Image Correlation Spectroscopy is a Robust Tool to Quantify Cellular DNA Damage Response
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eLife Assessment
This valuable paper shows image correlation spectroscopy (ICS) as a new tool to analyze the clustering of proteins involved in DNA damage response (DDR). The solid evidence presented demonstrates that this method is more sensitive than traditional focus counting, although some of the claims require further contextualization. This new method provides an alternative tool to analyze immuno-stained focus for researchers in the fields of DDR and cell biology.
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Abstract
The DNA Damage response (DDR) is both essential and highly complex. Evaluating the DDR is a critical aspect of cell biology. Counting DNA damage foci is one of the most common approaches to study the DDR. Yet, quantification of protein foci suffers from experimental limitations, subjectivity of analysis and is restricted to a handful of the hundreds of DDR proteins. Here we apply image correlation spectroscopy (ICS) to quantify the local clustering at sites of DNA damage directly. We found that ICS outperformed foci counting of traditional DDR markers and enabled quantification of other markers without the complex labeling procedures that are otherwise required. ICS analysis also provided insight into DDR protein recruitment that was previously undetectable. Further expansion incorporating analysis to cell cycle classification demonstrates a rapid, non-biased approach to fully study the DNA damage response within cells. ICS analysis presents an objective, quantitative image analysis technique to study the DNA damage response in unaltered cells that we expect will significantly enhance quantitative DNA damage response research.
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eLife Assessment
This valuable paper shows image correlation spectroscopy (ICS) as a new tool to analyze the clustering of proteins involved in DNA damage response (DDR). The solid evidence presented demonstrates that this method is more sensitive than traditional focus counting, although some of the claims require further contextualization. This new method provides an alternative tool to analyze immuno-stained focus for researchers in the fields of DDR and cell biology.
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Reviewer #1 (Public review):
Summary:
This manuscript assesses the utility of spatial image correlation spectroscopy (ICS) for measuring physiological responses to DNA damage. ICS is a long-established (~1993) method similar to fluorescence correlation spectroscopy, for deriving information about the fluorophore density that underlies the intensity distributions of images. The authors first provide a technical but fairly accessible background to the theory of ICS, then compare it with traditional spot-counting methods for its ability to analyze the characteristics of γH2AX staining. Based on the degree of aggregation (DA) value, the authors then survey other markers of DNA damage and uncover some novel findings, such as that RPA aggregation inversely tracks the sensitivity to PARP inhibitors of different cell lines.
The need for a more …
Reviewer #1 (Public review):
Summary:
This manuscript assesses the utility of spatial image correlation spectroscopy (ICS) for measuring physiological responses to DNA damage. ICS is a long-established (~1993) method similar to fluorescence correlation spectroscopy, for deriving information about the fluorophore density that underlies the intensity distributions of images. The authors first provide a technical but fairly accessible background to the theory of ICS, then compare it with traditional spot-counting methods for its ability to analyze the characteristics of γH2AX staining. Based on the degree of aggregation (DA) value, the authors then survey other markers of DNA damage and uncover some novel findings, such as that RPA aggregation inversely tracks the sensitivity to PARP inhibitors of different cell lines.
The need for a more objective and standardized tool for analyzing DNA damage has long been felt in the field and the authors argue convincingly for this. The data in the manuscript are in general well-supported and of high quality, and show promise of being a robust alternative to traditional focus counting. However, there are a number of areas where I would suggest further controls and explanations to strengthen the authors' case for the robustness of their ICS method.
Strengths:
The spatial ICS method the authors describe and demonstrate is easy to perform and applicable to a wide variety of images. The DDR was well-chosen as an arena to showcase its utility due to its well-characterized dose-responsiveness and known variability between cell types. Their method should be readily useable by any cell biologist wanting to assess the degree of aggregation of fluorescent tags of interest.
Weaknesses:
The spatial ICS method, though of longstanding history, is not as intuitive or well-known as spot-based quantitation. While the Theory section gives a standard mathematical introduction, it is not as accessible as it could be. Additionally, the values of TNoP and DA shown in the Results are not discussed sufficiently with regard to their physical and physiological interpretation.
The correlation of TNoP with γH2AX foci is high (Figure 2) and suggestive that the ICS method is suitable for measuring the strength of the DDR. The authors correctly mention that the number of spots found using traditional means can vary based on the parameters used for spot detection. They contrast this with their ICS detection method; however, the actual robustness of spatial ICS is not given equal consideration.
