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Biology subjects

Furman, M.

Publications and source records attributed to Furman, M..

2 recordsLinked to original sources

High-plex protein imaging across thick tissue by synchronized amplification

High-plex protein imaging is essential for decoding complex tissue organization, yet it remains largely confined to thin sections. Current approaches in millimeter-thick samples suffer from poor signal penetration and depth-dependent, uneven signal amplification. Even with specialized instrumentation to facilitate probe diffusion, iterative millimeter-thick tissue workflows can take more than four days per staining round, and reported eleven-marker experiments extend beyond a month. We introduce Amplification by Cyclic Extension (ACE), a DNA-barcoded, synchronized in situ amplification strategy that uses thermally controlled cyclic extension to coordinate DNA concatemer growth across tissue depths. By synchronously activating and coordinating reaction progression throughout the sample, ACE enables controlled, uniform signal amplification across tissue depths. Using ACE, we demonstrate 63-plex protein and RNA imaging in thin sections, 22-plex protein imaging in 200 m mouse brain sections, and 16-plex protein imaging in 1 mm-thick brain tissue encompassing over three million cells. For millimeter-thick tissues, ACE reduces per-round target-switching time from multiple days to less than eight hours, shifting volumetric high-plex protein imaging from months to days. Together, these results establish ACE as a synchronized amplification strategy that enables scalable high-plex protein imaging in thick tissues.

bioengineering↗

Insights into optimization of oleaginous fungi - genome-scale metabolic reconstruction and analysis of Umbelopsis sp. WA50703

Oleaginous fungi, known for their high lipid content--up to 80% of their dry mass--are of significant interest for biotechnological applications, particularly in biofuel and fatty acid production. Among these, the genus Umbelopsis, a common soil saprotroph of the Mucoromycota phylum, stands out for its rapid growth, low nutritional requirements, and ability to produce substantial amounts of lipids, especially polyunsaturated fatty acids (PUFAs). Despite previous studies on lipid production in Umbelopsis, metabolic engineering has been underexplored. This study fills that gap by presenting the first comprehensive metabolic model for Umbelopsis sp. WA50703, encompassing 2413 metabolites, 2216 reactions, and 1629 genes (iMD1629). The model demonstrated strong predictive accuracy, correctly predicting metabolic capabilities in 82.1% of cases when evaluated against experimental data. Using the Flux Scanning based on Enforced Objective Flux (FSEOF) algorithm, the study identified 33 genes linked to 23 metabolic reactions. Notably, reactions catalysed by acetyl-CoA carboxylase and carbonic anhydrase emerged as prime candidates for up-regulation. These findings provide a solid framework for future metabolic engineering efforts to optimize PUFA production in Umbelopsis strains. ImportanceUmbelopsis strains are capable of producing valuable compounds like polyunsaturated fatty acids (PUFAs). These compounds are essential for human health, found in various foods and supplements that support heart and brain function. In this study we developed a computer model to better understand how this fungus works at a metabolic level, guiding further research investigations towards optimization of PUFAs production in a cost-effective way. This research lays the groundwork for future innovations in metabolic engineering of Umbelopsis PUFA production leading to healthier food options and a more sustainable food system, directly impacting everyday life.

systems biology↗