Biology subjects

Villazon, J.

Publications and source records attributed to Villazon, J..

5 recordsLinked to original sources

bioRxiv2026

Long-lived yeast-derived lipids promote longevity via regional and systemic metabolic remodeling

Aging is marked by a progressive breakdown of intestinal integrity and metabolic homeostasis, which together drives systemic decline in physiology and reduces lifespan. Here, we found that dietary lipids extracted from a genetically engineered long-lived yeast strain robustly extend lifespan in Drosophila and further uncovered the mechanisms using deuterium oxide-probed stimulated Raman scattering microscopy to image metabolic dynamics and single nucleus RNA sequencing (scRNA-seq) to unveil the underlying pathways. These yeast lipids are enriched in shorter, more saturated fatty acids and phospholipids as revealed by Raman spectroscopy and lipidomics, contributing to increased membrane order and reduced lipid storage. Functionally, targeted dietary supplementation with these lipid components synergistically prolongs fly lifespan. We show that these lipids reverse age-related declines in gut lipid droplet abundance, enhance membrane lipid incorporation, and increase de novo lipid synthesis, thereby improving epithelial structural integrity and barrier function. snRNA-seq identifies transcriptional remodeling in metabolically active enterocytes, including upregulation of autophagy and protein turnover genes, alongside reduction of unsaturated fatty acid biosynthesis. In the brain, dietary lipids orchestrate a dual metabolic strategy--promoting energy conservation and enhanced signaling across most neuronal and glial populations, while selectively boosting mitochondrial function in memory-critical Kenyon cells. All these leads to the enhancement of gut-to-glia communication, particularly through EGFR and FGFR pathways. Finally, analysis of our data with the Fly Metabolic Analysis Pipeline (FLY-MAP) reveals that yeast lipids restructure gut metabolic modules to coordinate energy production, redox balance, and nutrient flexibility. Our study uncovers a cross-kingdom mechanism of metabolic longevity regulation, paving the way for leveraging yeast-derived nutritional components to support tissue homeostasis and promote healthy aging.

molecular biology↗

bioRxiv2026

NetTracer3D Enables User-Friendly Analysis of Diverse Microscopic and Medical 3D Datasets

Recent advances in high-resolution imaging and spatial transcriptomics have enabled reconstruction of complex 3D tissue maps, providing unprecedented insights into cellular connectivity, organization, and tissue architecture. However, standardization challenges hinder integration, sharing, and analysis of these datasets across research communities. We developed NetTracer3D to simplify three-dimensional image analysis across diverse datasets. NetTracer3D is an integrated tool for defining, processing, and sharing 3D tissue maps with standardized data formats and interactive exploration capabilities. It provides three broadly applicable network analysis modalities: Connectivity networks for analyzing functional tissue units or cells connected via secondary structures such as nerves or vasculature; Branch Adjacency and Branchpoint networks for converting branched anatomical structures into analyzable representations; and Proximity networks for grouping structures by spatial relationships to identify cellular organization patterns. We demonstrate several use cases applying NetTracer3D to analyze multidimensional data from CODEX and label free Raman spectroscopy, multiscalar data encompassing subcellular and anatomical scales and a range of modalities. NetTracer3D was able to characterize neural relationships between functional tissue units in human and mouse kidneys and mouse bronchi. Branchpoint networks were used to identify vascular defects in human brain angiogram and define the innervation structure of a lymph node. Finally, we demonstrate how proximity networks characterize the tumor microenvironment in 3D light sheet cancer images and auto-detect cellular neighborhoods in multiplexed 2D CODEX datasets. Beyond network creation, NetTracer3D enables analysis, spatial statistics, and visual analytics tailored for volumetric tissue data. By establishing interoperable formats and analysis workflows, this work provides accessible and reproducible analytical tools for 3D spatial biology, enabling new discoveries of relationships between structure and physiology.

