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Biology subjects

Nielsen, P.

Publications and source records attributed to Nielsen, P..

3 recordsLinked to original sources

Ratiometric fluorescence nanoscopy and lifetime imaging of novel Nile Red analogs for analysis of membrane packing in living cells

Subcellular membranes have complex lipid and protein compositions, which give rise to organelle-specific membrane packing, fluidity, and permeability. Due to its exquisite solvent sensitivity, the lipophilic fluorescence dye Nile Red has been used extensively to study membrane packing and polarity. Further improvement of Nile Red can be achieved by introducing electron-donating or withdrawing functional groups. Here, we compare the potential of derivatives of Nile Red with such functional substitutions for super-resolution fluorescence microscopy of lipid packing in model membranes and living cells. All studied Nile Red derivatives exhibit cholesterol-dependent fluorescence changes in model membranes, as shown by spectrally resolved stimulated emission depletion (STED) microscopy. STED imaging of Nile Red probes in cells reveals lower membrane packing in fibroblasts from healthy subjects compared to those from patients suffering from Niemann Pick type C1 (NPC1) disease, a lysosomal storage disorder with accumulation of cholesterol and sphingolipids in late endosomes and lysosomes. We also find small but consistent changes in the fluorescence lifetime of the Nile Red derivatives in NPC1 cells, suggesting altered hydrogen-bonding capacity in their membranes. All Nile Red derivatives are essentially non-fluorescent in water but increase their brightness in membranes, allowing for their use in MIN-FLUX single molecule tracking experiments. Our study uncovers the potential of Nile Red probes with functional substitutions for nanoscopic membrane imaging.

biophysics↗

Opposing immune and genetic forces shape oncogenic programs in synovial sarcoma

Synovial sarcoma is an aggressive mesenchymal neoplasm, driven by the SS18-SSX fusion, and characterized by immunogenic antigens expression and exceptionally low T cell infiltration levels. To study the cancer-immune interplay in this disease, we profiled 16,872 cells from 12 human synovial sarcoma tumors using single-cell RNA-sequencing (scRNA-Seq). Synovial sarcoma manifests antitumor immunity, high cellular plasticity and a core oncogenic program, which is predictive of low immune levels and poor clinical outcomes. Using genetic and pharmacological perturbations, we demonstrate that the program is controlled by the SS18-SSX driver and repressed by cytokines secreted by macrophages and T cells in the tumor microenvironment. Network modeling predicted that SS18-SSX promotes the program through HDAC1 and CDK6. Indeed, the combination of HDAC and CDK4/6 inhibitors represses the program, induces immunogenic cell states, and selectively targets synovial sarcoma cells. Our study demonstrates that immune evasion, cellular plasticity, and cell cycle are co-regulated and can be co-targeted in synovial sarcoma and potentially in other malignancies.

cancer biology↗

Quantifying the impact of rare and ultra-rare coding variation across the phenotypic spectrum

There is a limited understanding about the impact of rare protein truncating variants across multiple phenotypes. We explore the impact of this class of variants on 13 quantitative traits and 10 diseases using whole-exome sequencing data from 100,296 individuals. Protein truncating variants in genes intolerant to this class of mutations increased risk of autism, schizophrenia, bipolar disorder, intellectual disability, ADHD. In individuals without these disorders, there was an association with shorter height, lower education, increased hospitalization and reduced age. Gene sets implicated from GWAS did not show a significant protein truncating variants-burden beyond what captured by established Mendelian genes. In conclusion, we provide the most thorough investigation to date of the impact of rare deleterious coding variants on complex traits, suggesting widespread pleiotropic risk.\n\nMain abbreviations

genetics↗