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Reviewer #2 (Public review):
Summary:
Immunostaining of chromatin-associated proteins and visualization of these factors through fluorescence microscopy is a powerful technique to study molecular processes such as DNA damage and repair, their timing, and their genetic dependencies. Nonetheless, it is well-established that this methodology (sometimes called "foci-ology") is subject to biases introduced during sample preparation, immunostaining, foci visualization, and scoring. This manuscript addresses several of the shortcomings associated with immunostaining by using image correlation spectroscopy (ICS) to quantify the recruitment of several DNA damage response-associated proteins following various types of DNA damage.
The study compares automated foci counting and fluorescence intensity to image correlation spectroscopy degree of …
Reviewer #2 (Public review):
Summary:
Immunostaining of chromatin-associated proteins and visualization of these factors through fluorescence microscopy is a powerful technique to study molecular processes such as DNA damage and repair, their timing, and their genetic dependencies. Nonetheless, it is well-established that this methodology (sometimes called "foci-ology") is subject to biases introduced during sample preparation, immunostaining, foci visualization, and scoring. This manuscript addresses several of the shortcomings associated with immunostaining by using image correlation spectroscopy (ICS) to quantify the recruitment of several DNA damage response-associated proteins following various types of DNA damage.
The study compares automated foci counting and fluorescence intensity to image correlation spectroscopy degree of aggregation study the recruitment of DNA repair proteins to chromatin following DNA damage. After validating image correlation spectroscopy as a reliable method to visualize the recruitment of γH2AX to chromatin following DNA damage in two separate cell lines, the study demonstrates that this new method can also be used to quantify RPA1 and Rad51 recruitment to chromatin following DNA damage. The study further shows that RPA1 signal as measured by this method correlates with cell sensitivity to Olaparib, a widely-used PARP inhibitor.
Strengths:
Multiple proof-of-concept experiments demonstrate that using image correlation spectroscopy degree of aggregation is typically more sensitive than foci counting or foci intensity as a measure of recruitment of a protein of interest to a site of DNA damage. The sensitivity of the SKOV3 and OVCA429 cell lines to MMS and the PARP inhibitors Olaparib and Veliparib as measured by cell viability in response to increasing amounts of each compound is a valuable correlate to the image correlation spectroscopy degree of aggregation measurements.
Weaknesses:
The subjectivity of foci counting has been well-recognized in the DNA repair field, and thus foci counts are usually interpreted relative to a set of technical and biological controls and across a meaningful time period. As such:
(1) A more detailed description of the numerous prior studies examining the immunostaining of proteins such as γH2AX, RAD51, and RPA is needed to give context to the findings presented herein.
(2) The benefits of adopting image correlation spectroscopy should be discussed in comparison to other methods, such as super-resolution microscopy, which may also offer enhanced sensitivity over traditional microscopy.
(3) Additional controls demonstrating the specificity of their antibodies to detection of the proteins of interest should be added, or the appropriate citations validating these antibodies included.
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Reviewer #3 (Public review):
Summary:
This paper described a new tool called "Image Correlation Spectroscopy; ICS) to detect clustering fluorescence signals such as foci in the nucleus (or any other cellular structures). The authors compared ICS DA (degree of aggregation) data with Imaris Spots data (and ImageJ Find Maxima data) and found a comparable result between the two analyses and that the ICS sometimes produced a better quantification than the Imaris. Moreover, the authors extended the application of ICS to detect cell-cycle stages by analyzing the DAPI image of cells. This is a useful tool without the subjective bias of researchers and provides novel quantitative values in cell biology.
Strengths:
The authors developed a new tool to detect and quantify the aggregates of immuno-fluorescent signals, which is a center of modern …
Reviewer #3 (Public review):
Summary:
This paper described a new tool called "Image Correlation Spectroscopy; ICS) to detect clustering fluorescence signals such as foci in the nucleus (or any other cellular structures). The authors compared ICS DA (degree of aggregation) data with Imaris Spots data (and ImageJ Find Maxima data) and found a comparable result between the two analyses and that the ICS sometimes produced a better quantification than the Imaris. Moreover, the authors extended the application of ICS to detect cell-cycle stages by analyzing the DAPI image of cells. This is a useful tool without the subjective bias of researchers and provides novel quantitative values in cell biology.
Strengths:
The authors developed a new tool to detect and quantify the aggregates of immuno-fluorescent signals, which is a center of modern cell biology, such as the fields of DNA damage responses (DDR), including DNA repair. This new method could detect the "invisible" signal in cells without pre-extraction, which could prevent the effect of extracted materials on the pre-assembled ensembles, a target for the detection. This would be an alternative method for the quantification of fluorescent signals relative to conventional methods.
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