MYC modulates TOP2A diffusion to promote substrate detection and activity

Domain: neuroscience
Published: 2026-02-09
Editorial outcome: minor_revision

Abstract
Topoisomerases alleviate DNA supercoiling by cleaving and resealing DNA strands. Previously, we showed that the oncoprotein MYC recruits and stimulates topoisomerases to remove DNA entanglements generated by oncogenic transcription. Understanding this mechanism may suggest methods to inhibit MYC-driven topoisomerase activation, targeting tumor-specific transcription. Here, we demonstrate that the essential topoisomerase TOP2A in human cells exists in a dynamic equilibrium between sequestration in the nucleolus, substrate searching in transcription hubs, and active engagement on chromatin. This equilibrium is highly responsive to changes in DNA topology, allowing cells to regulate TOP2A levels. Using single molecule tracking, here we show that MYC accelerates TOP2A diffusion in cells. We explain this phenotype by demonstrating that MYC limits TOP2A self-interaction in vitro, while decreasing the size of TOP2A complexes in cells. By increasing TOP2A diffusion, MYC promotes substrate binding and increases TOP2A engagement on chromatin genome-wide, revealing the mechanism underlying MYC stimulation of TOP2A activity.

Introduction
MYC functions as a global activator of transcription, increasing the amplitude of transcriptional bursts and boosting promoter output1. Transcription also generates DNA supercoiling downstream and upstream of an elongating RNA Polymerase (RNAP)2. As MYC increases transcription rates, it drives more torsional stress into the DNA template, which, if not resolved, can slow down transcription and hinder MYC-driven overexpression3. Thus, MYC’s ability to increase transcriptional output depends on efficient relief of topological problems.

Topoisomerases relax DNA supercoils and decatenate intertwined DNA by cutting and resealing DNA strands. Topoisomerase 1 (TOP1) creates a transient single-strand break, allowing rotation around the unbroken strand to release DNA twist. Topoisomerase 2 (TOP2) generates a transient double-stranded break to pass one intact DNA duplex through the break, thus resolving supercoils or DNA catenanes. Both enzymes facilitate transcription by relieving topological stress. Although topoisomerases exhibit limited sequence specificity, their activity is directed by recognition of DNA topology or interaction with partner proteins4. Previously, we demonstrated that MYC can recruit and stimulate both TOP1 and TOP2A, localizing them to sites of high transcription, thereby promoting increased transcription rates5. However, the precise mechanism by which MYC mediates topoisomerase recruitment and stimulation remains unclear.

TOP2A, the isoform associated with proliferating cells, has a disordered carboxyl-terminal domain (CTD) that mediates both chromatin targeting and catalytic function6,7. Notably, TOP2A can form CTD-dependent phase-separated condensates in vitro, which partition with plasmid DNA at high concentrations8. These condensates reflect a transition in the activity of TOP2A from relaxation and decatenation to catenation, suggesting that TOP2A phase-separates on chromatin during mitosis to induce chromatid catenation, which is essential for chromosome condensation9. During interphase, transcription condensates containing MYC form at active sites, including super-enhancers, to drive transcription activation10. Because these condensates are often associated with elevated transcription10,11, they are likely to include TOP2A to relieve topological stress. Although TOP2A condensates that favor catenation may be beneficial for mitotic condensation, this action would hinder the removal of topological stress generated by transcription in interphase if local levels of TOP2A reach concentrations associated with condensate formation. It remains unclear whether TOP2A supports transcription via association with the interphase condensates.

In this study, we demonstrate that TOP2A maintains a dynamic equilibrium between nucleolar and transcription condensates in human cells. This equilibrium is maintained by the integrity of these condensates and is highly responsive to changes in DNA supercoiling. We found that MYC accelerates TOP2A diffusion in cells. In line with biophysical principles, MYC reduces the size of the TOP2A condensates in vitro and decreases the size of TOP2A-containing complexes in cells, providing a rationale for the enhanced diffusion. By increasing TOP2A diffusion, MYC favors TOP2A substrate detection and promotes TOP2A catalytic engagement on chromatin genome-wide, revealing the mechanism for MYC stimulation of TOP2A activity.

Results
TOP2A exists in an equilibrium between nucleolar and transcription condensates
We first examined TOP2A localization in interphase HCT116 cells, a colorectal cancer cell line previously used for studies of topoisomerases5,12. We applied stimulated emission depletion (STED) microscopy13 to achieve sub-diffractive optical resolution of TOP2A. Co-staining of nucleolar substructures—the fibrillar center (RNAPI), the dense fibrillar compartment (Fibrillarin), and the granular component (Nucleophosmin)—revealed that TOP2A was enriched across all three compartments (Fig. 1A, Supplementary Fig. 1A). Since rRNA transcription occurs specifically at the boundary of the fibrillar center14, this indicates that the nucleolar TOP2A enrichment is not specific to its known site of activity during ribosomal RNA (rRNA) transcription15. Following treatment with buffer to remove soluble proteins16, TOP2A enrichment in the nucleolus persisted, but was lost along with the nucleolar protein fibrillarin upon further treatment with RNase A (Fig. 1B, Supplementary Fig. 1B), suggesting its association with nucleolar structures was maintained by ribosomal RNA. Outside of the nucleolus, STED imaging also revealed heterogeneity of TOP2A, showing enrichment in nucleoplasmic puncta (Fig. 1A, Supplementary Fig. 1C). We predicted that these puncta correspond to transcription condensates, given TOP2A’s involvement in transcriptional regulation17. Indeed, co-staining with MED4, a component of the Mediator complex enriched in transcription condensates18, showed strong colocalization with TOP2A (Fig. 1C, Supplementary Fig. 1C), while treatment with 1,6-hexanediol, shown to rapidly dissolve Mediator-containing transcriptional condensates18, weakened TOP2A puncta intensity relative to the surrounding area (Fig. 1D, E, Supplementary Fig. 1D). The association between the two proteins was further supported by overlapping ChIP-seq signals of TOP2A and MED26—another subunit of Mediator—from previously published datasets5,19 at MED26 peaks (Supplementary Fig. 1E). These data suggest that TOP2A puncta may partially correspond to Mediator-containing transcription condensates, although they could also include other sub-nucleoplasmic structures.

