scholarly journals Unraveling the embryonic fate map through the mechanical signature of cells and their trajectories

2021 ◽  
Author(s):  
David Pastor-Escuredo ◽  
Benoit Lombardot ◽  
Thierry Savy ◽  
Adeline Adeline Boyreau ◽  
Rene Doursat ◽  
...  
Keyword(s):  
Deformation Rate ◽  
Phenotypic Variability ◽  
Early Developmental Stage ◽  
Embryonic Cells ◽  
Imaging Data ◽  
Fate Map ◽  
Cell Lineages ◽  
Multi Scale ◽  
Mesoscopic Level ◽  
Cumulative Deformation

Abstract Digital cell lineages reconstructed from 3D+time imaging data of the developing zebrafish embryo are used to uncover mechanical cues and their role in morphogenesis. A continuous approximation of cell displacements obtained from cell lineages is used to assess tissue deformation during gastrulation. At this stage, embryonic tissues display multi-scale compressible fluid-like properties. The deformation rate at the mesoscopic level of the cell’s immediate surroundings appears noisy, in both space and time. The patterns identified by clustering the cells, according to the cumulative deformation rate along their trajectory throughout gastrulation, lead to a robust, ordered and coherent biomechanical map. The timing and amplitude of the biomechanical deformations provide a measurement of the phenotypic variability in small cohorts of specimens. We show that the biomechanical map matches the embryonic fate map of the zebrafish presumptive forebrain, in both wild type and Nodal pathway mutants (zoeptz57/tz57), where it reveals the biomechanical defects that lead to cyclopia.. The comparison of biomechanical patterns and the expression pattern of a transgenic reporter for the transcription factor goosecoid (gsc), supports the hypothesis that embryonic cells acquire, at an early developmental stage, a biomechanical signature that contributes to defining their fate.

scholarly journals Kinematic analysis of cell lineage reveals coherent and robust mechanical deformation patterns in zebrafish gastrulation

2016 ◽  
Author(s):  
David Pastor-Escuredo ◽  
Benoît Lombardot ◽  
Thierry Savy ◽  
Adeline Boyreau ◽  
Jose M. Goicolea ◽  
...  
Keyword(s):  
Kinematic Analysis ◽  
Cell Lineage ◽  
Unsupervised Classification ◽  
Mechanical Deformation ◽  
Imaging Data ◽  
Fate Map ◽  
New Type ◽  
Mesoscopic Level ◽  
Deformation Patterns ◽  
Cell Trajectories

AbstractDigital cell lineages reconstructed from 3D+time imaging data provide unique information to unveil mechanical cues and their role in morphogenetic processes. Our methodology based on a kinematic analysis of cell lineage data reveals deformation patterns and quantitative morphogenetic landmarks for a new type of developmental table. The characteristic spatial and temporal length scales of mechanical deformation patterns derived from a continuous approximation of cell displacements indicate a compressible fluid-like behavior of zebrafish gastrulating tissues. The instantaneous deformation rate at the mesoscopic level of the cell’s neighborhood is spatially and temporally heterogeneous. The robustness of mechanical patterns results from their cumulative history along cell trajectories. Unsupervised classification of mechanical descriptor profiles was used to assess the homogeneity of biomechanical cues in cell populations. Further clustering of cell trajectories according to their cumulative mesoscopic biomechanical history during gastrulation revealed ordered and coherent spatiotemporal patterns comparable to that of the embryonic fate map.

Cell movements and cell fate during zebrafish gastrulation

Development ◽  
1992 ◽  
Vol 116 (Supplement) ◽  
pp. 65-73 ◽  
Author(s):  
Robert K. Ho
Keyword(s):  
Single Cell ◽  
Cell Fate ◽  
Fate Map ◽  
Cell Fates ◽  
Cell Lineages ◽  
Cell Position ◽  
Vertebrate Embryo ◽  
Cellular Identity ◽  
Transplantation Experiments

The early lineages of the zebrafish are indeterminate and a single cell labeled before the late blastula period will contribute progeny to a variety of tissues. Therefore, early cell lineages in the zebrafish do not establish future cell fates and early blastomeres must necessarily remain pluripotent. Eventually, after a period of random cell mixing, individual cells do become tissue restricted according to their later position within the blastoderm. The elucidation of a fate map for the zebrafish gastrula (Kimmel et al., 1990), has made it possible to study the processes by which cellular identity is conferred and maintained in the zebrafish. In this chapter, I describe single cell transplantation experiments designed to test for the irreversible restriction or ‘commitment’ of embryonic blastomeres in the zebrafish embryo. These experiments support the hypothesis that cell fate in the vertebrate embryo is determined by cell position. Work on the spadetail mutation will also be reviewed; this mutation causes a subset of mesodermal precursors to mismigrate during gastrulation thereby leading to a change in their eventual cell identity.

