Live imaging of Alu elements reveals non-uniform euchromatin dynamics coupled to transcription

Reviewer #1 (Public Review):

The manuscript from Chang et al. presents a new technique to track chromatin locus mobility in live cells, by specifically tracking Alu rich sequences using a CRISPR based technique. The experiments in Fig. 1-2 provide extensive validation of the reagent, and the experiments in Figs. 3-4 yield new insights into chromatin dynamics and its relationship to transcription. While the findings in this manuscript are interesting, some points need to be addressed to support the central claims.

One item of consideration is the use of bulk PIV methods to monitor chromatin mobility. While these whole genome methods certainly are useful for studying chromatin mobility at a diffraction limited (or higher scale) as well as tracking correlations at the micron scale, these methods obscure dynamics at the TAD/nucleosomal level (~200 nm). Since the studies use fluorescently labeled H2B to study chromatin dynamics, some consideration should be given to using Halo-tagged variants of H2B to get a single molecule view within specific chromatin contexts. A few recent studies (Saxton et al. 2023, Daugird et al. 2023) have used these methods to show how histone dynamics at the single molecule level depends on the chromatin context.

Secondly, there should be additional discussion of how the mean-squared network displacement relates to single locus and histone mobility at the sub-diffraction level. While it is reassuring to see that MSND and single particle tracking MSD exponents roughly agree at the sub-second time scale, how these relate at longer time scales is not clear. Figure S5A shows MSD for individual loci, but only timelags upto 1s are shown. It should be possible to track loci considerably longer than that. MSD exponents in the literature are quite varied beyond the second time-scale, and the authors have an excellent system to shed light on this question.

Finally, some additional discussion about why the transcriptional inhibition results shown here differ from other studies in the literature (e.g. Daugird et al. 2023) would better place these findings in context.

Reviewer #2 (Public Review):

Summary:

Chromatin organization and dynamics are critical for eukaryotic genome functions, but how are they related to each other? To address this question, Chang et al. developed a euchromatic labeling method using CRISPR/dCAS9 targeting Alu elements. These elements are highly enriched in the A compartment, which is closely associated with transcriptionally active and gene-rich regions. Labeling Alu elements allowed live-cell imaging of the gene-rich A compartment (euchromatin). Using the developed system, Chang et al. found while Alu-rich chromatin is depleted in regions with high chromatin density (putative heterochromatin), Alu density and chromatin density are not correlated in the euchromatin. Combining the live-cell imaging of Alu elements with bulk chromatin labeling (fluorescent histone H2B), the authors showed that transcriptionally active chromatin (A compartment) has an increased mobility. Transcription inhibitors flavopiridol and 𝛼-amanitin treatments increased the mobility of Alu-rich chromatin, and ActD had the opposite effect on chromatin mobility.

Strengths:

Alu labeling is a valuable euchromatin labeling method, and measuring its mobility would contribute to a comprehensive understanding of the relationship between chromatin dynamics and transcriptional activity.

Weaknesses:

Some of the findings are consistent with the previous reports and not new. There are some issues to be addressed. My specific comments are the following:

Line 58. "these methods generally lack information regarding the local chromatin environment (e.g., epigenetic state) and genomic context (e.g., A/B compartments and TADs)." This description is not accurate because Nozaki et al. (2023) performed euchromatin-specific nucleosome labeling/imaging (Hi-C contact domains with active histone marks, A-compartment). More recently, Semeigazin et al. (2024)(https://www.researchsquare.com/article/rs-3953132/v1) also did euchromatic-specific nucleosome labeling/imaging in living cells.

Line 154. "we defined the euchromatin regions in our images by excluding heterochromatin (top 5% pixel intensity) and nucleolar areas."
I am not so sure that this definition is reasonable. How were the top 5% H2B intensity regions distributed? Did they include the nuclear periphery region, which is also heterochromatin-rich? Could the authors show the ΔPCC between whole H2B (including both euchromatin and heterochromatin) and dCas9-sgAlu?

