Biology subjects

Morales-Navarrete, H.

Publications and source records attributed to Morales-Navarrete, H..

8 recordsLinked to original sources

bioRxiv2026

Temperature scaling of developmental tempo reveals reaction-dominated morphogen patterning

A central question in developmental biology is how embryonic patterning remains robust when developmental tempo changes. In ectotherms, temperature strongly alters developmental speed and biochemical reaction rates, whereas diffusion is expected to change only weakly. How morphogen gradients required for patterning remain correctly scaled under these conditions is unclear. We addressed this problem in medaka embryos by quantifying developmental speed, morphogen clearance, diffusion, and endogenous Nodal dynamics across a broad temperature range. Developmental tempo, morphogen production, clearance, and tissue movement increased approximately two- to threefold per 10{degrees}C, whereas effective morphogen diffusion remained largely unchanged. Despite this mismatch, germ-layer proportions and morphogen patterning remained robust. Our mathematical simulations suggest that this robustness arises because the system operates in a reaction-dominated regime, in which changes in reaction and growth kinetics - rather than diffusion - are sufficient to rescale morphogen gradients. Together, our experiments and simulations provide new insights into how morphogen gradients adjust to maintain accurate tissue patterning across changes in developmental time and tempo.

developmental biology↗

bioRxiv2026

NucVerse3D: Generalizable 3D nuclear instance segmentation across heterogeneous microscopy modalities

Accurate three-dimensional (3D) nuclear instance segmentation is a prerequisite for quantitative phenotyping in volumetric microscopy, yet remains challenging in densely packed tissues, irregular nuclear morphologies, and across heterogeneous imaging modalities. Here we present NucVerse3D, a deep-learning framework for generalized 3D nuclei instance segmentation that combines a residual attention 3D U-Net architecture with a reversible gradient-field representation for robust centroid-aware instance reconstruction. NucVerse3D is trained end to end in 3D using modality-agnostic preprocessing and isotropic scale normalization, enabling deployment across confocal microscopy, two-photon microscopy, light-sheet microscopy, micro-computed tomography, and scanning electron microscopy volumes. We benchmarked NucVerse3D on seven volumetric datasets spanning multiple species and tissues, comprising more than forty thousand manually annotated nuclei, including newly released ground-truth datasets of mouse liver tissue (control and hepatocellular carcinoma) and Drosophila brain glial nuclei. Across datasets, NucVerse3D achieved consistently high precision, recall, F1-score, and average precision, and outperformed the state-of-the-art methods particularly in dense and irregular settings, while remaining competitive on simpler cases. A single generalized model trained on pooled data matched the performance of dataset-specific models, and ablation experiments demonstrated that preprocessing and scale normalization substantially contribute to performance under strict intersection-over-union criteria. To demonstrate the biomedical utility of NucVerse3D, we applied it to three-dimensional liver images from a mouse model of hepatocellular carcinoma (HCC). High-fidelity, nucleus-by-nucleus segmentation enabled the quantification of the Nuclear Decoupling Score (NDS), which captures deviations in nuclear DNA-volume coupling at the single-nucleus level. NDS analysis revealed a progressive increase in nuclear abnormalities within tumor regions, forming spatially coherent domains of dysregulated nuclei and highlighting NDS as a potential quantitative biomarker of dysplastic and tumor tissue. Together, NucVerse3D provides a robust and generalizable solution for 3D nuclear instance segmentation and enables quantitative nuclear phenotyping across imaging modalities. Highlights- NucVerse3D provides accurate 3D nuclear instance segmentation across modalities - Residual attention and gradient fields enable robust separation of dense nuclei - New 3D annotated datasets of mouse liver and Drosophila brain are released - A generalized model achieves performance comparable to dataset-specific training - 3D nuclear phenotyping reveals spatially organized nuclear abnormalities in HCC

cell biology↗

bioRxiv2023

Gαi2-Mediated Regulation of Microtubules Dynamics and Rac1 Activity Orchestrates Cranial Neural Crest Cell Migration in Xenopus

