RESUMO
Genetically encoded sensors enable quantitative imaging of analytes in live cells. Sensors are commonly constructed by combining ligand-binding domains with one or more sensitized fluorescent protein (FP) domains. Sensors based on a single FP can be susceptible to artifacts caused by changes in sensor levels or distribution in vivo. To develop intensiometric sensors with the capacity for ratiometric quantification, dual-FP Matryoshka sensors were generated by using a single cassette with a large Stokes shift (LSS) reference FP nested within the reporter FP (cpEGFP). Here, we present a genetically encoded calcium sensor that employs green apple (GA) Matryoshka technology by incorporating a newly designed red LSSmApple fluorophore. LSSmApple matures faster and provides an optimized excitation spectrum overlap with cpEGFP, allowing for monochromatic coexcitation with blue light. The LSS of LSSmApple results in improved emission spectrum separation from cpEGFP, thereby minimizing fluorophore bleed-through and facilitating imaging using standard dichroic and red FP (RFP) emission filters. We developed an image analysis pipeline for yeast (Saccharomyces cerevisiae) timelapse imaging that utilizes LSSmApple to segment and track cells for high-throughput quantitative analysis. In summary, we engineered a new FP, constructed a genetically encoded calcium indicator (GA-MatryoshCaMP6s), and performed calcium imaging in yeast as a demonstration.
Assuntos
Cálcio , Saccharomyces cerevisiae , Proteínas Luminescentes/química , Cálcio/metabolismo , Saccharomyces cerevisiae/genética , Saccharomyces cerevisiae/metabolismo , Proteína Vermelha Fluorescente , Corantes FluorescentesRESUMO
For quality, interpretation, reproducibility and sharing value, microscopy images should be accompanied by detailed descriptions of the conditions that were used to produce them. Micro-Meta App is an intuitive, highly interoperable, open-source software tool that was developed in the context of the 4D Nucleome (4DN) consortium and is designed to facilitate the extraction and collection of relevant microscopy metadata as specified by the recent 4DN-BINA-OME tiered-system of Microscopy Metadata specifications. In addition to substantially lowering the burden of quality assurance, the visual nature of Micro-Meta App makes it particularly suited for training purposes.