Previous studies have demonstrated that TOP2A exists in an equilibrium between the nucleolus and the nucleoplasm20,21. This equilibrium persists as the TOP2A concentration fluctuates across cell cycle phases (Supplementary Fig. 1F, G). Given the enrichment of TOP2A in the nucleolus and nucleoplasmic transcription condensates, we propose that the integrity of these compartments supports this equilibrium. To challenge this hypothesis, we first observed how TOP2A distribution changes after these two compartments are targeted by drug treatment. Inhibition of RNAPI elongation with 5nM actinomycin D for 1h reduced ribosomal RNA expression (Supplementary Fig. 1H) and induced nucleolar-to-nucleoplasmic translocation of TOP2A (Fig. 1F, Supplementary Fig. 1I), as previously reported with other RNAPI transcription inhibitors21. Given that this treatment did not extensively affect the nucleolar structure under our experimental conditions, as observed by fibrillarin staining (Fig. 1F), it suggests that TOP2A is largely retained in the nucleolus via rRNA-mediated nucleolar interactions. This was previously observed with rat TOP2A, where the CTD confers both nucleolar localization and sensitivity of TOP2A activity to RNA inhibition22. Conversely, treatment with 1,6-hexanediol caused TOP2A to shift from the nucleoplasm into the nucleolus within 5min (Supplementary Fig. 1D). While 1,6-hexanediol can dissolve many condensates, including Mediator-containing transcriptional condensates23 (Supplementary Fig. 1D), by disrupting weak hydrophobic interactions, it can favor condensation of other compartments through hydrophilic interactions24. Indeed, other phase-separated proteins that are maintained through hydrophilic interactions are not dissolved by 1,6-hexanediol treatment25. This could include proteins, such as nucleophosmin, which is enriched in the nucleolus by its positively and negatively charged disordered domain26. This may explain why TOP2A enrichment in the nucleolus is not disrupted by 1,6-hexanediol treatment. Since the dysregulation of either the nucleolus or nucleoplasmic transcription condensates causes the rapid translocation of TOP2A from one region to the other, the data suggest the equilibrium is at least in part maintained by these two structures.

The presence of a dynamic equilibrium might allow for rapid TOP2A translocation upon changes in DNA topology. We predicted that the TOP2A equilibrium enables the cell to rapidly respond to changes in the supercoiling burden. If this is the case, increasing the level of supercoiling in the genome should provoke a redistribution of TOP2A from the nucleolus to the nucleoplasm. We tested this hypothesis in two ways. Firstly, because TOP1 and TOP2 can partially compensate for each other’s function, degradation of one enzyme is expected to trigger a compensatory increase in supercoiling, thereby enhancing engagement of the other topoisomerase on the DNA27. We therefore acutely degraded TOP1 by auxin28. Secondly, we treated cells with ICRF-193, which blocks TOP2A recycling after DNA religation29,30. Both treatments have been reported to increase genomic supercoiling by psoralen binding assay31. In both tested conditions, we observed a rapid translocation of TOP2A from the nucleolus to the nucleoplasm and nucleolar periphery (Fig. 1F, G, Supplementary Fig. 2A, B) without affecting total nuclear TOP2A concentration (Supplementary Fig. 2C, D). To test whether the translocated TOP2A was actively engaged on the DNA, we treated cells with a low dose (1μM) of etoposide for 60min. Etoposide traps covalently engaged TOP2 on the DNA, causing DNA damage, which we can visualize with γH2AX staining. We observed an increase in DNA damage only after TOP1 degradation by auxin and etoposide treatment, suggesting that the increased nucleoplasmic fraction of TOP2A after TOP1 degradation correlates with increased TOP2 activity (Fig. 1H, Supplementary Fig. 2E). These γH2AX puncta were enriched within the nucleoplasm relative to the nucleoli, indicating that the increased activity is spread across the genome rather than being specific to the ribosomal DNA loci (Supplementary Fig. 2F, G). It is also possible that part of the γH2AX signal is associated with the pre-existing nucleoplasmic TOP2A, trying to compensate for the absence of TOP1.

Overall, these findings suggest that TOP2A localization is regulated by its interaction with both nucleolar and transcription condensates, existing in an equilibrium between compartments that is sensitive to both their dysregulation and DNA supercoiling. Notably, TOP2B distribution across the nucleus was much more homogeneous, as compared to TOP2A, although ICRF-193 also caused a slight nucleolus-to-nucleoplasm relocalization (Supplementary Fig. 2H, I), suggesting it may also be responsive to similar stimuli to TOP2A, although the TOP2A response was more pronounced.

