The FLINC (fluorescence fluctuation increase upon contact) platform — in which proximity of the photoswitchable fluorescent protein Dronpa to TagRFP-T increases TagRFP-T's fluorescence fluctuations, read out pixelwise by pair-correlation stochastic optical fluctuation imaging (pcSOFI) — enabled the first super-resolution imaging of dynamic enzymatic activity (protein kinase A microdomains) in living cells, but its 2017 introduction explicitly left the method non-quantitative, narrow, and slow: normalized pcSOFI values are ordinal and cannot report absolute molecular distances; the FLINC effect was demonstrated for a single fluorescent-protein pair with no systematic orientation/linker design rules; temporal resolution is limited to tens of seconds by fluctuation statistics; the effects of biosensor diffusion and phosphatase accessibility on measured microdomains were uncharacterized; and whether the resulting activity architecture generalizes across other cell types, signaling pathways, and physiological stimuli remained unexamined.

Background

Optical microscopy of living cells is diffraction-limited to roughly half the wavelength of visible light (~200–250 nm laterally), while most signaling proteins and their regulators interact on the 1–100 nm scale. Super-resolution microscopy overcomes this limit: single-molecule localization microscopy (SMLM, e.g. PALM/STORM) exploits stochastic on/off switching (blinking) of fluorophores, and stimulated emission depletion (STED) shrinks the effective point-spread function with a second laser. Separately, genetically encoded fluorescent biosensors — engineered proteins that couple a molecular recognition event, such as phosphorylation of a kinase substrate, to a change in fluorescence of fused fluorescent proteins (FPs) — report biochemical activities in real time in living cells, most classically via Förster resonance energy transfer (FRET), the distance- and orientation-dependent energy transfer between two FPs that acts as a molecular ruler on the ~2–10 nm scale. Combining the two — visualizing enzymatic activity, not just molecular structure, at super-resolution in living cells — has been difficult because most biosensor readouts do not produce the fluorophore blinking that localization microscopy requires.

Mo et al. (2017) addressed this with FLINC, 'fluorescence fluctuation increase upon contact': proximity of the photoswitchable green FP Dronpa to the red FP TagRFP-T increases TagRFP-T's fluorescence fluctuations in a distance-dependent manner, and this fluctuation contrast is extracted by super-resolution optical fluctuation imaging (SOFI), which computes spatiotemporal cumulants of intensity fluctuations so that stochastically flickering emitters yield sub-diffraction images. The pair-correlation variant used for biosensing, pcSOFI, was introduced by Dedecker et al. (2012). Fusing kinase substrates and phosphoamino-acid-binding domains to the Dronpa/TagRFP-T pair produced the FLINC-AKAR biosensors, which resolved protein kinase A (PKA) activity microdomains on the plasma membranes of living cells and showed that these activity hotspots co-cluster with, and depend on, the scaffolding protein AKAP79 (an A-kinase anchoring protein that tethers PKA near its substrates). The results suggested that cellular biochemistry is spatially organized into a nanoscale 'activity architecture'.

The authors explicitly identified what the demonstration did not achieve. First, normalized pcSOFI values are ordinal (rank-order) measures of proximity or activity: absolute pcSOFI depends on biosensor expression level, camera gain, and excitation intensity, so pcSOFI cannot yet report absolute intermolecular distances, and quantitative calibration methods remain to be developed. Second, FLINC was demonstrated with only one FP pair (Dronpa/TagRFP-T); which other FP pairs or engineered mutants can reproduce or extend the effect, and how FP orientation and linker design can be systematically optimized across different sensor backbones, was left open. Third, temporal resolution is limited by the need to accumulate sufficient fluctuation statistics (the implementation acquired 4 s of data per 30-s interval), so tracking rapid signaling events requires faster, more sensitive detectors or algorithmic advances in fluctuation analysis. Fourth, although biosensor diffusion did not appreciably distort the reported measurements, the quantitative impact of biosensor diffusion and of local phosphatase accessibility (phosphatases reset phosphorylation-based biosensors) on measured microdomain size and amplitude needed characterization in varied cellular environments. Finally, the generality of activity-microdomain organization across other cell types, signaling pathways, and physiological stimuli remained to be explored. These five strands form one coherent methodological objective: turning a single successful demonstration into a general, quantitative, and temporally resolved live-cell nanoscopy of biochemical activity.

Problem Statement

Can fluorescence-fluctuation-based, genetically encoded biosensing — the FLINC/pcSOFI platform introduced by Mo et al. (2017) — be made into a general, quantitative, and temporally resolved method for super-resolution imaging of biochemical activity in living cells? Each of the following components contributes to this single objective, as acknowledged by the source; the strands are independently attackable, so a rigorous resolution of any one of them, or a demonstration that it cannot be resolved as stated, is a valid solution, and the remaining strands need not be addressed: (1) develop quantitative calibration methods that convert normalized pcSOFI/FLINC values into absolute intermolecular separations, removing their dependence on biosensor expression level, camera gain, and excitation intensity, which currently make the readout ordinal only; (2) determine which fluorescent-protein pairs or engineered mutants beyond Dronpa/TagRFP-T can reproduce or extend the FLINC effect, and establish how fluorescent-protein orientation and linker design can be systematically optimized across different sensor backbones; (3) improve temporal resolution so that rapid signaling events can be tracked beyond the ~30-s intervals (4 s of fluctuation data each) of the original implementation; (4) quantify the impact of biosensor diffusion and of local phosphatase accessibility on the measured size and amplitude of activity microdomains in varied cellular environments; and thereby (5) determine whether the organization of biochemical activities into microdomains and activity architectures, demonstrated for PKA/AKAP79 in the cell types studied, generalizes across other cell types, signaling pathways, and physiological stimuli.

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