Apollo-NADP reveals in vivo adaptation of NADPH/NADP metabolism in electrically activated pancreatic β cells.

Several genetically encoded sensors have been developed to study live cell NADPH/NADP dynamics, but their use has been predominantly in vitro. Here, we developed an in vivo assay using the Apollo-NADP sensor and microfluidic devices to measure endogenous NADPH/NADP dynamics in the pancreatic β cells of live zebrafish embryos. Flux through the pentose phosphate pathway, the main source of NADPH in many cell types, has been reported to be low in β cells.

Leveraging multimodal microscopy to optimize deep learning models for cell segmentation.

Deep learning provides an opportunity to automatically segment and extract cellular features from high-throughput microscopy images. Many labeling strategies have been developed for this purpose, ranging from the use of fluorescent markers to label-free approaches. However, differences in the channels available to each respective training dataset make it difficult to directly compare the effectiveness of these strategies across studies.

Apollo-NADP(+): a spectrally tunable family of genetically encoded sensors for NADP(+).

NADPH-dependent antioxidant pathways have a critical role in scavenging hydrogen peroxide (H2O2) produced by oxidative phosphorylation. Inadequate scavenging results in H2O2 accumulation and can cause disease. To measure NADPH/NADP(+) redox states, we explored genetically encoded sensors based on steady-state fluorescence anisotropy due to FRET (fluorescence resonance energy transfer) between homologous fluorescent proteins (homoFRET); we refer to these sensors as Apollo sensors.