Biology subjects

Colazo, A.

Publications and source records attributed to Colazo, A..

3 recordsLinked to original sources

bioRxiv2026

Optical metabolic imaging of the tricarboxylic acid cycle

The tricarboxylic acid (TCA) cycle lies at the core of cellular metabolism, integrating energy production, biosynthesis and redox homeostasis, yet direct quantitative imaging of its activity in living systems remains challenging. Here we introduce MATRIX-SRS (Metabolic Activity TRacing of the trIcarboXylic acid cycle by Stimulated Raman Scattering microscopy), a platform enabling spatially resolved quantification of TCA-linked metabolism in live cells. Using emerging deuterium-labeled probes, MATRIX-SRS visualizes subcellular TCA-associated carbon-deuterium bonds in live cancer cells and neurons. We then integrate density functional theory, reaction network mapping, and hyperspectral MATRIX-SRS to construct a robust in situ metabolic quantification pipeline. Integrating MATRIX-SRS with isotope-tracing mass spectrometry, we reveal a global attenuation of TCA activity during epithelial-to-mesenchymal transition, providing deep molecular insights. Applying this framework, we further quantify changes in deuterium-labeled biomass in absolute concentrations for the first time, under native and drug-treated conditions, establishing a generalizable foundation for live quantitative spatial metabolomics.

biochemistry↗

bioRxiv2025

Deep Learning-Augmented Stimulated Raman Imaging for Cell-Type-Specific Metabolic Profiling in Live Neuronal Co-Cultures

Neuronal metabolism is fundamental to brain functions and diseases, yet its spatial and temporal dynamics and interactions remain poorly understood. Here, we introduce a tandem deep-learning approach integrated with bioorthogonal chemical imaging using stimulated Raman scattering (SRS) microscopy. This method achieves high-speed and quantitative metabolic profiling in live neuronal co-cultures. Our deep-learning framework consists of a recurrent convolutional neural network (RCNN) that enables high-resolution 3D imaging with minimal photodamage and a U-Net segmentation model for cell-type-specific metabolic analysis. Using deuterium-labeled metabolites, we demonstrate the ability to trace lipid, protein, glucose, and D2O metabolism in neurons, astrocytes, and oligodendrocytes under physiological and pathological conditions, including NMDA receptor activation, proteasome inhibition, and Huntingtons disease. Our findings reveal distinct metabolic adaptations among neuronal cell types and underscore the importance of non-invasive metabolic profiling for understanding neuronal interactions and disease mechanisms. This platform significantly advances live-cell dynamic imaging with broad applications in neuroscience, disease modeling, and therapeutic screening.

neuroscience↗

bioRxiv2025

Single-Cell Metabolic Imaging Reveals Glycogen Driven-Adaptations in Endothelial Cells

Endothelial dysfunction (ED) is a defining feature of diabetes mellitus (DM) and a key contributor to many metabolic and cardiovascular diseases. Endothelial cells (ECs) are known to be highly glycolytic and primarily rely on glucose to meet their energy demands. However, the role of glycogen metabolism in ECs remains poorly characterized due to a lack of suitable tools. Here, we utilize stimulated Raman scattering (SRS) microscopy to investigate subcellular glycogen metabolism in live ECs under stress conditions associated with highly prevalent diabetes and diabetic complications. We demonstrate that ECs exposed to a diabetes-mimicking milieu- high glucose and tumor necrosis factor (TNF-)- divert excess glucose toward subcellular glycogen storage, and that this storage capacity is significantly enhanced by the inhibition of glycogen synthase kinase 3 (GSK3). Pulse-chase experiments uncover glycogen dynamics and reveal that glycogen is rapidly mobilized under glucose starvation, highlighting its role as an immediate energy reserve in ECs. We further extend the capabilities of SRS metabolic imaging to visualize glutamine and lactate metabolism for the first time, directly showcasing the reliance of ECs on these alternative carbon substrates during glucose deprivation. Our results indicate that ECs containing glycogen exhibit a reduced immediate metabolic demand for these gluconeogenic substrates in the absence of extracellular glucose. These findings suggest that glycogen may play a broader role beyond energy reserves in ECs by modulating stress-responsive metabolic adaptations and may offer potential therapeutic opportunities to address diabetes-induced ED and related cardiometabolic diseases.

cell biology↗