model the observations, the systematic errors and the non-systematic errors. The observations are modelled as a sum of (2-dimensional) sinusoids. In the present study the components of the frequency vector of the sinusoids are the only parameters of interest. Non-systematic errors in recorded electron images are described as white Gaussian noise. The most important systematic error is geometric distortion. Lattice vectors are measured using a two step procedure. First a coarse search is obtained using a Fast Fourier Transform on an image section of interest. Prior to Fourier transformation the image section is multiplied with a window, which gradually falls off to zero at the edges. The user indicates interactively the periodicities of interest by selecting spots in the digital diffractogram. A fine search for each selected frequency is implemented using a bilinear interpolation, which is dependent on the window function. It is possible to refine the estimation even further using a non-linear least squares estimation. The first two steps provide the proper starting values for the numerical minimization (e.g. Gauss-Newton). This third step increases the precision with 30% to the highest theoretically attainable (Cramer and Rao Lower Bound). In the present studies we use a Gatan 622 TV camera attached to the JEM 4000EX electron microscope. Image analysis is implemented on a Micro VAX II computer equipped with a powerful array processor and real time image processing hardware. The typical precision, as defined by the standard deviation of the distribution of measurement errors, is found to be <0.003Å measured on single crystal silicon and <0.02Å measured on small (10-30Å) specimen areas. These values are ×10 times larger than predicted by theory. Furthermore, the measured precision is observed to be independent on signal-to-noise ratio (determined by the number of averaged TV frames). Obviously, the precision is restricted by geometric distortion mainly caused by the TV camera. For this reason, we are replacing the Gatan 622 TV camera with a modern high-grade CCD-based camera system. Such a system not only has negligible geometric distortion, but also high dynamic range (>10,000) and high resolution (1024x1024 pixels). The geometric distortion of the projector lenses can be measured, and corrected through re-sampling of the digitized image.

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