1. Cell Culture
Use sterile culture tubes and pipette tips. The E. coli strain AB1157 polA-PAmCherry carries a C-terminal PAmCherry fusion of Pol1. The fusion was inserted at the native chromosomal location by replacing the wild-type gene using lambda-Red recombination as described in Datsenko et al.8 Functionality of the fusion protein was confirmed as judged by cellular growth rates and sensitivity to the DNA damaging agent methyl methanesulfonate (MMS). More information on construction of the cell strain can be found in Uphoff et al.7, Datsenko et al.8, and Reyes-Lamothe et al.9 Cell cultures are grown in M9 minimal medium to reduce autofluorescence and avoid background particles on the microscope slide. Alternatively, a nutrient-rich defined medium can be used10.
2. Microscope Slide Preparation
3. Preparing Microscopy Data Acquisition
PALM relies on the detection and precise localization of single fluorescent proteins. The sensitivity and optimal alignment of the microscope is critical for the data quality. Single-molecule fluorescence microscopes typically employ Total Internal Reflection (TIR) illumination to enhance the signal-to-noise ratio by exciting only fluorophores within a thin section above the coverslip surface. Here, imaging inside E. coli requires highly inclined illumination11, which can be achieved on a TIRF microscope by slightly decreasing the angle of the excitation light. PAmCherry imaging further requires a 405 nm photoactivation laser and a 561 nm excitation laser. The fluorescence emission is recorded on an electron multiplying CCD (EMCCD) camera at a magnification resulting in a pixel length of 114.5 nm/pixel. For optimal localization precision, the pixel size should approximately match the standard deviation width of the PSF to ensure sufficient sampling without spreading the signal over too many pixels. Figure 3 shows a schematic of a minimal PALM setup. Movie 1 gives an impression of the bespoke microscope building process; see Uphoff et al.7 for a detailed description of the instrument.
4. Data Acquisition
Here, we describe the general protocol for acquisition of a PALM movie. The same procedure applies for imaging Pol1-PAmCherry fusion proteins in undamaged E. coli cells and under continuous DNA damage treatment with MMS. Application of the method to fusion proteins of different molecular weight or copy number per cell will require different acquisition settings (see Discussion section).
5. Data Analysis
An automated and robust data analysis framework is essential for the performance and efficiency of the method. We use custom software written in MATLAB.
The concept of photoactivated single-molecule tracking to study protein-DNA interactions in vivo is illustrated in Figure 1. PAmCherry fusion proteins are detected in live E. coli cells in a sequential manner by photoactivating single molecules stochastically with 405 nm light at a frequency of less than one molecule per cell at a time. Activated molecules are imaged under continuous 561 nm excitation. Molecular movement in the cell can be tracked by connecting nearby localizations in a series of frames until irreversible photobleaching. Because the diffusion of DNA-binding proteins is slowed upon binding the chromosome, the apparent diffusion coefficient D* obtained per track directly reports on individual protein-DNA interactions.
Figure 2 demonstrates photoactivation of Pol1-PAmCherry fusion proteins in live E. coli cells. The influence of the 405 nm intensity on the density of fluorescent molecules can be seen in Figure 4. Note that the density is not solely determined by the 405 nm intensity but additionally by the number of molecules that are available for activation; the pool of remaining molecules is depleted over the course of a PALM movie.
Localization analysis is performed for each frame of a PALM movie as illustrated in Figure 5. We measured the localization precision using immobile molecules in fixed cells or bound molecules in live cells. Our acquisition settings gave a localization precision of σloc = 40 nm, in agreement with the theoretical prediction3.
The resulting Pol1 localizations occupy the central area of the cell (Figure 6A), broadly recapitulating the spatial organization of the E. coli nucleoid7. The majority of Pol1 tracks in undamaged cells display diffusion as shown in Figure 6C. A typical cell contains several hundred Pol1 tracks (Figure 6D), consistent with the copy number of approximately 400 Pol1 molecules per E. coli cell1. Figures 6B and 6E-F provide guidance on choosing a suitable tracking window parameter – if the tracking window is too large, different molecules are more likely to become erroneously linked to a track; if the tracking window is too small, tracks with longer steps will be split. The MSD curve for Pol1 rises linearly for short lag times and saturates at longer lag times due to cell confinement (Figure 6G). Different types of molecular motion can be identified by MSD analysis. Directed motion gives a parabolic curve; Brownian motion is characterized by a straight line; the confined diffusion curve reaches a plateau; an offset of the MSD curve for immobile particles represents the localization uncertainty (Figure 6H). Additional information on single-particle tracking and troubleshooting tips can be found in Arnauld et al.16
We previously applied the method to measure the DNA-repair activity of Pol1 in response to exogenous DNA alkylation damage7. The D* histogram of Pol1 tracks in undamaged cells shows a dominant population of diffusing molecules (Figures 7A-C). A small fraction of 2.7% bound Pol1 molecules is likely involved in lagging strand replication and repair of endogenous DNA damage. Under continuous 100 mM MMS damage, the population of tracks with D* ~ 0 µm2/sec increases to 13.8% (Figure 7D). These tracks represent individual Pol1 molecules performing DNA repair synthesis to fill single-nucleotide gaps as part of the base-excision repair pathway. The positions of bound tracks show the locations of individual DNA damage and repair sites (Figure 7E-F).
