Biology subjects

Martinez Casals, A.

Publications and source records attributed to Martinez Casals, A..

3 recordsLinked to original sources

bioRxiv2025

Latent plasticity of the human pancreas across development, health, and disease.

The pancreas plays a central role in major human diseases, yet our understanding of its cellular diversity and plasticity remains incomplete. Here, we present a single-cell multiomics atlas of the human pancreas, profiling over four million cells and nuclei from 57 donors across fetal development, adult homeostasis, and type 2 diabetes (T2D). Integrating sc/snRNA-seq, snATAC-seq, VASA-seq, spatial transcriptomics (Xenium), and multiplexed proteomics (CODEX), we resolve gene expression, chromatin accessibility, and spatial organization at high resolution. We identify transcriptionally plastic centroacinar-like cells (pCACs) in adults with fetal-like features, delineate endocrine and exocrine lineage trajectories during development, and uncover HNF1A-defined beta cell epigenetic states. In T2D, we observe shifts in beta cell subtypes and altered regulatory programs. Glucose perturbation of healthy islets reveals cell-type-specific adaptation and stress responses. This atlas provides a foundational framework to understand pancreas biology and the role of cellular plasticity in regeneration and disease.

genomics↗

bioRxiv2025

Streamlining Multiplexed Tissue Image Analysis with PIP{Sigma}X: An Integrated Automated Pipeline for Image Processing and EXploration for Diverse Tissue Types

Spatial proteomics via multiplexed tissue imaging is transforming how we study biology, enabling researchers to investigate dozens of markers in a single tissue section and explore how cells behave in their native habitat. While imaging technologies have advanced rapidly, data analyses remain a bottleneck. To address this, we developed PIP{Sigma}X (Pipeline for Image Processing and EXploration), a user-friendly, end-to-end open-source software designed to make complex image analysis approachable, even for those with little or no programming skills. PIP{Sigma}X combines robust automation with an intuitive graphical user interface, guiding users through each step of the analysis, from image preprocessing and membrane-aware cell segmentation to signal quantification and spatial data exploration. Each feature includes built-in explanations, recommendations, and quality controls to help users make confident choices throughout the process. PIP{Sigma}X is compatible with a wide range of multiplexed imaging platforms, and its outputs integrate seamlessly with visualization tools like TissUUmaps and QuPath. Also, it supports downstream applications by enabling direct export of selected cell coordinates for laser microdissection. This functionality facilitates precise isolation of target cell populations for deep proteomic or transcriptomic profiling. With PIP{Sigma}X, researchers can extract meaningful biological insights from multiplexed images more easily and robustly, helping to bridge the gap between powerful imaging technologies and real-world scientific discovery. HighlightsO_LIPIP{Sigma}X offers a user-friendly "one-stop shop" pipeline for multiplexed tissue image analysis C_LIO_LIwithout coding C_LIO_LIWorks across diverse tissue types and imaging platforms at whole-slide scale C_LIO_LIIncludes membrane-aware segmentation and quality control features C_LIO_LISeamlessly integrates with visualization platforms like TissUUmaps and QuPath for data exploration C_LIO_LIEnables export for automated laser microdissection and spatial single-cell profiling C_LI

bioinformatics↗

bioRxiv2022

Developmental origins of cell heterogeneity in the human lung

The lung contains numerous specialized cell-types with distinct roles in tissue function and integrity. To clarify the origins and mechanisms generating cell heterogeneity, we created a first comprehensive topographic atlas of early human lung development. We report 83 cell states, several spatially-resolved developmental trajectories and predict cell interactions within defined tissue niches. We integrated scRNA-Seq and spatial transcriptomics into a web-based, open platform for interactive exploration. To illustrate the utility of our approach we show distinct states of secretory and neuroendocrine cells, largely overlapping with the programs activated either during lung fibrosis or small cell lung cancer progression. We define the origin of uncharacterized airway fibroblasts associated with airway smooth muscle in bronchovascular bundles, and describe a trajectory of Schwann cell progenitors to intrinsic parasympathetic neurons controlling bronchoconstriction. Our atlas provides a rich resource for further research and a reference for defining deviations from homeostatic and repair mechanisms leading to pulmonary diseases.

developmental biology↗