Cell migration is a complex and essential process in various biological contexts, from embryonic development to tissue repair and cancer metastasis. Central to this process are the actin and tubulin cytoskeletons, which control cell morphology, polarity, focal adhesion dynamics, and overall motility in response to diverse chemical and mechanical cues. Despite the well-established involvement of heterotrimeric G proteins in cell migration, the precise underlying mechanism remains elusive, particularly in the context of development. This study explores the involvement of Gi2, a subunit of heterotrimeric G proteins, in cranial neural crest cell migration, a critical event in embryonic development. Our research uncovers the intricate mechanisms underlying Gi2 influence, revealing a direct interaction with the microtubule-associated protein EB1, and through this with tubulin, suggesting a regulatory function in microtubule dynamics modulation. Here, we show that Gi2 knockdown leads to microtubule stabilization, alterations in cell polarity and morphology with an increased Rac1-GTP concentration at the leading edge and cell-cell contacts, impaired cortical actin localization and focal adhesion disassembly. Interestingly, in Gi2 knockdown cells, RhoA-GTP was found to be reduced at cell-cell contacts and concentrated at the leading edge, providing evidence of Gi2 significant role in polarity. Remarkably, treatment with nocodazole, a microtubule-depolymerizing agent, effectively reduces Rac1 activity, restoring cranial NC cell morphology, actin distribution, and overall migration. Collectively, our findings shed light on the intricate molecular mechanisms underlying cranial neural crest cell migration and highlight the pivotal role of Gi2 in orchestrating microtubule dynamics through EB1 and EB3 interaction, modulating Rac1 activity during this crucial developmental process.

cell biology↗

bioRxiv2023

Virtual tissue microstructure reconstruction by deep learning and fluorescence microscopy

Analyzing tissue microstructure is essential for understanding complex biological systems in different species. Tissue functions largely depend on their intrinsic tissue architecture. Therefore, studying the three-dimensional (3D) microstructure of tissues, such as the liver, is particularly fascinating due to its conserved essential roles in metabolic processes and detoxification. Here, we present TiMiGNet, a novel deep learning approach for virtual 3D tissue microstructure reconstruction using Generative Adversarial Networks (GANs) and fluorescence microscopy. TiMiGNet overcomes challenges such as poor antibody penetration and time-intensive procedures by generating accurate, high-resolution predictions of tissue components across large volumes without the need of paired images as input. We applied TiMiGNet to analyze tissue microstructure in mouse and human liver tissue. TiMiGNet shows high performance in predicting structures like bile canaliculi, sinusoids, and Kupffer cell shapes from actin meshwork images. Remarkably, using TiMiGNet we were able to computationally reconstruct tissue structures that cannot be directly imaged due experimental limitations in deep dense tissues, a significant advancement in deep tissue imaging. Our open-source virtual prediction tool facilitates accessible and efficient multi-species tissue microstructure analysis, accommodating researchers with varying expertise levels. TiMiGNets simplicity and independence from paired images make it a versatile asset. Overall, our method represents a powerful and efficient approach for studying tissue microstructure, with far-reaching applications in diverse biological contexts and species.

bioinformatics↗

bioRxiv2023

Hep3D: A 3D single-cell digital atlas of the liver to study spatio-temporal tissue architecture

Three dimensional (3D) geometrical models are not only a powerful tool for quantitatively characterizing complex tissues but also useful for probing structure-function relationships in a tissue. However, these models are generally incomplete due to experimental limitations in acquiring multiple (>4) fluorescent channels simultaneously. Indeed, predictive geometrical and functional models of the liver have been restricted to few tissue and cellular components, excluding important cellular populations such as hepatic stellate cells (HSCs) and Kupffer cells (KCs). Here, we performed deep-tissue immunostaining, multiphoton microscopy, deeplearning techniques, and 3D image processing to computationally expand the number of simultaneously reconstructed tissue structures. We then generated a spatio-temporal singlecell atlas of hepatic architecture (Hep3D), including all main tissue and cellular components at different stages of post-natal development in mice. We used Hep3D to quantitatively study 1) hepatic morphodynamics from early post-natal development to adulthood, and 2) the structural role of KCs in the murine liver homeostasis. In addition to a complete description of bile canaliculi and sinusoidal network remodeling, our analysis uncovered unexpected spatiotemporal patterns of non-parenchymal cells and hepatocytes differing in size, number of nuclei, and DNA content. Surprisingly, we found that the specific depletion of KCs alters the number and morphology of the HSCs. These findings reveal novel characteristics of liver heterogeneity and have important implications for both the structural organization of liver tissue and its function. Our next-gen 3D single-cell atlas is a powerful tool to understand liver tissue architecture, under both physiological and pathological conditions.

