Biology subjects

Hilsenstein, V.

Publications and source records attributed to Hilsenstein, V..

4 recordsLinked to original sources

bioRxiv2024

HT SpaceM: A High-Throughput and Reproducible Method for Small-Molecule Single-Cell Metabolomics

Single-cell metabolomics promises to resolve metabolic cellular heterogeneity, yet current methods struggle with detecting small molecules, throughput, and reproducibility. Addressing these gaps, we developed HT SpaceM, a high-throughput single-cell metabolomics method with novel cell preparation, custom glass slides, small-molecule MALDI imaging mass spectrometry protocol, and batch processing. We propose a unified framework covering essential data analysis steps including quality control, characterization, differential analysis, structural validation and functional analysis. Interrogating human HeLa and mouse NIH3T3 cells, we detected 73 diverse small-molecule metabolites validated by bulk LC-MS/MS, achieving high reproducibility across wells and slides. Interrogating nine NCI-60 cancer cells and HeLa, we identified cell-type markers in small subpopulations. Functional analysis revealed overrepresented metabolic pathways, co-abundant metabolites, and metabolic hubs. We demonstrate the ability of SCM to analyze over 120,000 cells from over 112 samples, and provide guidance to interpret single-cell metabolic heterogeneity, revealing metabolic insights beyond population averages.

molecular biology↗

bioRxiv2023

Spatial single-cell isotope tracing reveals heterogeneity of de novo fatty acid synthesis in cancer cells

Metabolism has emerged as a key factor in homeostasis and disease including cancer. Yet, little is known about the heterogeneity of metabolic activity of cancer cells due to the lack of tools to directly probe it. Here, we present a novel method, 13C-SpaceM for spatial single-cell isotope tracing of glucose-dependent de novo lipogenesis. The method combines imaging mass spectrometry for spatially-resolved detection of 13C6-glucose-derived 13C label incorporated into esterified fatty acids with microscopy and computational methods for data integration and analysis. We validated 13C-SpaceM on a spatially-heterogeneous normoxia-hypoxia model of liver cancer cells. Investigating cultured cells, we revealed single-cell heterogeneity of lipogenic acetyl-CoA pool labelling degree upon ACLY knockdown that is hidden in the bulk analysis and its effect on synthesis of individual fatty acids. Next, we adapted 13C-SpaceM to analyze tissue sections of mice harboring isocitrate dehydrogenase (IDH)-mutant gliomas. We found a strong induction of de novo fatty acid synthesis in the tumor tissue compared to the surrounding brain. Comparison of fatty acid isotopologue patterns revealed elevated uptake of mono-unsaturated and essential fatty acids in the tumor. Furthermore, our analysis uncovered substantial spatial heterogeneity in the labelling of the lipogenic acetyl-CoA pool indicative of metabolic reprogramming during microenvironmental adaptation. Overall, 13C-SpaceM enables novel ways for spatial probing of metabolic activity at the single cell level. Additionally, this methodology provides unprecedented insight into fatty acid uptake, synthesis and modification in normal and cancerous tissues.

biochemistry↗

bioRxiv2021

CLEMSite, a software for automated phenotypic screens using light microscopy and FIB-SEM

Correlative light and electron microscopy (CLEM) combines two imaging modalities, balancing out the limits of one technique with the other. In recent years, Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) has emerged as a flexible method that enables semi-automated volume acquisition at the ultrastructural level. We present a toolset for adherent cultured cells that enables tracking and finding cell regions previously identified in light microscopy, in the FIB-SEM along with automatic acquisition of high-resolution volume datasets. We detect a grid pattern in both modalities (LM and EM), which identifies common reference points. The novel combination of these techniques enables complete automation of the workflow. This includes setting the coincidence point of both ion and electron beams, automated evaluation of the image quality and constantly tracking the sample position with the microscopes field of view reducing or even eliminating operator supervision. We show the ability to target the regions of interest in EM within 5 {micro}m accuracy, while iterating between different targets and implementing unattended data acquisition. Our results demonstrate that executing high throughput volume acquisition in electron microscopy is possible.

cell biology↗

bioRxiv2020

Bacteriophage uptake by Eukaryotic cell layers represents a major sink for phages during therapy

For over 100 years, bacteriophages have been known as viruses that infect bacteria. Yet it is becoming increasingly apparent that bacteriophages, or phages for short, have tropisms outside their bacterial hosts. During phage therapy, high doses of phages are directly administered and disseminated throughout the body, facilitating broad interactions with eukaryotic cells. Using live cell imaging across a range of cell lines we demonstrate that cell type plays a major role in phage internalisation and that smaller phages (< 100 nm) are internalised at higher rates. Uptake rates were validated under physiological shear stress conditions using a microfluidic device that mimics the shear stress to which endothelial cells are exposed to in the human body. Phages were found to rapidly adhere to eukaryotic cell layers, with adherent phages being subsequently internalised by macropinocytosis and functional phages accumulating and stably persisting intracellularly. Finally, we incorporate these results into an established pharmacokinetic model demonstrating the potential impact of phage accumulation by these cell layers, which represents a major sink for circulating phages in the body. Understanding these interactions will have important implications on innate immune responses, phage pharmacokinetics, and the efficacy of phage therapy.

microbiology↗