Mechanistic Studies of DNA Replication and Genetic Recombination

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Assembly and dynamics of the bacteriophage T4 homologous recombination machinery

Careful control experiments are critical for PALM imaging. Excitation of bacterial cells with high intensity laser illumination can lead to significant fluorescence background. In some cases this background is just a diffuse fluorescent haze, but in other cases it manifests as bright fluorescent spots, either mobile or stationary, in the cells or in the agarose pad or coverslip.

To assess the possibility of spurious detections of background fluorescence, it is important to image the parent strain of the PAFP fusion under matched imaging conditions. The use of carefully matched imaging conditions is critical; for example, we have observed significantly different levels of background localizations for relatively modest differences in nm photoactivation power. It should also be noted that the level of spurious background localizations varies significantly for different bacterial species [84] and can be affected by the presence of chemical additives like IPTG [81].

In two-color experiments, strains lacking either the PAFP fusion or the marker protein fusion should be imaged to assess possible crosstalk between the channels. Crosstalk in the PAFP channel is most likely from bright, multi-copy marker foci. If such crosstalk proves to be a problem, imaging conditions can be chosen to thoroughly bleach these foci before starting to record the PALM movie. As for all experiments involving fusion proteins, it is important to be mindful of possible artifacts due to the FP. Many FPs have a tendency to oligomerize, having evolved from naturally multimeric proteins [85].

Several studies have characterized the tendency of popular FP and PAFP variants to aggregate, at least under certain conditions [45] [86] [87]. When possible, highly monomeric FPs should be chosen. Another useful control experiment is to image the PAFP alone expressed from the same promoter, or at the same chromosomal locus if possible, to confirm that any observed localization is not driven by the behavior of the PAFP itself.

If there are concerns about aggregation due to the presence of the fluorescent protein, altering the expression level of the fusion by changing the strength of the promoter or using an inducible promoter can help confirm that the localization behavior and other results are not affected. Finally, there are a number of approaches that can be used to validate average localization and two-color colocalization analysis.

To avoid the loss of information due to averaging a heterogeneous population of cells, localization analysis is sometimes performed only for cells within a certain length range, which serves as a proxy for cell cycle state. Alternatively, localization analysis can be filtered by other cellular parameters, such as the number of replication forks, to look for differences within the population of cells. To ensure that apparent colocalization is robust in two-color experiments, the imaging and analysis can be repeated for a different marker protein.

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It can also be helpful to perform the colocalization analysis for a PAFP fusion to a protein that is not expected to colocalize with the marker of interest. This analysis can help distinguish similar average localization patterns from true intra-cell colocalization. For example, although a PAmCherry fusion to the DNA-binding protein HU was localized on average in a similar region of the cell as SSB-mYPet foci, we found little intra-cell colocalization as revealed by radial distribution function analysis [62].

To ensure adequate sampling of data for radial distribution function analysis, it is important to generate a random g r curve for the data set of interest; this random g r curve should be close to 1 for all r values. Large deviations from 1 in the random g r curve indicate that the data set is too small. Another approach that we have found helpful is to simulate multiple random localization distributions for the data set and to analyze the spread in the calculated g r curves to ensure that results are robust.

Particle-tracking PALM and two-color fluorescence imaging in live bacterial cells are powerful and versatile techniques that are providing new insight into the recruitment and action of TLS polymerases and other DNA replication and repair proteins. Careful control experiments, however, are critical for both the biological and imaging aspects of these assays. To ensure that results are physiologically relevant and not artifacts driven by the presence of the FP, it is important to confirm the functionality of PAFP fusions.

As for all single-molecule imaging experiments, it is also necessary to minimize sources of background fluorescence and to validate analysis methods. New in vivo single-molecule imaging and tracking methods that break the diffraction limit are transforming our understanding of complex biological processes, their structural organization and their dynamics inside bacterial cells.

One of the most successful of such methods relies on the combination of single-particle tracking SPT [88] with PALM [63] , a popular localization-based super-resolution imaging technique. Single-molecule tracking experiments typically rely on collecting wide-field images of cells containing molecules proteins, DNAs, lipids, etc. In contrast, if the GFP-protein fusion is fully fluorescent after folding and fluorophore maturation is complete, it is only possible to work with proteins of very low copy number molecules per cell ; another approach is to photobleach many of the proteins to arrive in the molecule-per-cell regime, but this also lowers the statistics obtained per single cell.

A prerequisite of tracking PALM is typically the construction of a fusion of the protein of interest with the PAFP, connected by a small amino acid linker. The choice of linker can impact protein function; in most cases, the linker is chosen from a wide range of sequences that vary in length and flexibility reviewed in Chen [95]. The PAFP can be inserted at either termini or as an internal fusion. However, the C-terminal fusion is the most widely used as it is easier to obtain chromosomally than either the N-terminal or internal fusions. If the C-terminal fusion compromises the protein activity, more challenging protein fusion positions can be explored.

Regardless of the insertion position, protein function should be assayed after every fusion. Unsuccessful fusions of essential genes with PAFP are easily screened by the absence of viable colonies after antibiotic selection on LB-agar plates.


Preparation of bacteria for imaging on agarose pads. To study DNA repair, multiple methods can be undertaken depending on the nature of the DNA repair mechanism studied [19] [62]. Cultures are then diluted , in M9 supplied with 0. The following day, the cells are diluted in fresh M9 media until they reach the early exponential growth phase with OD 0. Suitable DNA-damaging agents for a specific DNA repair pathway are then either incubated with the culture for up to an hour prior to PALM imaging [62] , or are added directly into the agarose pad preparation [19].

