LIVE-PAINT: Super-Resolution Microscopy Inside Live Cells Using Reversible Peptide-Protein Interactions

We present LIVE-PAINT, a new approach to super-resolution fluorescent imaging inside live cells. In LIVE-PAINT only a short peptide sequence is fused to the protein being studied, unlike conventional super-resolution methods, which rely on directly fusing the biomolecule of interest to a large fluorescent protein, organic fluorophore, or oligonucleotide. LIVE-PAINT works by observing the blinking of localized fluorescence as this peptide is reversibly bound by a protein that is fused to a fluorescent protein. We have demonstrated the effectiveness of LIVE-PAINT by imaging a number of different proteins inside live S. cerevisiae. Not only is LIVE-PAINT widely applicable, easily implemented, and the modifications minimally perturbing, but we also anticipate it will extend data acquisition times compared to those previously possible with methods that involve direct fusion to a fluorescent protein.


Introduction
Optical microscopy has traditionally been restricted to a resolution of ~250 nm due to the diffraction limit of light. New methods, collectively grouped under the term superresolution microscopy, have increased the resolution of fluorescence microscopy by almost two orders of magnitude, allowing systems previously inaccessible to fluorescence microscopy to be studied [1][2][3][4][5] . These methods rely on either limiting the illumination of the sample to regions smaller than the diffraction limit 1 , or stochastically and temporally separating the emission of individual fluorophores to allow their positions to be precisely localized. This latter strategy is termed single-molecule localization microscopy (SMLM), and various approaches have been developed to enable the required stochastic emission, including stochastic optical reconstruction microscopy (STORM) 5 , photo-activation localization microscopy (PALM) 2 , and point accumulation for imaging in nanoscale topography (PAINT) 6 .
In the original implementation of PAINT, fluorescent molecules (for example, Nile red) bind transiently and non-specifically to hydrophobic regions of a structure 6 , and a superresolution image is built up as each one is localized. Unlike PALM and STORM methods, which are limited by photobleaching of the dye molecules over time, in PAINTbased methods there is continual replenishment of the fluorescent probes, which allows much longer imaging times, resulting in a higher density of localizations, and the potential for a higher resolution image 7 . In all PAINT methods, the concentration of the interacting fluorescent molecule can be varied and optimized. can be discarded, which also contributes to increased resolution.
DNA-PAINT has seen many variations and innovative applications [8][9][10][11] . A significant limitation, however, is that DNA-PAINT cannot be used to visualize proteins inside live cells 12 . Although extensions of DNA-PAINT, in which the DNA is fused to a nanobody or another protein-binding module, enable intra-cellular proteins to be visualized, the cell must be permeabilized to allow them to enter. As a result, work in live cells has been 6 limited to the visualization of cell-surface proteins 12 . Here, we describe a PAINT-based method that has all the advantages of DNA-PAINT, but with the enormous benefit that it can be used for imaging inside live cells. We refer to this approach as LIVE-PAINT (Live cell Imaging using reVersible intEractions PAINT).
In LIVE-PAINT, reversible peptide-protein interactions, rather than zipping/unzipping of a DNA oligonucleotide duplex, are responsible for the transient localizations required for SMLM. The protein to be imaged is genetically fused to a short peptide and expressed from the protein's endogenous promoter. Additionally, integrated at a suitable place in the genome, a peptide-binding protein is genetically fused to a fluorescent protein (FP) and expressed from an inducible promoter, allowing its expression level to be controlled and optimised. The small size of the peptide tags fused to the protein of interest is another important strength of the method. It enables post-translational fluorescent labeling of target proteins that do not tolerate a direct fusion to a FP. To illustrate this point, we show that LIVE-PAINT can be used to perform in vivo super-resolution imaging of proteins, such as actin and cofilin, which are notoriously refractory to direct fusions 13,14 . Furthermore, we show that LIVE-PAINT can be used to perform diffractionlimited tracking of individual biomolecules for extended periods of time.