The dynamics of TOP2A in the nucleus can be described by three states
To better characterize the dynamic equilibrium of TOP2A between its associated compartments, we tagged endogenous TOP2A with a Halo-tag and used a custom Highly Inclined Laminated Optical sheet (HILO) imaging platform32 to perform Single Molecule Tracking (SMT) in live HCT116 cells. This approach allowed us to measure the location and motion of single fluorescently labeled TOP2A molecules over time (Fig. 2A). Single TOP2A molecules exhibited a spectrum of diffusion coefficients, peaking at very low diffusion coefficients (corresponding to immobilized molecules) and with a second peak at ~1µm2/s (corresponding to molecules quickly diffusing through the nucleus). Between these two peaks, an intermediate regime, corresponding to a shoulder in the spectra at ~0.1µm2/s was visible (Fig. 2B, Supplementary Movie 1). Notably, TOP2A mobility was substantially reduced when trapped on DNA by ICRF-193 treatment33 (Fig. 2B, Supplementary Movie 2).

To assign individual track segments to different diffusing states, we used a Hidden Markov Model approach (variational Bayes single particle tracking, vbSPT)34 and characterized nuclear TOP2A diffusion into three distinct populations. The slowest population had diffusion coefficients below 0.1µm2/s (Fig. 2C), comparable to the mobility of histones and chromatin-bound proteins35. We refer to this group as the bound fraction. The other two populations, which represent TOP2A molecules diffusing in the nucleus, are referred to as slow and fast fractions based on their diffusion rates (Fig. 2C). Treatment with ICRF-193 caused a marked increase in the bound population (Fig. 2C). As it takes over an order of magnitude longer for strand passage by TOP2A to occur than the framerate of our imaging (300ms for strand passage36,37 compared with 10ms between frames), and since DNA-bound TOP2A exhibits diffusion rates far lower than TOP2A in the fast and slow fraction, we conclude that this fraction includes TOP2A covalently engaged on the DNA. However, this may also include TOP2A that is interacting with chromatin without catalytic engagement. TOP2A in the fast and slow states is not precluded from becoming covalently engaged on the DNA, given the observed transitions between the fast and slow fractions as well as between the slow and bound fractions (see arrows in Fig. 2C). It is notable that fast-to-slow and slow-to-bound transitions are substantially more frequent than fast-bound transitions, suggesting the TOP2A molecules must pass through the slow state before becoming chromatin-bound.

Using a GFP-Nucleolin marker to separately analyze TOP2A diffusion in the nucleolus and the nucleoplasm, we observed that diffusion speed was reduced by more than 50% in the nucleolus relative to the nucleoplasm, with a rate of 0.61μm2/s in the nucleoplasm compared to 0.28μm2/s in the nucleolus. In addition, the nucleolus predominantly contained slow and bound TOP2A, while the nucleoplasm contained more equal amounts of all three populations (Fig. 2D, E). This indicates that TOP2A diffusion is more constrained within the nucleolus.

The fast and slow fractions are further distinguishable by their diffusional anisotropy, with the nucleoplasmic slow fraction exhibiting anisotropy values greater than 1 (Fig. 2F), indicative of protein retention within discrete compartments. Nucleoplasmic tracks with average anisotropy greater than 1 were limited to regions of about 150nm in size (Fig. 2G), consistent with both the approximate size of the MED4 puncta (Fig. 1C) and the reported size of a transcriptional condensate38. These features suggest that the slow TOP2A fraction in the nucleoplasm likely contains molecules performing compact target searching in transcription condensates39. Importantly, previous studies have shown that transcription condensates associate with gene loci only transiently11. Thus, if the slow TOP2A fraction represents TOP2A localized in transcriptional condensates and the bound fraction corresponds to TOP2A interacting directly with chromatin, we would expect the slow fraction to border the bound fraction, reflecting transient spatially proximal interactions between transcription condensates and chromatin. Consistent with this expectation, spatial cross-correlation analysis32 demonstrates that regions containing slow TOP2A are enriched near bound TOP2A loci (Supplementary Fig. 3A, B), with a decay length of ~250nm, indicating that slow molecules are most likely to be found within this distance from bound ones. Following 1,6-hexanediol treatment, the cross-correlation between slow-diffusing and bound TOP2A molecules diminished by about two-fold relative to the control, indicative of decreased proximity (Supplementary Fig. 3C). We should also be able to visualize the TOP2A equilibrium shift upon ICRF-193 treatment. To test this, we used STED to observe TOP2A association with transcription condensates labeled with MED4 and TOP2A association with open chromatin labeled with H3.3, which we predict to contain TOP2A molecules belonging to the slow and bound fractions, respectively40 (Fig. 2H). TOP2A was enriched in both compartments, indicating overlap with transcriptional condensates and transcribed chromatin (Fig. 2I). Notably, ICRF-193 treatment shifted TOP2A from the MED4 compartment to the H3.3 compartment (Fig. 2I, J), consistent with its movement from the slow fraction to the bound fraction (Fig. 2C). This shift was not observed with actinomycin D treatment, ruling out the possibility that it was driven solely by increased nucleoplasmic translocation (Fig. 2J, Supplementary Fig. 3D). Altogether these results indirectly support an association between TOP2A and Mediator-containing condensates and suggest that these structures may contribute to the behavior of the TOP2A slow fraction. Thus, nucleoplasmic TOP2A can be grouped into three states based on diffusion rates: a bound fraction interacting or catalytically engaged with chromatin, a slow fraction enriched in transcription condensates, and a fast fraction diffusing through the nucleoplasm. The equilibrium maintained between these states and the nucleolus enables TOP2A to rapidly shift to regions where topological regulation is needed.