Cells are then spun down and immobilized on the lower side of an agarose pad sandwiched between two coverslips. In preparation for single molecule fluorescence microscopy, the coverslips should be burned or sonicated to remove any contaminants that may contribute to the auto-fluorescence background. PALM imaging system. Experiments are performed on a single-molecule fluorescence microscope, with laser illumination used for photoactivation and excitation e.

The mode of illumination is chosen to match the region of the sample being studied. In TIRF microscopy, excitation is generated by an evanescent field which penetrates nm into the sample, limiting the region of study to a shallow depth, but very effectively suppressing background fluorescence. Epifluorescence illumination excites molecules throughout the sample, generating significantly more noise.

Acquisition and reduction of PALM data. The intensity of the photoactivation light is adjusted such that there is a maximum of approximately one fluorescent particle per cell at any given time. A typical tracking PALM experiment lasting 2. A total of 10, frames are acquired during a single experiment.

Initially, each frame is processed separately to extract particle positions Figure 7A , left. Tracks are then identified by linking particle localizations, both spatially and temporally Figure 7A , right. The localization process identifies point spread functions PSFs for each particle within a frame using elliptical Gaussian fitting. Cell tracks are reconstructed by searching for localizations in neighboring frames that fall within a maximum spatial distance; this threshold also depends upon the frame rate.

Cell segmentation is performed using an algorithm that determines the edges of cells present in a bright-field or phase-contrast image taken immediately before the experiment, extracting a set of meshes which define the boundary of each cell within the field of view. The segmentation process, which assigns the localizations to individual cells, may be implemented either before or after the localization and tracking procedures. A Bright-field image of a single E.

B Mean MSD analysis obtained for 2, molecular tracks. C Apparent diffusion coefficient histogram from 2, molecules, calculated from MSDs; the inset numbers indicate the proportion of molecules in each population. D Heat maps of molecular localizations for the bound top , and freely-diffusing bottom populations.

Molecular mobility.

The localizations and reconstructed tracks contain a great deal of information about the underlying processes studied. First, the number of localizations per cell provides an indication of the approximate copy number of the labeled protein.

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This can be used to detect differential expression of the protein of interest by comparing the number of localizations in the original and mutated strains. Further, the traces offer ample information to characterize different types of diffusion.


A popular method for the classification of diffusion modes is based on the MSD obtained from the trajectories of individual molecules. The gradient of the plot of MSD over a range of interval times gives the mobility of the molecular species being studied.

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A linear MSD plot indicates free diffusion, unbounded by a nucleoid or cell periphery, such that the particles obey Brownian motion with random movements originating from collisions with other molecules. It is common for acquired MSD curves to be non-linear, such that the particles exhibit anomalous diffusion. Anomalous diffusion is sub-categorized into either sub-diffusion, where diffusion is either confined geometrically, or limited by molecular interactions; or super-diffusion, where movement is governed by an external process or structure, such as active molecular transport, or cellular tracks.

Immobile molecules exhibit the extreme case of sub-diffusion, however, the resulting MSD is non-zero due to contributions from the localization error which generate apparent movements in the 1—40 nm range , uncorrected microscope drift, cell motion, and cell growth. Further analysis of the MSD enables separate diffusion behaviors to be identified. Uphoff et al. Diffusion constants for each track were then compiled into a histogram Figure 7C , yielding two distinct diffusing populations which represent the bound and diffusing populations of Pol following MMS treatment.

As Pol binds to DNA during the repair process, its kinetics change from the high diffusion constant of the Pol molecules during the search process as it diffuses through the nucleoid, to the lower diffusion constant associated with pol binding to DNA [19].

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  5. In addition to the large aggregated diffusion data generated by tracking PALM, the technique also allows all individual tracks to be interrogated separately. In doing so, they were able to capture timescales for the full search, and repair processes, identifying a mean repair time of 2.

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    Analysis of localizations using clustering algorithms, such as Density Based Spatial Clustering of Applications with Noise DBSCAN , provides unbiased, quantitative identification of molecular clusters [98] , allowing theories regarding the dynamic clustering of protein machinery, such as transcription factories [99] , to be investigated in detail.

    Such a study has already provided early evidence of the absence of an equivalent system in DNA repair [19]. Functionality of the target protein should not be compromised by the PAFP to which it is fused. It is thus important to avoid disrupting functional domains or protein folding. To achieve this, multiple steps can be taken towards a successful fusion. Fusion sites in regions that have previously been documented as crucial for interaction with other proteins or DNA should be avoided.

    Mechanistic Studies of DNA Replication and Genetic Recombination Mechanistic Studies of DNA Replication and Genetic Recombination
    Mechanistic Studies of DNA Replication and Genetic Recombination Mechanistic Studies of DNA Replication and Genetic Recombination
    Mechanistic Studies of DNA Replication and Genetic Recombination Mechanistic Studies of DNA Replication and Genetic Recombination
    Mechanistic Studies of DNA Replication and Genetic Recombination Mechanistic Studies of DNA Replication and Genetic Recombination
    Mechanistic Studies of DNA Replication and Genetic Recombination Mechanistic Studies of DNA Replication and Genetic Recombination
    Mechanistic Studies of DNA Replication and Genetic Recombination Mechanistic Studies of DNA Replication and Genetic Recombination

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