LIVE-PAINT achieves super-resolution inside live cells using reversible peptideprotein interactions
The essence of LIVE-PAINT is to visualize individual fluorescent molecules transiently attached to a cellular structure of interest. The individual fluorophores are thus identified by temporal, rather than spatial, separation. LIVE-PAINT achieves sparse labeling by using reversible peptide-protein interactions. The protein of interest is directly fused to a peptide and a FP is fused to the cognate protein ( Figure 1A). The peptide-protein interactions are chosen so that solution exchange occurs on a timescale shorter than or comparable to the bleaching lifetime, allowing many sequential images to be obtained.
In each image, a different peptide-tagged protein of interest is bound to a different protein-FP, allowing individual proteins to be precisely localized ( Figure 1A-D). These localization events are then summed to generate a super-resolution image ( Figure 1E).
As a test case with which to optimize this approach, we visualized the cell division septin protein Cdc12, a component of the readily-identifiable septum that is formed during Saccharomyces cerevisiae budding. We tested LIVE-PAINT using two different peptide-protein interactions with very different dissociation constants and molecular structures: TRAP4-MEEVF (a TPR-peptide pair with a dissociation constant (KD) of 300 nM) and SYNZIP17-SYNZIP18 (an antiparallel coiled coil pair with a KD of 1 nM) [15][16][17][18] . In both cases, the peptide (MEEVF or SYNZIP18) is fused to Cdc12 and the cognate protein or peptide (TRAP4 or SYNZIP17, respectively) is fused to the bright green FP mNeonGreen (mNG) (11). Although mNG is known to blink intrinsically 19 , we chose to use it in our experiments because it is very bright and therefore can produce very precise localization events. mNeonGreen has a brightness of 93 20 , while other FPs we use in this work, mKO and mOrange, have brightness of 31 21 and 49 22 , respectively.
Most importantly, we show that mKO and mOrange, which are not known to blink intrinsically, are also compatible with LIVE-PAINT ( Figure S1 and Supplementary movies 1 and 2). TRAP-peptide pairs have been shown previously to be less perturbative for cellular imaging than direct fusion to a FP 23 . Both TRAP4-MEEVF and SYNZIP17-SYNZIP18, were well-tolerated by the cell, and both can be used for either diffraction limited or super-resolution imaging of the septum in live yeast ( Figure 1E).
We observed no distorted cell morphology or changes in growth rate in liquid media when using the TRAP4-MEEVF and SYNZIP17-SYNZIP18 interaction pairs. In previous work we observed distorted cell morphology for ~5% of yeast expressing a direct fusion of Cdc12 to an FP 23 . We also provide evidence that LIVE-PAINT can be performed with additional peptide-protein interaction pairs ( Figure S2), that the localizations events observed are specific to the protein being labeled ( Figure S3), and that two orthogonal interaction pairs can be used with two FPs to tag two different proteins specifically and concurrently ( Figure S4). 448. Scale bars are 1 μm, except for the inset to (E), which has a 100 nm scale bar.

Low FP expression levels result in a higher percentage of bona fide localization at the septum
In LIVE-PAINT, the peptide-binding proteins fused to mNG (TRAP4-mNG and SYNZIP17-mNG), are expressed from an inducible promoter, so that expression levels can be optimized 24 . See Figure S5 for fluorescence induction profile.
By varying the expression level of either TRAP4-mNG or SYNZIP17-mNG, for the TRAP4-MEEVF and SYNZIP17-SYNZIP18 interaction pairs respectively, we can determine which conditions generate the highest percentage of localizations at the septum relative to non-specific localizations ( Figure 2). For very low expression levels, for example for 0% galactose with 'leaky' expression, not enough mNG is expressed and not enough localization events are achieved to generate a super-resolution image.
Conversely, for example for 0.1% galactose, expression levels are too high and very few individual localization events can be visualized, because the density of mNG is too high to achieve sparse labeling. At intermediate expression levels, for example with 0.005% or 0.02% galactose, there are sufficient FPs that enough localization events can be recorded to resolve a super-resolution image, but the FP expression level is not so high that single localization events cannot be recorded.
We performed cluster analysis using the DBSCAN function (see methods) to quantify the number of localization events in the septum versus in the rest of the cell. We were thus able to identify the conditions that produced the most specific super-resolution images. In an analogous fashion to DNA-PAINT, the FP mNG does not give rise to a localization event until it binds and is immobilized. Some non-specific localization or blinking events are recorded, these are randomly distributed within the cell and can be removed from further analysis by using DBSCAN. The number of these non-specific localization events increases with galactose concentration, because by increasing galactose we increase the number of free mNG which are not bound to a Cdc12 protein.

