Live-cell imaging with fluorescent protein-based sensors allows us to monitor many dynamic changes in situ. The first genetic manipulation of green fluorescent protein to increase brightness initiated a boom, with a myriad of fluorescent protein sensors now available that span the UV, visible and near-IR range; capable of detecting a great number of metabolites, ions, and other biological signaling components with increased spatial and temporal precision. Used for both steady-state and time-resolved approaches, fluorescent proteins can be used in a wide variety of quantitative approaches. Steady-state sensors are typically characterized as intensiometric or ratiometric; and intensiometric sensors are characterized by an increase or decrease in emission intensity in response to analyte. However, moving in vivo, concentration and intensity dependence of the fluorophore, sample thickness, and photobleaching are limiting factors. Ratiometric probes respond by an inverse change in excitation or emission profiles in response to analyte, normalizing for bleaching or protein expression effects. As an intrinsic property of fluorophores, fluorescence lifetime does not rely on protein concentration, method of measurement or fluorescence intensity. By monitoring changes in lifetime using fluorescence lifetime spectroscopy, no special ratiometric fluorophores are needed, opening up a wider selection of potential fluorescent sensors. Lifetime and other time-resolved approaches are becoming more and more popular due to ease of quantitation and increased signal to background. Here we present the in vitro and live-cell characterization of genetically encoded, ratiometric and lifetime optimized red fluorescent protein pH sensors, a methodology for quantifying receptor trafficking in real time, as well as a lanthanide time resolved imaging approach.
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/8953376 |
| Date | 13 August 2019 |
| Creators | Emily P Haynes (6984989) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/Engineering_Genetically_Encoded_Biosensors_for_Quantifying_Cellular_Dynamics/8953376 |
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