Dataset Information

A predictive model of asymmetric morphogenesis from 3D reconstructions of mouse heart looping dynamics.

ABSTRACT: How left-right patterning drives asymmetric morphogenesis is unclear. Here, we have quantified shape changes during mouse heart looping, from 3D reconstructions by HREM. In combination with cell labelling and computer simulations, we propose a novel model of heart looping. Buckling, when the cardiac tube grows between fixed poles, is modulated by the progressive breakdown of the dorsal mesocardium. We have identified sequential left-right asymmetries at the poles, which bias the buckling in opposite directions, thus leading to a helical shape. Our predictive model is useful to explore the parameter space generating shape variations. The role of the dorsal mesocardium was validated in Shh^-/- mutants, which recapitulate heart shape changes expected from a persistent dorsal mesocardium. Our computer and quantitative tools provide novel insight into the mechanism of heart looping and the contribution of different factors, beyond the simple description of looping direction. This is relevant to congenital heart defects.

SUBMITTER: Le Garrec JF

PROVIDER: S-EPMC5705212 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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A predictive model of asymmetric morphogenesis from 3D reconstructions of mouse heart looping dynamics.

Le Garrec Jean-François JF Domínguez Jorge N JN Desgrange Audrey A Ivanovitch Kenzo D KD Raphaël Etienne E Bangham J Andrew JA Torres Miguel M Coen Enrico E Mohun Timothy J TJ Meilhac Sigolène M SM

eLife 20171128

How left-right patterning drives asymmetric morphogenesis is unclear. Here, we have quantified shape changes during mouse heart looping, from 3D reconstructions by HREM. In combination with cell labelling and computer simulations, we propose a novel model of heart looping. Buckling, when the cardiac tube grows between fixed poles, is modulated by the progressive breakdown of the dorsal mesocardium. We have identified sequential left-right asymmetries at the poles, which bias the buckling in oppo ...[more]

PMID: 29179813

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Project description:AimsVertebrate heart development requires the complex morphogenesis of a linear tube to form the mature organ, a process essential for correct cardiac form and function, requiring coordination of embryonic laterality, cardiac growth, and regionalized cellular changes. While previous studies have demonstrated broad requirements for extracellular matrix (ECM) components in cardiac morphogenesis, we hypothesized that ECM regionalization may fine tune cardiac shape during heart development.Methods and resultsUsing live in vivo light sheet imaging of zebrafish embryos, we describe a left-sided expansion of the ECM between the myocardium and endocardium prior to the onset of heart looping and chamber ballooning. Analysis using an ECM sensor revealed the cardiac ECM is further regionalized along the atrioventricular axis. Spatial transcriptomic analysis of gene expression in the heart tube identified candidate genes that may drive ECM expansion. This approach identified regionalized expression of hapln1a, encoding an ECM cross-linking protein. Validation of transcriptomic data by in situ hybridization confirmed regionalized hapln1a expression in the heart, with highest levels of expression in the future atrium and on the left side of the tube, overlapping with the observed ECM expansion. Analysis of CRISPR-Cas9-generated hapln1a mutants revealed a reduction in atrial size and reduced chamber ballooning. Loss-of-function analysis demonstrated that ECM expansion is dependent upon Hapln1a, together supporting a role for Hapln1a in regionalized ECM modulation and cardiac morphogenesis. Analysis of hapln1a expression in zebrafish mutants with randomized or absent embryonic left-right asymmetry revealed that laterality cues position hapln1a-expressing cells asymmetrically in the left side of the heart tube.ConclusionWe identify a regionalized ECM expansion in the heart tube which promotes correct heart development, and propose a novel model whereby embryonic laterality cues orient the axis of ECM asymmetry in the heart, suggesting these two pathways interact to promote robust cardiac morphogenesis.

Project description:Mammalian airways are highly ramified tree-like structures that develop by the repetitive branching of the lung epithelium into the surrounding mesenchyme through reciprocal interactions. Based on a morphometric analysis of the epithelial tree, it has been recently proposed that the complete branching scheme is specified early in each lineage by a programme using elementary patterning routines at specific sites and times in the developing lung. However, the coupled dynamics of both the epithelium and mesenchyme have been overlooked in this process. Using a qualitative and quantitative in vivo morphometric analysis of the E11.25 to E13.5 mouse whole right cranial lobe structure, we show that beyond the first generations, the branching stereotypy relaxes and both spatial and temporal variations are common. The branching pattern and branching rate are sensitive to the dynamic changes of the mesoderm shape that is in turn mainly dependent upon the volume and shape of the surrounding intrathoracic organs. Spatial and temporal variations of the tree architecture are related to local and subtle modifications of the mesoderm growth. Remarkably, buds never meet after suffering branching variations and continue to homogenously fill the opening spaces in the mesenchyme. Moreover despite inter-specimen variations, the growth of the epithelial tree and the mesenchyme remains highly correlated over time at the whole lobe level, implying a long-range regulation of the lung lobe morphogenesis. Together, these findings indicate that the lung epithelial tree is likely to adapt in real time to fill the available space in the mesenchyme, rather than being rigidly specified and predefined by a global programme. Our results strongly support the idea that a comprehensive understanding of lung branching mechanisms cannot be inferred from the branching pattern or behavior alone. Rather it needs to be elaborated upon with the reconsideration of mesenchyme-epithelium coupled growth and lung tissues mechanics.

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Project description:Objective. Model based deep learning (MBDL) has been challenging to apply to the reconstruction of 3D non-Cartesian MRI due to GPU memory demand because the entire volume is needed for data-consistency steps embedded in the model. This requirement makes holding even a single unroll in GPU memory difficult meaning memory efficient techniques used to increase unroll number like gradient checkpointing and deep equilibrium learning will not work well for high spatial resolution 3D non-Cartesian reconstructions without modification. Here we develop a memory efficient method called block-wise learning that combines gradient checkpointing with patch-wise training to overcome this obstacle and allow for fast and high-quality 3D non-Cartesian reconstructions using MBDL.Approach. Block-wise learning applied to a single unroll decomposes the input volume into smaller patches, gradient checkpoints each patch, passes each patch iteratively through a neural network regularizer, and then rebuilds the full volume from these output patches for data-consistency. This method is applied across unrolls during training. Block-wise learning significantly reduces memory requirements by tying GPU memory for a single unroll to user selected patch size instead of the full volume. This algorithm was used to train a MBDL architecture to reconstruct highly undersampled, 1.25 mm isotropic, pulmonary magnetic resonance angiography volumes with matrix sizes varying from 300-450 × 200-300 × 300-450 on a single GPU. We compared block-wise learning reconstructions against L1 wavelet compressed reconstructions and proxy ground truth images.Main results. MBDL with block-wise learning significantly improved image quality relative to L1 wavelet compressed sensing while simultaneously reducing average reconstruction time 38x.Significance. Block-wise learning allows for MBDL to be applied to high spatial resolution, 3D non-Cartesian datasets with improved image quality and significant reductions in reconstruction time relative to traditional iterative methods.

Dataset Information

A predictive model of asymmetric morphogenesis from 3D reconstructions of mouse heart looping dynamics.

Publications

A predictive model of asymmetric morphogenesis from 3D reconstructions of mouse heart looping dynamics.

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