Septum width increases with increasing yeast daughter:mother diameter ratio
To demonstrate the potential of LIVE-PAINT, we show an example of how it can be used to study a biological structure in live cells. By analyzing SMLM data for Cdc12 in individual cells, obtained using LIVE-PAINT with the SYNZIP17-SYNZIP18 interaction pair, we are able to describe various features of the yeast budding process. For example, we find that for small daughter cell sizes (daughter:mother diameter ratio less than approximately 0.85), the septum width is of the order 200 nm. As the daughter cell gets larger (daughter:mother diameter ratio approximately 0.85 to 1.0), the septum is clearly visible as two separate rings, with a septum width of approximately 400-800 nm.
See Figure S6. This example demonstrates that LIVE-PAINT can be used to study a biological structure in live cells on the single cell level.
Labeling using a construct with three tandem copies of mNG improves localization precision compared to a single copy.
In current super-resolution imaging techniques used inside live cells, such as PALM, the target protein is directly fused to a FP. This fusion adds a large, 25 kDa, modification to the target protein. Trying to enhance the PALM signal by fusing three FPs to the same target protein, would increase the size of the overall protein by about 75 kDa. Many proteins are unable to fold and correctly mature to their functional state when fused to a single FP, therefore a larger modification to a target protein, on the order of 75 kDa would likely be even more detrimental.
With the LIVE-PAINT method, however, the protein of interest is labeled posttranslationally and reversibly. Thus, labeling with multiple tandem FPs should be more feasible. We performed LIVE-PAINT on Cdc12-SYNZIP18 using the SYNZIP17 fused to one or three tandem copies of mNG and compared the super-resolution data obtained for both conditions ( Figures S7 and S8). Cdc12 not only tolerates such posttranslational labeling with the three tandem mNG, but labeling with this construct results in better localization precision. We note, however, that the larger size of the three tandem mNG construct creates additional distance between the protein of interest which would result in increased uncertainty about its actual position.

LIVE-PAINT enables longer data acquisition times
An additional advantageous feature of the LIVE-PAINT method is that it allows bleached fluorescent labels to exchange with unbleached fluorescent labels, in vivo. In the case of STORM and PALM imaging methods, photobleaching of the probe adds a limitation to the number of emitters that can be localized. This photobleaching reduces the resolution of the image because it limits the density of emitters that can be measured.
Thus, researchers have to resort to using localization events with lower signal to noise than is optimal. In many cases, control of the emission is difficult to achieve, and much of the fluorescent probe is bleached early in the acquisition when individual emitters cannot be discerned due to their density being too high, further limiting the density of localizations measured. Here we demonstrate the ability to image for longer periods of time with LIVE-PAINT, using the SYNZIP labeling pair.
When imaging using a conventional direct fusion of Cdc12 to mNG, we observe that after we deliberately photobleach by irradiating with high laser power for two minutes, very few localization events are subsequently observed. In contrast, when using SYNZIP17-SYNZIP18 to localize mNG to Cdc12, after we deliberately photobleach by irradiating with high laser power for two minutes, we subsequently observe many more new localization events, indicating that the bleached SYNZIP17-mNGs can unbind and be replaced by unbleached SYNZIP17-mNGs from the cytoplasm. This result shows that the LIVE-PAINT imaging strategy allows one to obtain more total localization events during an imaging session, because they allow for longer imaging times ( Figure 3). The

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individual cells imaged using LIVE-PAINT for the data in Figure 3 were measured to have a resolution of ~20 nm (see Figure S9 for maximum projection images of the individual cells analyzed in Figure 3).