MYC modulates TOP2A diffusion in cells
We have previously shown that the oncogenic transcription factor c-MYC (hereafter referred to as MYC) is able to join TOP1 and TOP2A to form the topoisome. Within this complex, MYC stimulates the catalytic activity of both topoisomerases, thereby coupling oncogenic transcription rates to relief from DNA entanglements5. If the formation of a topoisome prevents the binding of other proteins, thereby limiting the effective size of the complex, as shown in the MYC-driven topoisome study, then we would expect to observe differences in TOP2A diffusion with or without MYC, since protein diffusion is inversely correlated with the complex radius41.

We generated HCT116 cells expressing MYC tagged with an auxin-inducible degron (AID)42, enabling 95% knockdown of MYC protein within 90min of auxin treatment (Fig. 3A). We then tagged endogenous TOP2A via Halo-tag and performed SMT to track TOP2A diffusion upon auxin-dependent MYC degradation. We observed that the proportion of TOP2A found in the fast, slow, and bound fractions was not significantly different between the CTRL and Auxin conditions (Fig. 3B). However, TOP2A diffusion speed was reduced after MYC degradation in both the fast and slow fractions of the nucleoplasm (Fig. 3C), while we found no difference in the nucleolus (Fig. 3D) where MYC is largely excluded (Supplementary Fig. 4A). This reduction in TOP2A diffusion was not observed upon global transcription inhibition by triptolide treatment43, indicating that the diffusion change observed upon MYC depletion was not linked to secondary transcriptional effects (Supplementary Fig. 4B). Indeed, consistent with its ability to reduce transcription-induced supercoiling44, triptolide increased slow and bound TOP2A diffusion coefficients, potentially by decreasing its DNA engagement, while the unchanged fast fraction coefficient indicates the size of the freely diffusing TOP2A complex remains unaffected (Supplementary Fig. 4B).

If MYC promotes formation of comparatively smaller TOP2A complexes by favoring a TOP1-containing topoisome, then removing TOP1 should further increase TOP2A diffusion, as the MYC–TOP2A interaction persists in the absence of TOP1 (Supplementary Fig. 4C–E), yielding an even smaller, more mobile complex. To test this, we depleted free TOP1 either with acute treatments of camptothecin (CPT) to trap and stabilize TOP1 cleavage complex on the DNA45, or by auxin-mediated degradation in HCT116 cells5,28 (Supplementary Fig. 4F). In both conditions, TOP1 loss increased TOP2A diffusion, particularly in the slow and bound fractions (Supplementary Fig. 4G, H), potentially indicating that the topoisome forms predominantly within the transcriptional condensates and on the chromatin. Thus, consistent with diffusion scaling inversely with complex size, these results reveal that MYC limits complex size to promote TOP2A diffusion. We next asked whether this phenotype is recapitulated both in vitro and in cells.

MYC limits TOP2A droplet size
In vitro, we took advantage of recent findings that TOP2A forms phase-separated droplets8. The droplets are largely dependent on the presence of the TOP2A-CTD, which is intrinsically disordered. We were able to observe droplet formation using 2μM recombinant human TOP2A in an isotonic salt solution that was enhanced both by co-incubation with DNA and reduction in salt concentration (Fig. 4A, B, Supplementary Fig. 5A, B), in line with previous reports8. These droplets were also able to fuse (Supplementary Fig. 5C). Furthermore, we observed that while supercoiled plasmid DNA and catenated kDNA—both known substrates of TOP2A—as well as RNA could increase droplet formation, short 20bps DNA oligonucleotides did not (Fig. 4A, B), confirming previous data that DNA was required to be at least 50–100 bps to favor droplets formation8.

The dependence on DNA length to stimulate droplet formation implies the existence of a percolated network structure within the droplets, where physical crosslinks form between molecules, such as through ionic interactions46. This contrasts with classical liquid-liquid phase separation (LLPS), where a density transition occurs at the saturation concentration47. If these droplets form through LLPS, we would expect to observe free diffusion between the dilute and droplet phases and a strict threshold for determining the concentration where phase separation occurs. However, we observed limited diffusion between phases as assessed by fluorescence recovery after photobleaching (FRAP) (Fig. 4C), in contrast to near complete fluorescence recovery as seen with liquid-liquid phase-separated droplets formed by the protein FUS48. To image TOP2A condensates at protein concentrations below previously reported saturation concentrations, we adapted a protocol where glass coverslips are functionalized to generate a surface with net positive charge that attracts the negatively charged DNA, thus keeping the condensates stationary49 (Fig. 4D). Using this technique, we could observe droplet formation in the presence of plasmid DNA at protein concentrations as low as 5nM (Fig. 4E). The variance in puncta size indicated that these droplets are made up of multiple TOP2A molecules, excluding the possibility that we observed individual TOP2A molecules. Additionally, these TOP2A condensates were also observed independently of DNA, ruling out the possibility that the TOP2A molecules were merely connected by binding to the same DNA (Supplementary Fig. 5D, Fig. 4A). These data suggest that TOP2A droplets form by percolation and that TOP2A condensates can still form at sub-saturating concentrations of proteins.

