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Abstract
Luciferase-based reporters provide a key measurement approach in a broad range of applications, from in vitro high-throughput screening to whole animal imaging. For example, luminescence intensity is widely used to measure promoter activity, protein expression levels, and cell growth. However, luminescence intensity measurements are subject to quantitative irregularities caused by luminescence decay and variation in reporter expression level. In contrast, bioluminescence resonance energy transfer (BRET) sensors provide the advantages of luciferase-based reporters but overcome the aforementioned irregularities because of the inherently ratiometric readout. Here, we generated a new ratiometric BRET sensor of ATP (ARSeNL—ATP detection with a Ratiometric mScarlet-NanoLuc sensor), and we demonstrated that it provides a stable and robust readout across protein, cell, and whole animal tissue contexts. The ARSeNL sensor was engineered by screening a color palette of sensors utilizing variants of the high photon flux NanoLuc luciferase as donors and a panel of red fluorescent proteins as acceptors. We found that the novel combination of NanoLuc and mScarlet exhibited the largest dynamic range, with a 5-fold change in the BRET ratio upon saturation with ATP. Importantly, the NanoLuc-mScarlet BRET pair provided a large spectral separation between luminescence emission channels that is compatible with green and red filter sets extensively used in typical biological microscopes and animal imaging systems. Using this new sensor, we showed that the BRET ratio was independent of luminescence intensity decay and sensor expression level, and the BRET ratio faithfully reported differences in live-cell energy metabolism whether in culture or within mouse tissue. In particular, BRET analyte sensors have not been used broadly in tissue contexts, and thus, in principle, our sensor could provide a new tool for in vivo imaging of metabolic status.
Highlights
Bioluminescence imaging has been widely adopted in biomedical research because it offers a cost-effective, accessible method for low background and high signal-to-noise non-invasive optical measurements [1,2,3,4,5]
In contrast to intensity-based reporters, ratiometric sensors that employ intramolecular bioluminescence resonance energy transfer (BRET) provide an optical signal normalized for variations in luminescence flux caused by differences in sensor expression level or changing substrate concentration
We validated that the system could efficiently detect different levels of photon flux without causing artifacts in the BRET ratio, and in doing so we demonstrated that the BRET ratio faithfully reported differences in ATP levels in a protein concentration-independent manner (Figure S4)
Summary
Bioluminescence imaging has been widely adopted in biomedical research because it offers a cost-effective, accessible method for low background and high signal-to-noise non-invasive optical measurements [1,2,3,4,5]. Bioluminescent reporters have been extensively used with rodent cancer models to measure signaling, tumor volume, and immune cell infiltration in vivo [6,7]. In contrast to intensity-based reporters, ratiometric sensors that employ intramolecular bioluminescence resonance energy transfer (BRET) provide an optical signal normalized for variations in luminescence flux caused by differences in sensor expression level or changing substrate concentration. Ratiometric BRET sensors have not been widely used beyond in vitro applications, with notable exceptions, such as luminescent calcium imaging in brain slices and the detection of protein-protein interactions in vivo [12,18]. Our objective was to demonstrate that a ratiometric BRET sensor provides an effective tool for live-cell measurements across model systems, from single-cell microscopy of cultured cells to macroscopic imaging through animal tissue. We showed that it is possible to use a red fluorescent protein (RFP) acceptor to create a BRET sensor with a large donor-acceptor emission wavelength difference that facilitates filter-based imaging in widely available animal imaging systems
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