genomics↗

bioRxiv2025

Imaging Cellular Metabolic Rewiring with SuMMIT-SRS

Cells dynamically rewire their metabolic pathways in response to physiological and pathological cues. Such plasticity is particularly critical in neurons, stem cells, cancer cells, and immune cells, where biosynthetic demands can shift rapidly. However, current metabolic imaging techniques using isotope labeling typically track only one metabolite at a time, limiting their ability to capture the rapid dynamics of complex metabolic networks including coordinated precursor utilization, crosstalk, and turnover. Here, we present Subcellular Multiplexed Metabolic Isotope Tracing Stimulated Raman Scattering microscopy (SuMMIT-SRS), a platform that enables simultaneous visualization of multiple metabolic dynamics at subcellular resolution. By exploiting the distinct vibrational signatures of carbon-deuterium bonds derived from multiple deuterated amino acids, lipids, and monosaccharide tracers, SuMMIT-SRS maps co-regulated DNA, RNA, protein, and lipid synthesis at the same time and resolves various individual amino acid-mediated metabolic pathways within intact cells and tissues. We demonstrate SuMMITs broad utility across Drosophila fat body tissue and developing brain, tumor organoids, aged human neurons, and mouse liver, capturing cell type-specific metabolic rewiring under genetic and pathological perturbations. This approach extends SRS to multiplexed isotope tracing, offering a powerful tool to uncover dynamic and complex biosynthesis programs in development, health, and disease.

bioengineering↗

bioRxiv2025

A multimodal imaging approach for imaging the metabolic changes resulting from bronchopulmonary dysplasia

Lung tissue is composed of various functional units, each essential for maintaining the intricate functions of the lung. Disruptions in the molecular and cellular mechanisms in the lung can cause tissue fibrosis, inflammation, and severe breathing difficulties, which are common in conditions such as bronchopulmonary dysplasia (BPD). BPDs molecular changes are not well understood, which hinders effective diagnosis and treatment. Here, we present a new multimodal imaging workflow for detailed molecular and metabolic characterization of tissues at multiple spatial scales. We applied a combined imaging approach using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) and ultrafast focused light-based imaging & photonics platform (U-FLIP) that included two-photon fluorescence (TPF), second harmonic generation (SHG), and stimulated Raman scattering (SRS). We also developed a hierarchical multimodal registration network (HiMReg) for the precise co-registration of each modality. This approach revealed previously unknown metabolic changes in distinct functional tissue units affected by BPD, including altered lipid distributions, reduced optical redox states, and specific collagen remodeling in bronchioles. Our findings evidenced alterations in lipid composition and metabolism of BPD-affected alveoli compared to healthy tissue, providing novel insights into disease pathophysiology. Our findings elucidate the intricate spatial and molecular complexity of BPD, building on prior research that did not provide the spatial resolution necessary to capture the nuances of metabolic alterations. This multimodal approach offers exceptional insights into disease exploration and could transform the way we study spatially heterogeneous conditions. By providing detailed maps of the metabolic shifts occurring in distinct tissue microanatomical features, the methods developed here could enable the discovery of new therapeutic avenues, making it highly attractive for the field of biomedical research.

physiology↗

bioRxiv2024

All-Optical Multimodal Mapping of Single Cell Type-Specific Metabolic Activities via REDCAT

Metabolism underlies cell growth, survival, and function, yet its activities vary widely across cell types and tissue environments. Spatially resolving these processes in situ at single-cell resolution is essential to advance our understanding of cellular function and tissue physiology in health and disease. However, existing approaches are limited by either destructive workflows, insufficient spatial resolution and biochemical specificity, or lack of direct linkage to cell identity. Here, we present Raman Enhanced Delineation of Cell Atlases in Tissues (REDCAT), a multimodal all-optical platform that integrates stimulated Raman scattering, autofluorescence redox imaging, second harmonic generation, and high-plex immunofluorescence to co-map metabolic activities and cell types within the same tissue section. REDCAT achieves subcellular resolution profiling of protein, lipid, redox, and nuclear acid metabolism, together with extracellular matrix composition, in both FFPE and fresh-frozen human tissues. Applied to normal lymph nodes, REDCAT delineated distinct redox and lipid remodeling programs across germinal center B-cell zones and immune subsets, highlighting cell-type-specific metabolic specialization. In lymphoma, it revealed profound metabolic reprogramming, including extensive lipid accumulation, nuclear metabolic heterogeneity, and a transitional metabolic state associated with transformation from chronic lymphocytic leukemia to diffuse large B-cell lymphoma, thereby illuminating tumor evolution in situ. In human liver, REDCAT resolved cell-type-specific lipid droplet diversity and zonation-dependent nuclear metabolic gradients, uncovering new principles of spatial metabolic organization. By directly linking cell identity with spatial metabolic states at single-cell or subcellular resolution, REDCAT establishes a broadly applicable framework for studying immune function, tumor progression, and tissue physiology, and offers a new path to deciphering the metabolic basis of health and disease.

cell biology↗