Since MYC can also bind TOP2A independently of TOP15 (Supplementary Fig. 4C–E), we tested whether MYC can affect TOP2A condensate formation in vitro. As a negative control, we used BSA as well as a MYC mutant containing only residues 200–320 (MYC200–320) that does not interact with TOP2A in immunoprecipitation experiments5. Incubation of fluorescently labeled recombinant TOP2A and MYCWT with plasmid DNA, showed that MYC co-localizes with TOP2A droplets (Fig. 4F) albeit in a non-stoichiometric manner (Supplementary Fig. 5E), while MYC200-320 showed only weak co-localization with TOP2A droplets (Fig. 4F, Supplementary Fig. 5F). While others have reported that MYC can phase-separate in the presence of crowding agents such as PEG10, we did not observe MYC-only droplets under the conditions used here (Supplementary Fig. 5G). We found that fluorescently labeled recombinant TOP1 could colocalize into TOP2A condensates together with MYC (Fig. 4G), while TOP1 showed only a limited capacity to form phase-separated droplets in the presence of DNA, as compared to TOP2A (Supplementary Fig. 5H).

To understand how MYC affects the properties of TOP2A droplets, we devised an imaging strategy that allowed us to observe droplets both in solution and at the well bottom (Fig. 4H). This allowed the visualization of droplets independently of interaction with the plastic surface. We combined 500nM of fluorescently labeled TOP2A and supercoiled plasmid DNA with 3.5μM MYCWT, or MYC200–320, or BSA in an isotonic buffer and measured the resulting TOP2A droplet properties. MYCWT induced a decrease in TOP2A droplet size (Fig. 4I). Similar results were seen at 2μM (Supplementary Fig. 5I) and 25nM (Supplementary Fig. 5J) of TOP2A, roughly covering the range of TOP2A nuclear concentrations reported in quantitative mass spectrometry assays50,51. In line with the above observation, the TOP2A droplets formed in the presence of MYCWT exhibited a markedly slower rate of sedimentation over a time course of 95min (Fig. 4J, K) as demonstrated by comparing the relative number of droplets that remain in suspension vs. those at the well bottom. This is in contrast to co-incubation of TOP2A with MYC200–320, where sedimentation rates were consistent with the BSA control, suggesting that co-localization of MYCWT within TOP2A condensates also reduces their droplet density.

We noted that MYC200–320 elicited a limited decrease in TOP2A droplet size (Fig. 4I, Supplementary Fig. 5I), indicating that it was able to modulate TOP2A droplet formation to some degree, while lacking the region required for direct interaction with TOP2A. However, these experiments were done with much higher concentrations of MYC as compared to pull-down conditions (100nM) where we demonstrated that MYC200–320 did not bind TOP2A during immunoprecipitation. We propose this could be due to the presence of MYC200–320, albeit lower than MYCWT, in the TOP2A droplets (Fig. 4F). Thus, reducing protein concentration should abrogate this effect. Using the glass coverslip system described previously (Fig. 4D), we demonstrated that at lower protein concentration (25nM TOP2A and 100nM MYC), MYCWT reduced the size of TOP2A droplets, whereas this effect was negligible with MYC200-320. This suggests that the effect of the mutant required a much higher concentration than MYCWT (Supplementary Fig. 5J). Note that, despite MYC’s ability to interfere with TOP2A droplet formation, MYC-TOP2A interaction does not directly depend on TOP2A’s CTD, as shown by the immunoprecipitation of MYC with the TOP2AΔCTD mutant that lacks this domain (Supplementary Fig. 5K, L).

We also examined whether the addition of TOP1 influences droplet behavior. Notably, MYCWT also induced a decrease in TOP2A droplet size and an increase in the number of droplets in suspension in the presence of 500nM TOP1. This indicates that the ability of MYC to reduce TOP2A condensate size and sedimentation is independent of TOP1 and likely affects the entire topoisome. Importantly, droplets containing only TOP2A and TOP1 did not exhibit this reduction, confirming that the effect is MYC-dependent (Fig. 4L, Supplementary Fig. 5M). Together, these data suggest that MYC reduces the size of TOP2A droplets both in the presence and absence of TOP1, potentially by weakening the interactions of TOP2A with other TOP2A molecules.

MYC limits TOP2A interactions in cells
To test whether MYC regulates the size of TOP2A-containing complexes in cells, we used K562 MYC-AID cells42, previously used to study topoisomerases upon MYC acute depletion5, to rapidly degrade MYC and test whether it affects the ability of TOP2A to establish interaction with other molecules. MYC was almost completely degraded upon 90-min treatment with auxin, while TOP2A protein levels were unaffected (Supplementary Fig. 6A). Glycerol gradient centrifugations of benzonase-digested protein lysates revealed that acute MYC-depletion caused a shift of TOP2A toward higher molecular-weight complexes (Fig. 5A, Supplementary Fig. 6B-E). Altogether, these findings suggest a mechanism of MYC target regulation, where the presence of MYC is required to accelerate diffusion of TOP2A by limiting the effective size of TOP2A-forming complexes, both outside (fast fraction) and within (slow fraction) transcription condensates.