Line 214. "our data suggests that Alu-rich (gene-rich) regions have increased chromatin mobility compared to Alu-poor (gene-poor) regions." A similar finding on nucleosome motion has already been published by Nozaki et al. 2023 and Semeigazin et al. 2024 (described above).

Line 282. A recent important paper on the relationship between histone acetylation, transcription initiation, and nucleosome mobility (PMID: 37792937) is missing and should be discussed.

Line 303. "Alu-rich chromatin may be more sensitive upon flavopiridol and 𝛼-amanitin treatments compared to Alu-poor chromatin (Figure 5)." Nagashima et al. (2019) also revealed that 𝛼-amanitin treatment did not increase the chromatin dynamics in heterochromatin-rich nuclear periphery regions.

Reviewer #3 (Public Review):

The manuscript by Chang, Quinodoz and Brangwynne describes the results of live cell imaging of fluorescently labeled Alu element genomic sites in combination with H2B-GFP marked chromatin in human cancer cells. The study includes dCas9 based genomic engineering for Suntag enhanced Alu element labeling. The motion of Alu elements and chromatin was analyzed in real time at 500 ms intervals over 1 min at high resolution. Advanced image analysis algorithms were developed.

The main objective of the study is to understand how motion of euchromatin or active chromatin relates to chromatin density. Alu elements, which are spread throughout the genome are used as a proxy for euchromatin or also A compartments. The study finds that Alu-rich chromatin is more mobile than Alu poor one and that actinomycin but not flavopyridol or alpha amanitin cause some decrease in the determined mobility. The authors emphasize the heterogeneity of motion, Alu clustering and chromatin density underscoring the complexity of the problem.

Although the topic is important and the imaging well performed, the study lacks depth and does not provide any truly new insights into our understanding of the link between genome activity and mobility nor diffusive behavior of the chromatin fiber in situ. Although the approach to record context dependent dynamics based on segmentation of pixels of varying intensity is elegant, the analysis of the trajectories requires further explanation and justification to be able to interpret the results. Important information on the biology of the engineered cell lines is lacking. Presented results are not discussed with respect to existing literature and knowledge.

Major concerns:
- Are Alu elements a good proxy for A compartments? What consequences do massive dCas9 tags have on the genome and the engineered cells? How does the bulky dCas9-Suntag label impact mobility and transcription of Alu elements themselves? How many off target sites are potentially labeled?

(1) The authors should state the size of the dCas9-Suntag construct and perform FRAP analysis to compare the tag's behavior to the one of H2B-GFP
(2) dCas9 locally unwinds DNA and is strongly bound to its target sequence impeding polymerase progression.
(3) The authors need to check if DNA breaks are induced. An immunofluorescence using a gH2AX antibody is a minimum in all conditions tested. DNA breaks largely affect chromatin mobility which is a topic of major debate (see PMC5769766, PMID33061931).
(4) The authors need to confirm that in dCas/sgAlu cells Alu elements are still transcribed similarly to wt cells (transcriptome or at least some qPCR).
(5) Please compare H2B-GFP mobility of sgAlu tagged and untagged cells.
(6) Figure 1D shows significant background in the Cut&run sgAlu line compared to H3K4me3 line. Are these off target sites? Was the H3K4me3 Cut&run performed in the engineered cell line? Did the authors test another guide RNA? Non-specific binding could also contribute to the observed heterogeneity in the measured dynamics.
(7) Figure 3G shows that H2B MSND at tau=5s is high for high H2B density independently of Alu density questioning the value of using Alu sg tagging as a proxy for euchromatin.