LIVE-PAINT signal replenishment increases with increasing concentration of FP
The data in Figure 3 shows that reversible interaction pairs can unbind from the target protein and signal can be replenished by free protein-mNG binding to the target protein.
Building on this result, we compared how long data collection can be continued, when there is a high versus low level of peptide-binding protein-mNG in the cytoplasm. Figure   4 shows the results of such experiments for both the SYNZIP17-SYNZIP18 and TRAP4-MEEVF interaction pairs. For 0% galactose, where the expression level of peptidebinding-module-FP is low, almost all the binding-module-FP will be initially bound to Cdc12, thus all FPs will be illuminated and bleached rapidly, because there is not a cytoplasmic pool of peptide-binding-protein-FP for them to exchange with. By contrast, for 0.1% galactose, where the expression level of the peptide-binding protein-FP is high, there is a sizeable cytoplasmic pool available to exchange with molecules bound to peptide-Cdc12, but which have been bleached. In Figure 4B, for example, we observe that when imaging Cdc12-SYNZIP18 + SYNZIP17-mNG using 0.1% galactose, even after 200 s of imaging, localizations are still being recorded at about 30-40% of the initial rate.

LIVE-PAINT can be used to image proteins that are refractory to direct fusion to a large protein
Actin, an important cytoskeletal protein, is notoriously difficult to tag and image. A number of different methods have been developed to circumvent this problem, but they are not without issues, including changing the stability, dynamics, and lifetime of actin structures 13,25,26 . Moreover, very few of these methods can be used inside live cells and none is currently compatible with live cell super-resolution imaging. We therefore investigated if LIVE-PAINT could be used to image actin. Wild-type actin was chromosomally expressed from its endogenous promoter. We expressed SYNZIP18actin from a low copy number plasmid, using a copper-inducible promoter. SYNZIP17-mNG was expressed, as previously, from the galactose inducible promoter, chromosomally integrated at the GAL2 locus ( Figure 5).
Using LIVE-PAINT, we were able to readily visualize actin patches, which assemble at the cell membrane, at sites of endocytosis 27 ( Figure 5A). Because actin structures are quite dynamic, we investigated how quickly we could obtain super-resolution images (compared to the acquisition time of 200 s for the data shown in Fig 5C). Actin rings, or actin cables that span the cell, are likely not observed because we are imaging in TIRF, which illuminates only about 200 nm into the cell (a typical yeast cell is 1-3 μm thick).
Alternatively, or additionally, it could be that the stringent structural requirements for actin in these assemblies means that even actin with very small ~2 kDa tags may be 24 excluded from ring and cable structures 28 . We find that with a data acquisition time as short as 3 s, we can obtain data with a resolution of approximately 50 nm ( Figure S10).