MYC promotes substrate detection for TOP2A
Intuitively, increasing enzyme diffusion rates should enhance substrate detection and, therefore, enzyme activity. We directly visualized this using quadruple trap optical tweezers (Q-TRAP) coupled with fluorescent imaging to monitor TOP2A binding at a DNA crossover formed by intertwining two linearized lambda DNA molecules (Fig. 5B). Using this system, we are also able to visualize the product of TOP2A activity by observing the decatenation of the DNA strands. Under physiological conditions including Mg2+ and ATP, TOP2A-mediated decatenation occurs extremely quickly (within the ~4s it takes to image another frame) such that we observe decatenation in more than 72% of instances immediately upon TOP2A binding or without even detecting the bound intermediate (Fig. 5C). The rapid nature of the decatenation reaction, combined with signal-to-noise constraints that arise when further lowering TOP2A concentration, makes it challenging to directly compare decatenation rates with or without MYC in real time using this system. To circumvent this issue, we removed ATP so that decatenation could not occur, thereby prolonging the observation window. We then collected images at 30s intervals and measured TOP2A droplet binding at the crossover by applying an intensity threshold (Fig. 5D). Under these conditions, we detected more frequent TOP2A binding events when MYC was present (Fig. 5E). Given that increased substrate binding would logically translate into higher catalytic turnover when ATP is available and, considering our prior demonstration that MYC stimulates TOP2A activity in standard assays5, these data strongly suggest that the MYC-enhanced TOP2A diffusion promotes greater substrate engagement, thereby increasing enzymatic activity.

MYC increases TOP2A activity in cells
If MYC promotes TOP2A enzymatic activity by favoring substrate detection, decreasing MYC levels should decrease TOP2A-DNA cleavage complexes (TOP2Accs) in cells. To detect TOP2Accs genome-wide, we optimized our previously developed CAD-seq52 for TOP2A to immunoprecipitate only catalytically engaged TOP2A. HCT116 MYC-AID cells were treated sequentially with auxin, proteasome inhibitor MG132, and—in the last 6min—etoposide to trap and stabilize TOP2ccs45,53 (Fig. 5F). MG132 was included to prevent TOP2cc degradation53. In control cells, TOP2Acc accumulated at transcription start sites (TSS) and downstream of transcription end sites (TES) of the top 1500 (~10%) expressed genes (Fig. 5G, Supplementary Fig. 6F) as previously observed54. With MYC degradation, TOP2Accs were markedly reduced across all gene locations, particularly toward the TESs, indicating that TOP2A catalytic engagement on the DNA is MYC-dependent. This was not due to a general downregulation of transcription, as 90min of auxin treatment caused essentially no change in transcript production either globally or among the top 10% most highly expressed genes, as assessed by SLAM-seq, which metabolically labels nascent transcripts genome-wide42 (Fig. 5H, Supplementary Fig. 6G, H). Altogether, these findings demonstrate that MYC limits the size of TOP2A complexes, increasing diffusion and substrate detection, which affects TOP2A catalytic engagement on the DNA (Fig. 6). Without ruling out the possibility of additional mechanisms, we suggest that these results reveal the primary mechanism by which MYC stimulates TOP2A.

Methods
Cell lines
The human colon carcinoma cell line HCT116 (ATCC, CCL-247) and variants thereof are used throughout this manuscript. Halo-TOP2A HCT116 MYC-AID cells were generated by knocking in an N-terminal Halo-tag into both TOP2A alleles of HCT116 cells expressing MYC tagged with an Auxin-Inducible Degron (AID) system42 (gift of Dr. Zuber, (IMP, Austria)). These cells were subsequently transduced with a BFP-labeled OsTir1 delivery vector42 to enable MYC degradation. Halo-TOP2A HCT116 TOP1-AID cells were generated by knocking in an N-terminal Halo-tag into both TOP2A alleles of HCT116 CMV-OsTIR1 mAID-TOP1 cells28 (here referred to as HCT116 TOP1-AID). All HCT116 cells were cultured in high glucose (4.5g/L) DMEM (Thermo Fisher, 61965059) with 10% Fetal Bovine Serum (Thermo Fisher, 10270106) in a 37°C incubator with 5% CO2. Halo-TOP2A HCT116 TOP1-AID cells28 were additionally cultured with 1μg/ml puromycin (Thermo Fisher, A11138-03) and 125μg/ml hygromycin B (Thermo Fisher, 10687010). K562 MYC-AID cells (gift from Dr. J. Zuber (IMP, Austria))42 were cultured in RPMI 1640 medium (Thermo Fisher, 21875034) supplemented with 10% Fetal Bovine Serum (Thermo Fisher, 10270106) and 2 mM L-Glutamine (Thermo Fisher, 25030081), 1mM sodium pyruvate (Thermo Fisher, P5770598) in a 37°C incubator with 5% CO2. AID-mediated degradation was induced by treatment with 500μΜ auxin (3-indoleacetic acid, Merck, I3750).

Recombinant protein expression
Recombinant human TOP2A labeled at the N-terminal with the SNAP-tag sequence76 was expressed from the 12-URA-B plasmid in yeast cells and purified as previously described77. Briefly, the plasmid was transformed into URA-deficient yeast and grown in uracil-deficient media to select for transformed cells. Yeast cultures were grown in YPLG media (1% yeast extract, 2% peptone, 2% sodium DL-lactate, 1.5% glycerol) overnight, and TOP2A expression was induced by the addition of 2% galactose for 6h. The protein lysate was extracted by cryo-milling, filtered, and TOP2A was enriched using sequential HisTrap nickel and HiTrap CP cation exchange columns before cleavage with His-tagged TEV protease overnight. The TEV and cleaved His-tag were removed by repassage through a HisTrap nickel column, and the SNAP-TOP2A was purified using a Superdex 200 16/60 column, concentrated by filter centrifugation, and stored at −80°C. SNAP-tagged TOP2 activity was tested by relaxation/decatenation assay, confirming that the tag does not alter enzyme catalysis.

