Accurate 4Pi single-molecule localization using an experimental PSF model.

Interferometric single-molecule localization microscopy (iPALM, 4Pi-SMS) uses multiphase interferometry to localize single fluorophores and achieves nanometer isotropic resolution in 3D. The current data analysis workflow, however, fails to reach the theoretical resolution limit due to the suboptimal localization algorithm. Here, we develop a method to fit an experimentally derived point spread function (PSF) model to the interference 4Pi-PSF. As the interference phase is not fixed with respect to the shape of the PSF, we decoupled the phase term in the model from the 3D position of the PSF. The fitter can reliably infer the interference period even without introducing astigmatism, reducing the complexity of the microscope. Using a spline-interpolated experimental PSF model and by fitting all phase images globally, we show on simulated data that we can achieve the theoretical limit of 3D resolution, the Cramér-Rao lower bound (CRLB), also for the 4Pi microscope.

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

While heterogeneity is a key feature of cancer, understanding metabolic heterogeneity at the single-cell level remains a challenge. Here we present 13C-SpaceM, a method for spatial single-cell isotope tracing that extends the previously published SpaceM method with detection of 13C6-glucose-derived carbons in esterified fatty acids. We validated 13C-SpaceM on spatially heterogeneous models using liver cancer cells subjected to either normoxia-hypoxia or ATP citrate lyase depletion. This revealed substantial single-cell heterogeneity in labelling of the lipogenic acetyl-CoA pool and in relative fatty acid uptake versus synthesis hidden in bulk analyses. Analysing tumour-bearing brain tissue from mice fed a 13C6-glucose-containing diet, we found higher glucose-dependent synthesis of saturated fatty acids and increased elongation of essential fatty acids in tumours compared with healthy brains. Furthermore, our analysis uncovered spatial heterogeneity in lipogenic acetyl-CoA pool labelling in tumours. Our method enhances spatial probing of metabolic activities in single cells and tissues, providing insights into fatty acid metabolism in homoeostasis and disease.

13C-SpaceM: Spatial single-cell isotope tracing reveals heterogeneity of de novo fatty acid synthesis in cancer.

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.

Single-molecule sensing of peptides and nucleic acids by engineered aerolysin nanopores.

Nanopore sensing is a powerful single-molecule approach for the detection of biomolecules. Recent studies have demonstrated that aerolysin is a promising candidate to improve the accuracy of DNA sequencing and to develop novel single-molecule proteomic strategies. However, the structure-function relationship between the aerolysin nanopore and its molecular sensing properties remains insufficiently explored. Herein, a set of mutated pores were rationally designed and evaluated in silico by molecular simulations and in vitro by single-channel recording and molecular translocation experiments to study the pore structural variation, ion selectivity, ionic conductance and capabilities for sensing several biomolecules. Our results show that the ion selectivity and sensing ability of aerolysin are mostly controlled by electrostatics and the narrow diameter of the double ß-barrel cap. By engineering single-site mutants, a more accurate molecular detection of nucleic acids and peptides has been achieved. These findings open avenues for developing aerolysin nanopores into powerful sensing devices.