LIVE-PAINT enables long tracking times in vivo
In the data presented so far, we have used LIVE-PAINT to generate super-resolution images of proteins which do not move significantly during the period of data acquisition.
The extended imaging lifetime enabled by LIVE-PAINT, however, offers the opportunity to detect and track the motion of diffusing molecules within live cells. Cofilin is an important protein that binds to actin filaments promoting severing 14 . It has so far, however, proven difficult to image due to its function being affected by either N-or Cterminal direct fusion of an FP 14 . We therefore C-terminally tagged cofilin with SYNZIP18, and tracked it using the LIVE-PAINT strategy (diffraction-limited, not superresolution). We were able to observe the diffusion of cofilin during the 100 s of imaging ( Figure 6 and Supplementary Movie 3). We observed a wide range of behaviors ( Figure   6).
The success of the LIVE-PAINT tagging approach in these examples demonstrates the value of the method for visualizing proteins that are refractory to direct fusion to an FP 14 , and also its potential to be developed to track moving proteins. Finally, LIVE-PAINT, especially in a TIRFM (or LSFM) format, enables data to be acquired for much longer than other current methods (such as PALM) that can be used inside live cells. In such methods, the FP is directly fused to the protein of interest, so once a fluorophore is bleached, it is not replaced and from then onwards is dark. By contrast, in LIVE-PAINT, the non-covalently bound FP can be exchanged after bleaching, with a non-bleached FP from the cytoplasm. Acquiring data for longer results in more localizations being detected and consequently higher resolution images being obtained. Unbound FPs in LIVE-PAINT result in background fluorescence, but this effect can be mitigated by reducing the illumination volume in the cell, as we have done using TIRFM in this work, or by using other strategies, such as light-sheet fluorescence microscopy (LSFM).
We have demonstrated the power of LIVE-PAINT in S. cerevisiae by using it to image Cdc12 and hence to study septum formation. Furthermore, we have used it to image actin and cofilin, two important proteins that are intractable to direct fusion. Finally, we showed that this approach is fundamentally compatible with tracking the movement of individual proteins inside live cells.
We expect that it will be straightforward to extend LIVE-PAINT to other organisms and cell types. In our work we found that two of the three peptide-pairs that we tested were suitable for LIVE-PAINT. Many more potentially compatible interaction pairs exist, and may be better suited for particular applications. In future work, we will investigate how the optimal labeling requirements differ for different cellular proteins and how best to label and image multiple proteins simultaneously.

Molecular biology
All cloning was performed in Escherichia coli strain TOP10. Peptide tags were cloned into pFA6a-KANMX6 by amplifying the plasmid backbone and inserting gBlocks (Integrated DNA Technologies) using NEBuilder ® HiFi DNA Assembly Master Mix (New England Biolabs). Except where otherwise noted, the protein sequence used to link different protein components was GGSGSGLQ. The two residue linker, GS, was used between the mNG proteins to create the three mNG array. The 3xmNG construct itself was joined to SYNZIP17 using our standard GGSGSGLQ linker.
Peptide-binding proteins fused to FPs were cloned into the pFA6a-HIS3MX6 and tagged actin constructs were cloned into the pCu415CUP1 vector (CEN6/ARS4 origin of replication) using the methods referenced above.
The linker used to fuse actin to SYNZIP18 or MEEVF was GGSGSG.
Primer sequences used in this study are listed in Tables S3, S4, and S5.

Yeast strain construction
Except where otherwise noted, standard methods for genetically modifying yeast and preparing growth media were used 34 . The yeast strains and selection markers used in this study are listed in Table S2.
Yeast strains constructed in this study are all derived from the parent strain BY4741. Transformants were selected by plating first on YPD plates and then replica plating to yeast agar plates including 600 mg/L geneticin (Gibco) and incubating for a further 16 hours.
FP fusions were inserted into the yeast genome at the GAL2 locus by amplifying the desired protein's sequence from a plasmid. The amplification primers also included 45 bp homology arms that match sequences upstream and downstream of the GAL2 gene, and the HIS3 gene.
Transformants were selected by plating on synthetic complete agar plates lacking histidine.
Strain construction was verified by PCR amplification of the modified locus (using primers from Table S3).

Microscopy
For imaging experiments, yeast cells were grown overnight in 500 μL of synthetic complete media. Constructs using the galactose inducible promoter, pGAL1, were all grown with 1% w/v raffinose plus the concentration of galactose desired for a particular experiment. The concentration of galactose used varied between 0% and 2% w/v. One colony was picked into a 500 μL overnight culture to ensure that the OD600 of the cells was between 0.1 and 0.5 by the time of imaging. Two dilutions of the overnight culture, 1:1 and 1:5, were prepared to ensure that one would fall in this OD600 range.
22x22 mm glass coverslips with thickness no. 1 (VWR) were cleaned by a 20 minute exposure in a 2.6 L Zepto plasma laboratory unit (Diener Electronic). Frame-Seal slide chambers (9 × 9 mm 2 , Biorad, Hercules, CA) were then secured to a coverslip. The surface was prepared for the attachment of yeast cells by coating the surface with 2 mg/mL concanavalin A (Sigma-Aldrich), which was dissolved in PBS pH 7.4, using approximately 100 μL per well. After leaving the concanavalin A on the surface of the slide for 30 seconds, it was removed using a pipette tip and by tilting the slide to ensure all liquid was removed. Then, 150 μL of prepared yeast culture was pipetted onto the slide. The yeast culture was left to sit on the slide for approximately 5 minutes. The cells were then aspirated from the slide, the surface washed with milliQ water three times, and then 150 μL fresh milliQ water was then added to the slide before imaging.
Single-molecule imaging was performed using a custom-built TIRF microscope, which For photobleach-and-recovery experiments we first imaged the samples at very high laser power density (26.6 W/cm 2 ). After 1,000 frames (50 s) of imaging, this power density was dropped to 3.1 W/cm 2 . The sample was then imaged for another 1,000 frames (50 s).