For expression of TOP2AΔCTD, the previously published78 expression vector coding for the wild-type human TOP2A was mutated by site-directed mutagenesis to introduce a STOP codon at residue 1217 using the QuikChange XL Site-Directed Mutagenesis kit (Agilent), generating the hTopoIIAΔ1217 plasmid. TOP2AΔCTD was overexpressed in Baby Hamster Kidney cells (BHK21). TOP2AΔCTD was first purified on a StrepTrap HP column (Cytiva, 23151816). The protein was washed with 25mM Hepes, 100mM NaCl, 100mM KCl, 1mM MgCl2, 10% v/v glycerol, 2mM DTT, pH 8 and eluted with the same buffer supplemented with 3mM Desthiobiotin (Merck, 533-48-2). The Twin-strep tag was removed by the addition of P3C (PreScission protease, Merck, 27-0843-01) at a 1:50 ratio (w/w) and incubated overnight at 4°C. The cleaved protein was then loaded on a HiTrap Heparin HP column (Cytiva, 17-0407-01). Elution was performed by a single step using 25mM Hepes, 370mM NaCl, 370mM KCl, 1mM MgCl2, 10% v/v glycerol, 2mM DTT, pH 8.

Recombinant human MYCWT and MYC200-320 with N-terminal SNAP-tag were expressed in Rosetta-gami competent cells in LB media. Expression of MYC was induced with 1mM IPTG for 4h, and cells were lysed by probe sonication. Protein was resuspended in buffer (500mM NaCl, 20mM Tris pH 8, 35mM imidazole, 1% Triton X-100) with increasing urea (0M then 1.6M) before being solubilized in buffer (NaCl, 20mM Tris pH 8, 35mM imidazole, 1% Triton X-100, 7M urea). Lysate was centrifuged, filtered before passing through a HisTrap column (Merck, GE17-5319-01), concentrated and dialyzed to remove urea before being stored at −80°C.

Full-length human TOP1 (gift from Yves Pommier, NIH/USA) was cloned into the pFastBac1 vector with either N-terminal His6-SNAP-tag or C-terminal SNAP-tag-His6 coding sequence. Assembled plasmids were transformed into DH10Bac competent cells, and the resulting recombinant bacmids were identified using blue-white colony screening. Isolated bacmids were transfected into Spodoptera frugiperda (Sf9) cells using FuGENE HD transfection reagent (Promega, E2311). Baculovirus was gradually amplified to P3 to achieve a higher titer before initiating expression. To express both SNAP-tagged TOP1 constructs, ~1.5×106 cells/mL were incubated with 1:50 P3 virus at 27°C while maintaining 115 rpm orbital shaking for 3 days. Cells were harvested and lysed by sonication in a lysis buffer (20mM HEPES, pH 7.3, 300mM NaCl, 5mM MgCl2, 5% Glycerol, 0.5mM TCEP, 10mM imidazole) supplemented with cOmplete™, EDTA-free Protease Inhibitor Cocktail (Roche, 04693132001). Soluble fraction was obtained by centrifugation at 17,000xg for 40min and subsequently incubated with Ni-NTA Agarose resin (QIAGEN, 30210) for 30min, while rotating in a cold room. Loosely bound protein was washed off with 50mM imidazole, and the TOP1 proteins were eluted with 300mM imidazole prior to size-exclusion chromatography. Eluted fractions were loaded onto the ÄKTApure™ system (Cytiva) coupled with S200 10/300 GL pre-equilibrated in 20mM HEPES, pH 7.3, 300mM NaCl, 5mM MgCl2, 5% Glycerol, 0.5mM TCEP. Fractions containing TOP1 were concentrated to 1–2mg/mL using Vivaspin® Turbo 4 MWCO 50,000 (Sartorius, VS04T31), and flash-frozen before further use. SNAP-tagged TOP1 activity was tested by relaxation assay, confirming that the tag does not alter enzyme catalysis.

Droplet assays
N-terminal SNAP-tagged TOP2A was labeled by incubating with 5μM SNAP-surface AlexaFluor 488 (NEB, S9129S) at 37°C for 30min. Excess fluorophore was removed through dialysis for 24h into 500mM KCl, 20mM Tris, pH 8, 10% glycerol, 0.5mM TCEP buffer. C-terminal SNAP-tagged TOP1 was labeled by labeled in 5μM SNAP-surface AlexaFluor 546 (NEB, S9132S) at 37°C for 30min. Excess fluorophore was removed through dialysis for 24h into 100mM KCl, 20mM Tris, pH 8, 1mM EDTA, 20% glycerol, 1mM DTT buffer. N-terminal SNAP-tagged MYCWT and MYC200–320 were labeled in 5μM SNAP-surface AlexaFluor 647 (NEB, S9136S) at 37°C for 30min before being dialyzed into 20mM Tris pH 8, 100mM KCl, 1mM DTT, 1mM EDTA, 20% glycerol. BSA samples were treated in the same manner as the MYC samples.

