Biology subjects

Puchades, M. A.

Publications and source records attributed to Puchades, M. A..

4 recordsLinked to original sources

bioRxiv2025

Software and pipelines for registration and analyses of rodent brain image data in reference atlas space

Advancements in methodologies for large-scale acquisition of high-resolution serial microscopy image data have opened new possibilities for experimental studies of cellular and subcellular features across whole brains in animal models. There is a high demand for open-source software and workflows for automated or semi-automated analysis of such data, facilitating anatomical, functional, and molecular mapping in healthy and diseased brains. These studies share a common need to precisely identify, visualize, and quantify the location of observations within anatomically defined regions, ensuring consistent and reproducible interpretation of anatomical locations and thereby allowing meaningful comparisons of results across multiple independent studies. Addressing this need, we have developed a suite of desktop and web-applications for registration of serial brain section images to three-dimensional brain reference atlases (QuickNII, VisuAlign, WebAlign, WebWarp, and DeepSlice) and for performing data analysis in a spatial context provided by an atlas (Nutil, QCAlign, SeriesZoom, LocaliZoom, and MeshView). The software can be utilized in various combinations, creating customized analytical pipelines suited to specific research needs. The web-applications are integrated in the EBRAINS research infrastructure and coupled to the EBRAINS data platform, establishing the foundation for an online analytical workbench. We here present our software ecosystem, exemplify its use by the research community, and discuss possible directions for future developments.

bioinformatics↗

bioRxiv2024

DeMBA: a developmental atlas for navigating the mouse brain in space and time

Studies of the adult mouse brain have benefited from three-dimensional (3D) atlases providing standardised frameworks for data analysis and integration. However, few 3D atlases exist for the developing mouse brain, and none cover more than a few ages. This fails to represent the dynamic nature of development and is insufficient for researchers whose data fall between the ages of existent atlases. Existing atlases also neglect the spatial correspondence between ages, making comparison across ages difficult. We present the Developmental Mouse Brain Atlas (DeMBA), a 4D atlas encompassing every postnatal day from 4 to 56. DeMBA is incorporated in software for spatial registration and analysis, enabling brain-wide quantification of features of interest. Furthermore, we provide a software package, the CCF translator, allowing coordinates or image volumes to be transformed between ages for comparison. These resources provide age-specific spatial frameworks incorporated in accessible analytic pipelines for developmental mouse brain data.

neuroscience↗

bioRxiv2022

DeepSlice: rapid fully automatic registration of mouse brain imaging to a volumetric atlas

Registration of data to a common frame of reference is an essential step in the analysis and integration of diverse neuroscientific data modalities. To this end, volumetric brain atlases enable histological datasets to be spatially registered and analysed, yet accurate registration remains expertise-dependent and slow. We have trained a neural network, DeepSlice, to register mouse brain histology to the Allen Brain Atlas, retaining accuracy while improving speed by >1000 fold.

neuroscience↗

bioRxiv2021

3D atlas of the pituitary gland of the model fish medaka

In vertebrates, the anterior pituitary plays a crucial role in regulating several essential physiological processes via the secretion of at least seven peptide hormones by different endocrine cell types. Comparative and comprehensive knowledge of the spatial distribution of those endocrine cell types is required to better understand their role during the animal life. Using medaka as the model and several combinations of multi-color fluorescence in situ hybridization, we present the first 3D atlas revealing the gland-wide distribution of seven endocrine cell populations: lactotropes, thyrotropes, Lh and Fsh gonadotropes, somatotropes, and pomca-expressing cells (corticotropes and melanotropes) in the anterior pituitary of a teleost fish. By combining in situ hybridization and immunofluorescence techniques, we deciphered the location of corticotropes and melanotropes within the pomca-expressing cell population. The 3D localization approach reveals sexual dimorphism of tshba- and pomca-expressing cells in the adult medaka pituitary. Finally, we show the existence of bi-hormonal cells co-expressing lhb-fshb, fshb-tshba and lhb-sl using single-cell transcriptomics analysis and in situ hybridization. This study offers a solid basis for future comparative studies of the teleost pituitary and its developmental plasticity. Highlights- We offer the first 3D atlas of a teleost pituitary, which presents a valuable resource to the endocrinology and model fish community. - The atlas reveals the 3D spatial distribution of the seven endocrine cell types and blood vessels in the juvenile/adult male and female pituitary. - Gene expression for tshba and pomca, as well as the population size of cells expressing these genes, displays obvious sexual dimorphism in the adult medaka pituitary. - Multi-color in situ hybridization and single cell RNA-seq reveal the existence of bi-hormonal cells, co-expressing lhb-fshb, fshb-tshba, lhb-sl, and a few multi-hormonal cells. - An online version of the atlas is available at https://www.nmbu.no/go/mpg-atlas.

neuroscience↗