Figure 1. Graphical representation of the method. (A) The fluorescent protein PAmCherry can be photoactivated from an initial nonfluorescent state upon irradiation with 405 nm light. The bright state is excited at 561 nm and emits fluorescence around 600 nm until the fluorophore bleaches irreversibly. (B) Controlling the photoactivation rate allows imaging only a single stochastically activated PAmCherry fusion protein per cell at any time while the arbitrarily large pool of molecules that have not yet been activated or have already been bleached remains in a dark state. (C) The position of the fluorescent molecule is determined from the center of the isolated PSF and tracked for several frames until photobleaching. (D) Tracks of many molecules are recorded in a sequential manner. (E-F) The interaction of a DNA-binding protein with a chromosomal target sequence or structure halts the random diffusive motion. Bound and unbound molecules are distinguished by the apparent diffusion coefficient D* extracted from single tracks. The resulting fraction of bound molecules gives a quantitative measure for the activity of a DNA-binding protein in vivo. Click here to view larger image.
Figure 2. Photoactivation of Pol1-PAmCherry in live E. coli cells. Scale bars: 1 µm. Schematics are shown underneath each panel. (A) Transmitted light microscopy image of cells immobilized on an agarose pad. (B) Phototactivating a single PAmCherry fluorophore in one cell. (C) A higher photoactivation rate increases the number of fluorescent molecules. (D) Integrated PAmCherry fluorescence from a PALM movie. Click here to view larger image.
Figure 3. Schematic of a minimal PALM setup for photoactivating and imaging PAmCherry fusion proteins. D1: Dichroic mirror (e.g. 550 nm long-pass). D2: Dichroic mirror (e.g. 570 nm long-pass). L1: Collimating lens. L2: TIR lens. L3: Tube lens. Click here to view larger image.
Figure 4. Representative images from a PALM movie with 15.26 msec/frame. Scale bars: 1 µm. (A) Transmitted light image of cells immobilized on an agarose pad. (B) Dark background image measured on the EMCCD camera with the lasers switched off. (C) Excitation background image under continuous 561 nm excitation before photoactivation. (D-F) Increased 405 nm intensity leads to higher photoactivation rates of PAmCherry, imaged under continuous 561 nm excitation. The boxed areas are shown magnified below. (D) Low 405 nm intensity (<1 µW) actives very few fluorescent molecules per FOV. (E) Medium 405 nm intensity (~2 µW) photoactivation results in a good PSF density for localization and tracking analysis. (F) Higher 405 nm intensity (~10 µW) activates more than one fluorescent molecule in some cells, which obscures localization and tracking analysis. Click here to view larger image.
Figure 5. Illustration of the localization analysis. Scale bars: 1 µm. (A) Band-pass filtering removes spurious pixel noise and flattens intensity gradients across the FOV. (B) Candidate PSFs are identified in the filtered image based on a user-defined threshold that is chosen to minimize false positive and false negative detections. The threshold corresponds to the minimum intensity of a candidate pixel divided by the background standard deviation (signal-to-noise ratio, SNR). (C) The locally brightest pixel that passes the threshold serves as initial localization guess (orange cross) for a two-dimensional elliptical Gaussian fit. Scale bars: 0.5 µm. The resulting super-resolution localization (blue cross) has an average precision of σloc = 40 nm. Click here to view larger image.
Figure 6. Illustration of the tracking analysis. Scale bars: 1 µm. (A) All detected localizations of Pol1-PAmCherry in an example cell. (B) Number of tracks detected in the example cell as a function of the tracking window. Small tracking windows split molecule trajectories, which leads to artifactual high number of tracks. The dashed line indicates our choice for the tracking window parameter (0.57 µm, 5 pixels) - this gives a good compromise between detecting the full distribution of steps and keeping the trajectories of different molecules intact. (C) Example track of a single Pol1-PAmCherry molecule. (D) All measured tracks shown in random colors. (E) Tracking artifacts if the tracking window is chosen too large (here 0.8 µm, 7 pixels) or the density of PSFs per frame is too high. (F) Cumulative distributions of the step lengths for tracking windows: 0.34 µm (3 pixels, red line), 0.57 µm (5 pixels, blue line), and 0.80 µm (7 pixels, green line). Note that the 0.34 µm tracking window cuts off steps longer than 0.34 µm which clearly truncates the full distribution of steps. The 0.57 µm tracking window detects almost the same distribution of steps as does the 0.80 µm tracking window. (G) MSD curve shows confined diffusion of Pol1. (H) Schematic MSD curves for directed motion, Brownian motion, confined diffusion, and immobile particles. Click here to view larger image.