- What are the physical principles of the measured motion? What is the rationale for the MSND analyses deployed in this study?
(1) Please provide the equation used for MSND (seems to be different from the standard MSD one).
(2) Figure 3: all MSD curves have a slope suggesting an alpha exponent significantly smaller than 0.5 reminiscent of subdiffusion (example panels A and E compare thick line to slope of the triangle bottom right). Please explain. Is it gaussian noise? Confinement? This was seen before for faster acquisition rates, but still requires explanation and interpretation.
(3) What is the rationale for choosing the value at τ =5 s? Figure 3 panel E shows large variations in the MSND at all time points, curves do not start at the same lag time.
(4) Figure S5 shows that for Alu elements, alpha is close to 0.5 at τ =<1 s but lower for larger tau, the relationship to intensity is inverse as well. Please explain.
(5) It would be important to show the D values of your estimations. Plots for MSD curves in non log scale are important to be presented to show if there are different diffusion regimes (such as in Figure 4).
(6) It is mentioned that the "Our measurements of total chromatin dynamics at lag time τ = 5 s are typically on the order of 10-2 μm2 (Figure 3 A, B), in agreement with past studies (Shaban et al., 2020; Zidovska et al., 2013)". This is inaccurate as both cited studies were performed at different time lags 0.2 sec. Change in time lag is supposed to show different diffusion behaviour. For consistency, the comparison should be done at the same time lag and the same number of analyzed video frames.
(7) The study applies the MSND analysis for different time lags starting from 0.5 s to 11 s for videos of 60 s. Change in the number of data points affects the accuracy to calculate the diffusion coefficient. What is the impact of this uncertainty on the results and conclusions?

- Inhibition of polymerase 2 activity increases mobility as was shown before.
(1) Figure 4: change in motion following alpha amanitin and Flavopiridol treatments recapitulate results from the Maeshima group (Nagashima 2019). Data shown for actinomycin treated cells appear extreme. A huge drop in H2B MSND (panel B and D). Please ensure that the cells are still alive after 4-6h exposure to ActD. ActD also affects cytoskeleton and replication, so different conclusion may be drawn if cells are still alive.
(2) Treatment effects could also be enhanced should dCas9/ sgAlu induce massive DNA damage (see above). Check H2B-GFP motion in cells (both treated and not) not labeled with sgAlu.

- Positioning with respect to the literature:
(1) The introduction, first paragraph is oversimplified, please review the literature citing work performed by many groups in the field using H2B-GFP, telomere or single site labeling in the past 10 years. Give details on the cell type used (mouse or human normal or cancer cells, amplified signals or single genes, same cell or cells at different stages of development, methodologies from whole genome to single particle tracking etc.).
(2) The manuscript claims to introduce a novel mapping of the spatiotemporal dynamics of the A compartment in living cells. However, the authors did not discuss other previous approaches that were developed for the same purpose. The dynamic motion of active transcription chromatin domains/A compartment over the whole nucleus was investigated in different studies that used Mintbody labeling, please check PMCID: PMC7926250, PMCID: PMC8647360, PMID: 27534817, PMCID: PMC8491620
(3) PIV applies a relatively large interrogation window size of micrometers to estimate the displacement vectors. Dynamic changes within the set window can include both A and B compartments, where the contribution of genomic processes to local chromatin motion, typically taking place at the nanometer scale, is missed. The Hi-D method ( PMCID: PMC7168861) introduced an Optical Flow approach to overcome this limitation of PIV (PMCID: PMC6061878 ). Could the authors test if Hi-D method to analyze the movies recorded in this study confirms their conclusions?

Heterogeneity of chromatin dynamics independent of chromatin density was shown by previous studies such as PMCID: PMC7775763 , and PMCID: PMC7168861 . Could the authors discuss their findings in the context of these studies?

Author response:

We thank the reviewers for their positive feedback and helpful suggestions for improving our manuscript.

We appreciate the reviewers highlighting areas where we can improve clarity, particularly in the analysis methodologies and details. We agree that additional control experiments and expansion on single-molecule tracking analysis will provide additional support for our interpretations.

We acknowledge the reviewers' suggestion to describe our work's relationship to other studies. While some of our findings are similar to those in past studies, our work introduces a new approach for labeling euchromatin with direct sequence specificity on a genome-wide scale, enabling a deeper understanding of euchromatin organization and dynamics. We will provide more context on the novelty of our work and incorporate a more comprehensive discussion of our work’s relation to other studies in the manuscript.