Current approaches to fate mapping and lineage tracing using image data

Development ◽  
2021 ◽  
Vol 148 (18) ◽  
Author(s):  
Steffen Wolf ◽  
Yinan Wan ◽  
Katie McDole
Keyword(s):  
Developmental Biology ◽  
Light Microscopy ◽  
Cell Tracking ◽  
Image Data ◽  
Lineage Tracing ◽  
Imaging Data ◽  
Cell Lineages ◽  
Ongoing Effort ◽  
Complex Image ◽  
Software Methodologies

ABSTRACT Visualizing, tracking and reconstructing cell lineages in developing embryos has been an ongoing effort for well over a century. Recent advances in light microscopy, labelling strategies and computational methods to analyse complex image datasets have enabled detailed investigations into the fates of cells. Combined with powerful new advances in genomics and single-cell transcriptomics, the field of developmental biology is able to describe the formation of the embryo like never before. In this Review, we discuss some of the different strategies and applications to lineage tracing in live-imaging data and outline software methodologies that can be applied to various cell-tracking challenges.

Origin and organization of the zebrafish fate map

Development ◽  
1990 ◽  
Vol 108 (4) ◽  
pp. 581-594 ◽  
Author(s):  
C.B. Kimmel ◽  
R.M. Warga ◽  
T.F. Schilling
Keyword(s):  
Deep Layer ◽  
Cell Types ◽  
Fate Map ◽  
Animal Pole ◽  
Amphibian Embryo ◽  
Yolk Cell ◽  
Cell Lineages ◽  
Embryonic Tissues ◽  
Dorsal Cells ◽  
Early Gastrula

We have analyzed lineages of cells labeled by intracellular injection of tracer dye during early zebrafish development to learn when cells become allocated to particular fates during development, and how the fate map is organized. The earliest lineage restriction was described previously, and segregates the yolk cell from the blastoderm in the midblastula. After one or two more cell divisions, the lineages of epithelial enveloping layer (EVL) cells become restricted to generate exclusively periderm. Following an additional division in the late blastula, deep layer (DEL) cells generate clones that are restricted to single deep embryonic tissues. The appearance of both the EVL and DEL restrictions could be causally linked to blastoderm morphogenesis during epiboly. A fate map emerges as the DEL cell lineages become restricted in the late blastula. It is similar in organization to that of an amphibian embryo. DEL cells located near the animal pole of the early gastrula give rise to ectodermal fates (including the definitive epidermis). Cells located near the blastoderm margin give rise to mesodermal and endodermal fates. Dorsal cells in the gastrula form dorsal and anterior structures in the embryo, and ventral cells in the gastrula form dorsal, ventral and posterior structures. The exact locations of progenitors of single cell types and of local regions of the embryo cannot be mapped at the stages we examined, because of variable cell rearrangements during gastrulation.

The role of cell lineage in development

1985 ◽  
Vol 312 (1153) ◽  
pp. 3-19 ◽  
Keyword(s):  
Cell Fate ◽  
Cell Lineage ◽  
Early Embryo ◽  
Embryonic Cell ◽  
Evolutionary Divergence ◽  
Causative Role ◽  
Embryonic Cells ◽  
Developmental Potential ◽  
Cell Lineages

Studies of the role of cell lineage in development began in the latter part of the 19th century, fell into decline in the early part of the 20th, and were revived about 20 years ago. This recent revival was accompanied by the introduction of new and powerful analytical techniques. Concepts of importance for cell lineage studies include the principal division modes by which a cell may give rise to its descendant clone (proliferative, stem cell and diversifying); developmental determinacy , or indeterminacy , which refer to the degree to which the normal cleavage pattern of the early embryo and the developmental fate of its individual cells is, or is not, the same in specimen after specimen; commitment , which refers to the restriction of the developmental potential of a pluripotent embryonic cell; and equivalence group , which refers to two or more equivalently pluripotent cell clones that normally take on different fates but of which under abnormal conditions one clone can take on the fate of another. Cell lineage can be inferred to have a causative role in developmental cell fate in embryos in which induced changes in cell division patterns lead to changes in cell fate. Moreover, such a causative role of cell lineage is suggested by cases where homologous cell types characteristic of a symmetrical and longitudinally metameric body plan arise via homologous cell lineages. The developmental pathways of commitment to particular cell fates proceed according to a mixed typologic and topographic hierarchy, which appears to reflect an evolutionary compromise between maximizing the ease of ordering the spatial distribution of the determinants of commitment and minimizing the need for migration of differentially committed embryonic cells. Comparison of the developmental cell lineages in leeches and insects indicates that the early course of embryogenesis is radically different in these phyletically related taxa. This evolutionary divergence of the course of early embryogenesis appears to be attributable to an increasing prevalence of polyclonal rather than monoclonal commitment in the phylogenetic line leading from an annelid-like ancestor to insects.