Microscope settings/Imaging parameters
Images were analyzed using Fiji and single localizations were processed using the Peak Fit function of the Fiji GDSC SMLM plugin, using a signal strength threshold of 30, a minimum photon threshold of 100, and a precision threshold of 20 nm. The precision threshold was sometimes changed to 30 nm, 40 nm, or 1000 nm, in order to obtain the distribution of precision values for all obtained localization events. Figure S12 shows a matrix of precision and minimum photons per localization thresholds applied to one stack of images, which helped select the cutoffs used.

Image resolution calculation
Image resolution was calculated by first performing cluster analysis using DBSCAN 35 in Python 2.7 to identify localizations in the yeast bud neck. Then, resolution was measured using the equation !"" = #( ̅ ## ) $ + ( *) $ , where Reff is the effective image resolution, ̅ ## is the mean nearest neighbor distance between localizations in the septum, and * is the average localization precision 36 .

Cluster analysis for identifying yeast septum
For the images shown in Figure 2, septum localizations were identified from total cellular localization events using DBSCAN 35 in Python 2.7 and the percent of total cellular localizations in the septum was determined. In order to prevent misidentification of septa in background localizations, DBSCAN was applied to localizations within a 1 μm radius of the center of the cell. DBSCAN parameters were maintained for images of cells the same galactose concentration: 0% galactose -ε = 2, N = 25; 0.005% galactose -ε = 2, N = 50; 0.02% galactose -ε = 1.75, N = 50; 0.1% galactose -ε = 2.8, N = 75.

Quantifying septum width
Budding yeast with septa were identified from z-projections and following thresholding, ImageJ's Analyze Particles tool was used to determine: the maximum Feret's diameter of the cell, the starting coordinates of the Feret's diameter, the angle between the Feret's diameter and the x-axis, and the coordinates of the cellular center of mass. The end coordinates of the Feret's diameter were calculated from the Feret's diameter data.
In the same cells, septum localizations were identified from total cellular localization events as described in above cluster analysis within a radius of the Feret's diameter/5 from the cell's center of mass and using parameters of ε = 2, N = 100.
The distance between the center of the septum points and the coordinates of both the start and end of the Feret's diameter was determined and the larger of the two was taken to be the mother cell diameter and the smaller, the daughter cell diameter.
To find the septum width, the mean absolute perpendicular distance between all the septum localizations and the line bisecting the angle between the center of the septum, and the mother and daughter diameters was doubled.

Plate reader measurements
Plate reader measurements were carried out on a POLARstar Omega microplate reader (BMG LABTECH). To observe the galactose dependent induction of mNG under the pGAL1 promoter in a Δgal2 background, budding yeast cells were grown overnight in 500 μL of synthetic complete media plus 1% w/v raffinose and galactose concentrations ranging from 0 to 0.1% w/v. The next morning, 200 μL of this culture was added to individual wells in a 96 well clear bottom plate (Greiner bio-one, item 655096). Cellular fluorescence was excited using the 485 nm excitation filter and measured using the 520 nm emission filter.
The optical density of the cells was measured using the absorbance setting at 600 nm.
The fluorescence readings were then normalized to the number of cells by dividing the measured cellular fluorescence by the optical density.