Auto-FPFA: An Automated Microscope for Characterizing Genetically Encoded Biosensors

Abstract

Genetically encoded biosensors function by linking structural change in a protein construct, typically tagged with one or more fluorescent proteins, to changes in a biological parameter of interest (such as calcium concentration, pH, phosphorylation-state, etc.). Typically, the structural change triggered by alterations in the bio-parameter is monitored as a change in either fluorescent intensity, or lifetime. Potentially, other photo-physical properties of fluorophores, such as fluorescence anisotropy, molecular brightness, concentration, and lateral and/or rotational diffusion could also be used. Furthermore, while it is likely that multiple photo-physical attributes of a biosensor might be altered as a function of the bio-parameter, standard measurements monitor only a single photo-physical trait. This limits how biosensors are designed, as well as the accuracy and interpretation of biosensor measurements. Here we describe the design and construction of an automated multimodal-microscope. This system can autonomously analyze 96 samples in a micro-titer dish and for each sample simultaneously measure intensity (photon count), fluorescence lifetime, time-resolved anisotropy, molecular brightness, lateral diffusion time, and concentration. We characterize the accuracy and precision of this instrument, and then demonstrate its utility by characterizing three types of genetically encoded calcium sensors as well as a negative control.

Effects of excitation light polarization on fluorescence emission in two-photon light-sheet microscopy

“…(7) and (8) in Section 2. For fluorescein, we set V∼0.34 nm 3 and τ∼4.1 ns [43]; for EGFP, we set V∼33 nm 3 [44] and τ∼2.6 ns [45] and for GCaMP6s, we set V∼91 nm 3 [44,46] and τ∼2.5 ns [47]. Since all measurements were performed at room temperature, we use T = 293.15 K and, regarding the medium viscosity, for the water solution we set η∼8.9•10 −4 Pa•s, while for the intracellular environment we set η∼1.2•10 −3 Pa•s [44].…”

VenusA206 Dimers Behave Coherently at Room Temperature

“…Typically, a single component three-dimensional Gaussian diffusion model (34) was used to fit the FCS cross correlation curve, as previously described (35)(36)(37)(38):…”

“…where <N> is the average number of fluctuating fluorescent molecules in the excitation/detection volume, t D is the correlation time (i.e., the average time a molecule spends in the excitation/detection volume), t represents the lag time, and u and z are the radial and axial beam waists, respectively, and g, a volume shape factor, is assumed to have a value of 0.35. Lifetime normalized brightness was measured by auto-fluorescence polarization and fluctuation analysis, as previously described (38). The average number of fluctuating fluorescent molecules, <N>, in Eq.…”

A Guide to Fluorescence Lifetime Microscopy and Förster's Resonance Energy Transfer in Neuroscience

“…Furthermore, multiplexed optical signals can be isolated based on the fluorophore's spectral emission profile, its spectral absorption profile, its lifetime profile, or a combination of these traits. This reduction in spectral bandwidth requirements is even more striking for applications that monitor multiple homo-FRET-based biosensors (Bunt & Wouters, 2017;Ross et al, 2018;Warren et al, 2015), and potentially in applications simultaneously monitoring homo-FRET and hetero-FRET based sensors using simultaneous FLIM and time-resolved anisotropy measurements (Nguyen, Puhl, Pham, & Vogel, 2018) Other exciting FLIM-FRET applications involve combining FLIM-FRET microscopy with other advanced optical imaging techniques. For example, in a recent report, a wide-field TCSPC-based fluorescence lifetime imaging was combined with a light-sheet illumination configuration for rapid 3D lifetime imaging (Hirvonen et al, 2020).…”

“…Furthermore, multiplexed optical signals can be isolated based on the fluorophore's spectral emission profile, its spectral absorption profile, its lifetime profile, or a combination of these traits. This reduction in spectral bandwidth requirements is even more striking for applications that monitor multiple homo‐FRET‐based biosensors (Bunt & Wouters, 2017; Ross et al., 2018; Warren et al., 2015), and potentially in applications simultaneously monitoring homo‐FRET and hetero‐FRET based sensors using simultaneous FLIM and time‐resolved anisotropy measurements (Nguyen, Puhl, Pham, & Vogel, 2018)…”