Epidermal turnover in the planarian Schmidtea mediterranea involves basal cell extrusion and intestinal digestion.

Planarian flatworms undergo continuous internal turnover, wherein old cells are replaced by the division progeny of adult pluripotent stem cells (neoblasts). How cell turnover is carried out at the organismal level remains an intriguing question in planarians and other systems. While previous studies have predominantly focused on neoblast proliferation, little is known about the processes that mediate cell loss during tissue homeostasis. Here, we use the planarian epidermis as a model to study the mechanisms of cell removal. We established a covalent dye-labeling assay and image analysis pipeline to quantify the cell turnover rate in the planarian epidermis. Our findings indicate that the ventral epidermis is highly dynamic and epidermal cells undergo internalization via basal extrusion, followed by a relocation toward the intestine and ultimately digestion by intestinal phagocytes. Overall, our study reveals a complex homeostatic process of cell clearance that may generally allow planarians to catabolize their own cells.

Content aware image restoration improves spatiotemporal resolution in luminescence imaging.

Luminescent reporters are due to their intrinsically high signal-to-noise ratio a powerful labelling tool for microscopy and macroscopic in vivo imaging in biomedical research. However, luminescence signal detection requires longer exposure times than fluorescence imaging and is consequently less suited for applications requiring high temporal resolution or throughput. Here we demonstrate that content aware image restoration can drastically reduce the exposure time requirements in luminescence imaging, thus overcoming one of the major limitations of the technique.

Content-aware image restoration: pushing the limits of fluorescence microscopy.

Fluorescence microscopy is a key driver of discoveries in the life sciences, with observable phenomena being limited by the optics of the microscope, the chemistry of the fluorophores, and the maximum photon exposure tolerated by the sample. These limits necessitate trade-offs between imaging speed, spatial resolution, light exposure, and imaging depth. In this work we show how content-aware image restoration based on deep learning extends the range of biological phenomena observable by microscopy. We demonstrate on eight concrete examples how microscopy images can be restored even if 60-fold fewer photons are used during acquisition, how near isotropic resolution can be achieved with up to tenfold under-sampling along the axial direction, and how tubular and granular structures smaller than the diffraction limit can be resolved at 20-times-higher frame rates compared to state-of-the-art methods. All developed image restoration methods are freely available as open source software in Python, FIJI, and KNIME.

A tunable refractive index matching medium for live imaging cells, tissues and model organisms.

In light microscopy, refractive index mismatches between media and sample cause spherical aberrations that often limit penetration depth and resolution. Optical clearing techniques can alleviate these mismatches, but they are so far limited to fixed samples. We present Iodixanol as a non-toxic medium supplement that allows refractive index matching in live specimens and thus substantially improves image quality in live-imaged primary cell cultures, planarians, zebrafish and human cerebral organoids.

Inter-domain tagging implicates caveolin-1 in insulin receptor trafficking and Erk signaling bias in pancreatic beta-cells.

OBJECTIVE: The role and mechanisms of insulin receptor internalization remain incompletely understood. Previous trafficking studies of insulin receptors involved fluorescent protein tagging at their termini, manipulations that may be expected to result in dysfunctional receptors. Our objective was to determine the trafficking route and molecular mechanisms of functional tagged insulin receptors and endogenous insulin receptors in pancreatic beta-cells. METHODS: We generated functional insulin receptors tagged with pH-resistant fluorescent proteins between domains. Confocal, TIRF and STED imaging revealed a trafficking pattern of inter-domain tagged insulin receptors and endogenous insulin receptors detected with antibodies. RESULTS: Surprisingly, interdomain-tagged and endogenous insulin receptors in beta-cells bypassed classical Rab5a- or Rab7-mediated endocytic routes. Instead, we found that removal of insulin receptors from the plasma membrane involved tyrosine-phosphorylated caveolin-1, prior to trafficking within flotillin-1-positive structures to lysosomes. Multiple methods of inhibiting caveolin-1 significantly reduced Erk activation in vitro or in vivo, while leaving Akt signaling mostly intact. CONCLUSIONS: We conclude that phosphorylated caveolin-1 plays a role in insulin receptor internalization towards lysosomes through flotillin-1-positive structures and that caveolin-1 helps bias physiological beta-cell insulin signaling towards Erk activation.

Statistical approaches and software for clustering islet cell functional heterogeneity.

Worldwide efforts are underway to replace or repair lost or dysfunctional pancreatic ß-cells to cure diabetes. However, it is unclear what the final product of these efforts should be, as ß-cells are thought to be heterogeneous. To enable the analysis of ß-cell heterogeneity in an unbiased and quantitative way, we developed model-free and model-based statistical clustering approaches, and created new software called TraceCluster. Using an example data set, we illustrate the utility of these approaches by clustering dynamic intracellular Ca(2+) responses to high glucose in ∼300 simultaneously imaged single islet cells. Using feature extraction from the Ca(2+) traces on this reference data set, we identified 2 distinct populations of cells with ß-like responses to glucose. To the best of our knowledge, this report represents the first unbiased cluster-based analysis of human ß-cell functional heterogeneity of simultaneous recordings. We hope that the approaches and tools described here will be helpful for those studying heterogeneity in primary islet cells, as well as excitable cells derived from embryonic stem cells or induced pluripotent cells.