Detecting

A Lentiviral Fluorescent Reporter to Study Circadian Rhythms in Single Cells

Authors

Christian H. Gabriel, Luis Lehmann, Joana Ahlburg, and Achim Kramer

Journal

Journal of Biological Rhythms

Abstract

Circadian rhythms—self-sustained, ~24-h oscillations in transcript and protein levels—are generated by a cell-autonomous molecular clock. These rhythms shape how individual cells respond to external signals, influencing key decisions such as differentiation and apoptosis. However, current tools for visualizing circadian rhythms at the single-cell level often rely on genomic engineering and clonal expansion, limiting their accessibility and applicability. We present fluorescent circadian reporters based on the murine REVERBα/Nr1d1 gene, delivered via lentiviral transduction and compatible with time-lapse single-cell microscopy. These reporters produce oscillatory signals that depend on a functional circadian clock and can be used to determine a cell’s circadian dynamics parameters, such as circadian phase. Their simple and efficient delivery should make them suitable for a wide variety of cell types, greatly expanding opportunities to study single-cell circadian dynamics and their impact across diverse biological processes and systems.

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Supporting media

Member authors

Research area

S01

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Scientific service project

This consortium relies on standardized methods, high-quality biospecimens, and computational tools to enable circadian medicine research. This service project provides molecular biomarker assays, standardized cohorts, multi-omics datasets, and bioinformatics support for the analysis of high-dimensional circadian data. Its resources and expertise are used across the consortium, supporting the discovery of circadian principles and facilitating personalized interventions.

Scientific service project

This consortium relies on standardized methods, high-quality biospecimens, and computational tools to enable circadian medicine research. This service project provides molecular biomarker assays, standardized cohorts, multi-omics datasets, and bioinformatics support for the analysis of high-dimensional circadian data. Its resources and expertise are used across the consortium, supporting the discovery of circadian principles and facilitating personalized interventions.