cell biology↗

bioRxiv2019

Metabolic control of YAP via the acto-myosin system during liver regeneration

The mechanisms of organ size control remain poorly understood. A key question is how cells collectively sense the overall status of a tissue. We addressed this problem focusing on mouse liver regeneration, which is controlled by Hippo signalling. Using digital tissue reconstruction and quantitative image analysis, we found that the apical surface of hepatocytes forming the bile canalicular network expands concomitant with an increase of F-actin and phospho-Myosin, to compensate an overload of bile acids. Interestingly, these changes are sensed by the Hippo transcriptional co-activator YAP, which localizes to the apical F-actin-rich region and translocates to the nucleus in dependence of the acto-myosin system. This mechanism tolerates moderate bile acid fluctuations under tissue homeostasis, but activates YAP in response to sustained bile acid overload. Using an integrated biophysical-biochemical model of bile pressure and Hippo signalling, we explained this behaviour by the existence of a mechano-sensory mechanism that activates YAP in a switch-like manner. We propose that the apical surface of hepatocytes acts as a self-regulatory mechano-sensory system that responds to critical levels of bile acids as readout of tissue status.

systems biology↗

bioRxiv2019

3D spatially-resolved geometrical and functional models of human liver tissue reveal new aspects of NAFLD progression

Early disease diagnosis is key for the effective treatment of diseases. It relies on the identification of biomarkers and morphological inspection of organs and tissues. Histopathological analysis of human biopsies is the gold standard to diagnose tissue alterations. However, this approach has low resolution and overlooks 3D structural changes that are consequence of functional alterations. Here, we applied multiphoton imaging, 3D digital reconstructions and computational simulations to generate spatially-resolved geometrical and functional models of human liver tissue at different stages of non-alcoholic fatty liver disease (NAFLD). We identified a set of new morphometric cellular parameters correlated with disease progression. Moreover, we found profound topological defects in the 3D bile canaliculi (BC) network. Personalized biliary fluid dynamic simulations predicted an increased pericentral biliary pressure and zonated cholestasis, consistent with elevated cholestatic biomarkers in patients sera. Our spatially-resolved models of human liver tissue can contribute to high-definition medicine by identifying quantitative multi-parametric cellular and tissue signatures to define disease progression and provide new insights into NAFLD pathophysiology.

pathology↗

bioRxiv2018

Liquid-crystal organization of liver tissue

Functional tissue architecture originates by self-assembly of distinct cell types, following tissue-specific rules of cell-cell interactions. In the liver, a structural model of the lobule was pioneered by Elias in 1949. This model, however, is in contrast with the apparent random 3D arrangement of hepatocytes. Since then, no significant progress has been made to derive the organizing principles of liver tissue. To solve this outstanding problem, we computationally reconstructed 3D tissue geometry from microscopy images and analyzed it applying soft-condensed-matter-physics concepts. Surprisingly, analysis of the spatial organization of cell polarity revealed that hepatocytes are not randomly oriented but follow a long-range liquid-crystal order. This does not depend exclusively on hepatocytes receiving instructive signals by endothelial cells as generally assumed, since silencing Integrin-{beta}1 disrupted both liquid-crystal order and organization of the sinusoidal network. Our results suggest that bi-directional communication between hepatocytes and sinusoids underlies the self-organization of liver tissue.

biophysics↗