Embryonic origin of the Arabidopsis primary root and root meristem initials

Development ◽  
1994 ◽  
Vol 120 (9) ◽  
pp. 2475-2487 ◽  
Author(s):  
B. Scheres ◽  
H. Wolkenfelt ◽  
V. Willemsen ◽  
M. Terlouw ◽  
E. Lawson ◽  
...  
Keyword(s):  
Root Meristem ◽  
Marker Gene ◽  
Primary Root ◽  
Cortical Cell ◽  
Fate Map ◽  
Cell Region ◽  
End Points ◽  
Histological Techniques ◽  
Cell Lineages ◽  
Embryonic Origin

The embryonic origin of the Arabidopsis root and hypocotyl region has been investigated using histological techniques and clonal analysis. Our data reveal the pattern of cell division in the embryo giving rise to the various initials within the root promeristem. A small region of the root at its connection with the hypocotyl appears not to be derived from the promeristem initials. This region contains two cortical cell layer and [3H]thymidine incorporation data suggest that it lacks postembryonic cell divisions. Sectors marked by transposon excision from the beta-glucuronidase marker gene are used to investigate cell lineages giving rise to root and hypocotyl. The position of end points from sectors with embryonic origin show little variation and hence reveal preferred positions in the seedling for cells derived from different regions of the embryo. The radial extent of complete root sectors is consistent with the radial arrangement of root meristem initials at the heart stage of embryogenesis inferred from histological analysis. Using the clonal data, a fate map is constructed depicting the destiny of heart stage embryonic cell tiers, in the seedling root and hypocotyl. The variability in the sector end points indicates that distinct cell lineages are not restricted for root or hypocotyl fate. In contrast, derivatives of the hypophyseal cell do appear to be restricted to the columella and central cell region of the root.

scholarly journals Multi-Scale Microfluidics for Transport in Shale Fabric

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 21
Author(s):  
Bowen Ling ◽  
Hasan J. Khan ◽  
Jennifer L. Druhan ◽  
Ilenia Battiato
Keyword(s):  
Spatial Scales ◽  
Fracture Network ◽  
Breakthrough Curves ◽  
Fracture Aperture ◽  
Imaging Data ◽  
Fracture Networks ◽  
Multi Scale ◽  
Microfluidic Flow ◽  
Scaling Relationship ◽  
Fracture Apertures

We develop a microfluidic experimental platform to study solute transport in multi-scale fracture networks with a disparity of spatial scales ranging between two and five orders of magnitude. Using the experimental scaling relationship observed in Marcellus shales between fracture aperture and frequency, the microfluidic design of the fracture network spans all length scales from the micron (1 μ) to the dm (10 dm). This intentional `tyranny of scales’ in the design, a determining feature of shale fabric, introduces unique complexities during microchip fabrication, microfluidic flow-through experiments, imaging, data acquisition and interpretation. Here, we establish best practices to achieve a reliable experimental protocol, critical for reproducible studies involving multi-scale physical micromodels spanning from the Darcy- to the pore-scale (dm to μm). With this protocol, two fracture networks are created: a macrofracture network with fracture apertures between 5 and 500 μm and a microfracture network with fracture apertures between 1 and 500 μm. The latter includes the addition of 1 μm ‘microfractures’, at a bearing of 55°, to the backbone of the former. Comparative analysis of the breakthrough curves measured at corresponding locations along primary, secondary and tertiary fractures in both models allows one to assess the scale and the conditions at which microfractures may impact passive transport.

scholarly journals Multi-scale semi-supervised clustering of brain images: deriving disease subtypes

2021 ◽  
Author(s):  
Junhao WEN ◽  
Erdem Varol ◽  
Aristeidis Sotiras ◽  
Zhijian Yang ◽  
Ganesh B. Chand ◽  
...  
Keyword(s):  
Control Sample ◽  
Optimization Procedure ◽  
Brain Diseases ◽  
Imaging Data ◽  
Clustering Methods ◽  
Disease Heterogeneity ◽  
Supervised Clustering ◽  
Multi Scale ◽  
Clustering Model ◽  
Disease Subtypes

Disease heterogeneity is a significant obstacle to understanding pathological processes and delivering precision diagnostics and treatment. Clustering methods have gained popularity in stratifying patients into subpopulations (i.e., subtypes) of brain diseases using imaging data. However, unsupervised clustering approaches are often confounded by anatomical and functional variations not related to a disease or pathology of interest. Semi-supervised clustering techniques have been proposed to overcome this and, therefore, capture disease-specific patterns more effectively. An additional limitation of both unsupervised and semi-supervised conventional machine learning methods is that they typically model, learn and infer from data at a basis of feature sets pre- defined at a fixed scale or scales (e.g, an atlas-based regions of interest). Herein we propose a novel method, Multi-scAle heteroGeneity analysIs and Clustering (MAGIC), to depict the multi-scale presentation of disease heterogeneity, which builds on a previously proposed semi-supervised clustering method, HYDRA. It derives multi-scale and clinically interpretable feature representations and exploits a double-cyclic optimization procedure to drive inter-scale-consistent disease subtypes or neuroanatomical dimensions effectively. More importantly, to fill in the gap of understanding under what conditions the clustering model can estimate true heterogeneity related to diseases, we conducted extensive and systematic semi-simulated experiments to evaluate the proposed method on a sizeable healthy control sample from the UK Biobank (N=4403). We then applied MAGIC to real imaging data of Alzheimers disease (ADNI, N=1728) to demonstrate its potential and challenges in dissecting the neuroanatomical heterogeneity of brain diseases. Taken together, we aim to provide guidelines on when such analyses can succeed or should be taken with caution. The code of the proposed method is publicly available at https://github.com/anbai106/MAGIC.

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