Figure 7. Direct measurement of the DNA repair activity of Pol1 in live E. coli cells. Scale bars: 1 µm. (A) Histogram of the apparent diffusion coefficient D* for all tracks of 4 or more steps in a FOV of undamaged cells (N = 4,162 tracks). The population of molecules classified as bound is highlighted in red. (B-C) Tracks of Pol1-PAmCherry are shown on a transmitted light microscopy image. Tracks classified as bound according to their diffusion coefficient are shown in red. (D) D* histogram for Pol1 tracks measured in cells immobilized on an agarose pad with 100 mM MMS and incubated for 20 min before imaging (N = 2,128 tracks). The population of bound molecules engaged in DNA repair is shown in red. (E-F) Pol1-PAmCherry tracks on transmitted light microscopy image showing the tracks of single Pol1 DNA repair events in red. Click here to view larger image.
Movie 1. Building a bespoke PALM setup. Click here to view video.
E.coli strain carrying a chromosomal insertion for a PAmCherry DNA-binding fusion protein | created by Lambda-Red recombination | ||
MEM amino acids | Invitrogen | 11130-051 | minimal medium supplement |
MEM vitamins | Invitrogen | 11120-052 | minimal medium supplement |
Agarose | BioRad | 161-3100 | certified molecular biology grade |
Microscope coverslips No 1.5 thickness | Menzel | BB024060SC | remove background particles by heating slides in furnace at 500 °C for 1h |
Methyl methanesulfonate (MMS) | Sigma-Aldrich | 129925 | CAUTION: toxic |
PALM setup | home-built | described in Uphoff et al. 2013 | |
MATLAB | MathWorks | for data analysis and visualization | |
Localization software | custom-written, available online | http://www.physics.ox.ac.uk/Users/kapanidis/Group/Main.Software.html | MATLAB and C++ software package that can be adapted for localization analysis. Cite Holden et al. 2010 if used in publication. |
Tracking software | available online | http://physics.georgetown.edu/matlab/ | MATLAB implementation by Blair and Dufresne. Cite Crocker & Grier 1996 if used in publication. |
Protein-DNA interactions are at the heart of many fundamental cellular processes. For example, DNA replication, transcription, repair, and chromosome organization are governed by DNA-binding proteins that recognize specific DNA structures or sequences. In vitro experiments have helped to generate detailed models for the function of many types of DNA-binding proteins, yet, the exact mechanisms of these processes and their organization in the complex environment of the living cell remain far less understood. We recently introduced a method for quantifying DNA-repair activities in live Escherichia coli cells using Photoactivated Localization Microscopy (PALM) combined with single-molecule tracking. Our general approach identifies individual DNA-binding events by the change in the mobility of a single protein upon association with the chromosome. The fraction of bound molecules provides a direct quantitative measure for the protein activity and abundance of substrates or binding sites at the single-cell level. Here, we describe the concept of the method and demonstrate sample preparation, data acquisition, and data analysis procedures.
Protein-DNA interactions are at the heart of many fundamental cellular processes. For example, DNA replication, transcription, repair, and chromosome organization are governed by DNA-binding proteins that recognize specific DNA structures or sequences. In vitro experiments have helped to generate detailed models for the function of many types of DNA-binding proteins, yet, the exact mechanisms of these processes and their organization in the complex environment of the living cell remain far less understood. We recently introduced a method for quantifying DNA-repair activities in live Escherichia coli cells using Photoactivated Localization Microscopy (PALM) combined with single-molecule tracking. Our general approach identifies individual DNA-binding events by the change in the mobility of a single protein upon association with the chromosome. The fraction of bound molecules provides a direct quantitative measure for the protein activity and abundance of substrates or binding sites at the single-cell level. Here, we describe the concept of the method and demonstrate sample preparation, data acquisition, and data analysis procedures.
Protein-DNA interactions are at the heart of many fundamental cellular processes. For example, DNA replication, transcription, repair, and chromosome organization are governed by DNA-binding proteins that recognize specific DNA structures or sequences. In vitro experiments have helped to generate detailed models for the function of many types of DNA-binding proteins, yet, the exact mechanisms of these processes and their organization in the complex environment of the living cell remain far less understood. We recently introduced a method for quantifying DNA-repair activities in live Escherichia coli cells using Photoactivated Localization Microscopy (PALM) combined with single-molecule tracking. Our general approach identifies individual DNA-binding events by the change in the mobility of a single protein upon association with the chromosome. The fraction of bound molecules provides a direct quantitative measure for the protein activity and abundance of substrates or binding sites at the single-cell level. Here, we describe the concept of the method and demonstrate sample preparation, data acquisition, and data analysis procedures.