Biochemistry
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Utilizing Time-Resolved Protein-Induced Fluorescence Enhancement to Identify Stable Local Conformations One α-Synuclein Monomer at a Time
Chapters
Summary May 30th, 2021
Time-resolved single-molecule protein-induced fluorescence enhancement is a useful fluorescence spectroscopic proximity sensor sensitive to local structural changes in proteins. Here we show it can be used to uncover stable local conformations in α-Synuclein, which is otherwise known as globularly unstructured and unstable when measured using the longer range FRET ruler.
Transcript
Single-molecule, protein-induced fluorescence enhancement can compliment single-molecule FRET measurements when studying protein structural subpopulations and conformations, especially in cases when distinct structural subpopulations report on stable local structures. The main advantage of this technique is that it captures distinct site-specific structural sub-populations based on the vicinity of the dye labeling site to the protein surfaces. Single-molecule, protein-induced fluorescence enhancement can be applied to any biomolecular system of interest to probe distinct, local, structural subpopulations.
Begin by preparing 25 picomolar Sulfo-Cy3-labeled alpha-synuclein in measurement buffer in a low-protein binding tube. Add 100 microliters of one milligram per milliliter BSA to the 18-chamber microscopy cover slide and incubate for one minute, then, discard the BSA. Add 100 microliters of 25 picomolar Sulfo-Cy3-labeled alpha-synuclein sample into the chamber of the cover slip slide.
Next, for the data acquisition, add a drop of ultrapure water on the top of the high-numerical-aperture water immersion objective lens, fix the cover slip slide in the stage chamber, and then install the assembly on the top of the microscope stage. Bring the objective lens upwards until the water droplet on top of the objective lens smears at the bottom of the cover slip slide, and open the laser shutter. When the objective lens moves upward, inspect the pattern of the airy rings on a CCD camera.
The first ring represents the focus at the water/glass interface, and the second ring represents the focus at the interface between the glass and the sample solution. Increase the height of the objective lens by 75 micrometers to bring the laser focus deep in the solution for minimizing the autofluorescence from the glass surface of the cover slip. Tune the laser power at the objective lens approximately 100, microwatts.
Start the acquisition of the detected photons for a predefined time. Open the Jupyter Notebooks, then open the sample notebook. Load the FRETBursts and Photon-HDF5 data file.
Use the histogram of the interphoton times to calculate the background rates for every 30 seconds of data acquisition. Move a time window of one photon at a time for 20 consecutive photons, and collect the photon data if the instantaneous photon rate F is at least 11 times larger than the background rate for that period of the data acquisition. Calculate the burst size and amount of photons in a burst, the burst duration, the time difference between the last and first photon detection times in a burst, the burst brightness, the largest value of the instantaneous photon rate in a burst, and the burst separation, the time interval between consecutive bursts.
Plot the histogram of burst brightness values with the events axis in a logarithmic scale. Define the burst brightness threshold as the minimum burst brightness value from which the histogram exhibits a decaying pattern, and selects the bursts with brightness values larger than the burst brightness threshold. For the burst mean fluorescence lifetime measurement, plot the histogram of photon nanotime for all photons in the selected bursts with the photon counts axis in a logarithmic scale.
Define the nanotime threshold as the minimum nanotime value from which the histogram of photon nanotimes exhibits a decaying pattern. Select only those photons with nanotimes larger than the nanotime threshold. Calculate the algebraic average of all the selected photon nanotimes.
Subtract the nanotime threshold from the photon nanotime algebraic average. The obtained value is the mean photon nanotime of the burst, directly proportional to the mean fluorescence lifetime. Plot the histogram of all the burst mean fluorescence lifetimes.
The centrally-distributed subpopulations of fluorescence lifetime may appear. The subpopulations with lower-value averages represent the molecular species with Sulfo-Cy3 that were not sterically obstructed, while the subpopulations with higher-value averages represent the molecule species with S-Cy3 that were more sterically obstructed. For the slow, between-burst dynamics assessment, plot the histogram of the burst separation times with a separation time axis in a logarithmic scale.
Select to save all the pairs of the consecutive bursts that are separated by less than a maximal separation time that defines the same-molecule subpopulation. Plot a histogram or a scatterplot of the mean fluorescence lifetimes of the first and second bursts for all pairs of the bursts that recurred below a certain separation time threshold. The histograms of the mean fluorescence lifetimes of a single, S-Cy3-labeled, alpha-synuclein-56 molecule showed that the first subpopulation had a characteristic fluorescence lifetime of 1.6 nanoseconds, and representing alpha-synuclein conformational states with few protein surfaces in the vicinity of residue 56.
The second subpopulation had a characteristic fluorescence lifetime of 3.5 nanoseconds and representing alpha-synuclein conformational states with more protein surfaces in the vicinity of residue 56. The non-amyloid beta component segments of alpha-synuclein molecules are known to adopt a helical, hairpin structure upon binding to SDS vesicles, which was confirmed as a single florescence lifetime population with a characteristic lifetime of approximately three nanoseconds, and absence of the subpopulation with the characteristic lifetime of 1.6 nanoseconds. The histogram of the separation times between consecutive, single-molecule bursts reports recurring molecules for the separation times faster than 100 milliseconds, where the first and second bursts arise from the same molecule.
The mean fluorescence lifetime histogram of all single molecule-bursts showed subpopulations with a short characteristic lifetime, as well as with a long characteristic lifetime, which indicates that individual molecules could undergo transitions between different average lifetime values slower than burst duration times. Within burst separation times of 100 milliseconds at most, there was a fraction of molecules that started as a first burst in the short-lifetime subpopulation, and recurred as a second burst within the long-lifetime subpopulation. While the fraction of molecules that started as a first burst in the long-lifetime subpopulation, and recurred as a second burst within the short-lifetime population, indicates the transitions between the two subpopulations within 10 to 100 milliseconds.
The most important thing to remember when analyzing the experimental results is to properly separate single-molecule fluorescence signals from background, and to analyze bursts with enough photon nanotimes. Development of smPIFE paved the way for researchers to explore nucleic acid protein interactions at the single-molecule level. This advancement lays the ground for studying local structural dynamics within proteins.
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