Droplet assays done with 500nM or 2μΜ TOP2A and 3.5μΜ MYCWT, MYC200–320, or BSA were mixed with 10ng/ul pUC19 plasmid DNA or water and allowed to settle for 25min before imaging over a total of 95min. Where relevant, 500nM SNAP-TOP1 was added. Assays done using 500nM TOP2A were imaged in six locations per well once every 25min, and images were taken at the well bottom and 6 additional z-stacks with increments of 10μm. Assays done using 2μM TOP2A were imaged in one location per well every 5min, once at the bottom of the well and again focusing 25μm higher within the well. Imaging was done using a Nikon CrEST X-Light V3 spinning disk microscope. Analysis was done using CellProfiler79. Droplet assays were performed in 384-well black non-binding μCLEAR microplates (Greiner, 781906).

Confocal imaging and immunofluorescence
For all treatments, cells were seeded on 18mm coverslips (Marienfeld, 630-2200) in 12-well plates to reach 70% confluency by the time of fixation.

For TOP2A localization after ICRF-193 or Actinomycin D treatments, HCT116 cells were treated with 5μM ICRF-193 (Enzo Life Sciences, BML-GR332) for 15min, or 5nM Actinomycin D (Merck, A1410) for 1h. After treatments, cells were washed once with PBS before being fixed with 3% paraformaldehyde (Thermo Fisher, 28908) for 5min at room temperature and permeabilized with 100% methanol at −20°C for 2min.

For TOP1 degradation and etoposide (Merck, E1383) treatments, HCT116 TOP1-AID cells were treated with 500uM auxin for 3h to induced TOP1 degradation, or degradation was blocked using 0.1mM auxinole (MedChemExpress, HY-111444) overnight. Etoposide (1μM) treatments were performed for 1h. Cells were fixed and permeabilized as described above.

For CSK treatments, cells were washed with PBS (Thermo Fisher, 14190169). Cells were either incubated with 500ul CSK buffer (10mM PIPES, 100mM NaCl, 3mM MgCl2, 300mM sucrose, 0.1% Triton X-100) with or without 300ng/ml RNase A (Thermo Fisher, 12091021) at room temperature for 5min or immediately fixed in PFA. All cells were fixed in 3% paraformaldehyde and washed twice in PBS.

After treatments and fixation, cells were blocked in 2% BSA in PBS-T (0.1% Triton X-100 in PBS) for 1h and then incubated in primary antibodies against: TOP2A diluted 1:200 (Abcam, ab52934), fibrillarin diluted 1:150 (Santa Cruz Biotechnology, sc-166001; or Abcam, ab184817), MYC diluted 1:200 (Abcam, ab32072), anti-γH2AX diluted 1:200 (Merck, 05-636), or TOP2B diluted 1:200 (Santa Cruz Biotechnology, sc-365071) in PBS-T with 2% BSA. Coverslips were then washed three times in PBS-T and incubated in anti-rabbit (Thermo, A32790) or anti-mouse (Thermo, A32744) fluorescently conjugated secondary antibodies diluted 1:500 and DAPI diluted 1:1000 (Thermo Fisher, D1306) in PBS-T with 2% BSA. Finally, coverslips were washed three times in PBS-T and mounted using ProLong Diamond Antifade Mountant with DAPI (Thermo Fisher, P36966) and sealed with nail polish or mounted using ProLong Diamond Antifade Mountant (Thermo Fisher, P36970) and left to cure overnight.

TOP2A nucleolar to nucleoplasmic intensities were calculated using CellProfiler version 4.2.8. Fibrillarin staining was used to identify nucleoli, and DAPI staining was used to identify the whole nucleus. Nuclei were masked with nucleolar objects to obtain the nucleoplasmic signal. TOP2A (or TOP2B) intensity was measured in the nucleoli and nucleoplasm, and mean nucleolus intensity was divided by mean nucleoplasmic intensity for each cell. Where applicable, the γH2AX signal was instead measured in the nucleoplasm or nucleoli.

Cell cycle staging was enabled by incubation of HCT116 cells seeded to 70% confluency with 20μM EdU (taken from Invitrogen, C10424) for one hour, before fixation and labeling of TOP2A, fibrillarin, and DAPI as described above. 3D images of the cells were collected, and the z-stacks were averaged in 2D to ensure that the DAPI signal throughout the cell was measured. The DAPI signal was plotted by histogram to determine cutoffs for G1 and G2 peaks. Cells with EdU staining between these cutoffs were considered in S phase. After categorizing cells into cell cycle stages, TOP2A intensity and nucleolar:nucleoplasm ratio were calculated as described previously.

Cells were imaged on Zeiss LSM700, 710, 880, 980-Airy confocal microscopes using a 63x magnification objective. Graphs and statistical analysis were done on GraphPad Prism version 10.4.1.

Fluorescence recovery after photobleaching (FRAP)
Recombinant SNAP-tagged TOP2A was labeled with SNAP-surface AlexaFluor 488, as described above, before being aliquoted and stored at −80°C. 500nM TOP2A, 10ng/ul pUC19 plasmid DNA, and 3.5μM MYCWT were combined in 384-well black non-binding μCLEAR microplates (Grenier, 781906), and droplets were allowed to form and settle for 10min before bleaching. Whole droplets were bleached with a 488nm laser at 100% intensity for 75 iterations. Bleached droplet intensity was measured over 8min, and droplet intensity was normalized to that of a second, unbleached droplet and plotted with the average pre-bleach signal defined as 1 and the first measurement post-bleach defined as 0. Values measured in instances where unbleached droplets passed in front of either measured droplet were excluded. Intensity measurements were taken using ImageJ. FRAP was performed on a Zeiss LSM980-Airy confocal microscope using a 63x magnification objective. Graphs and statistical analysis were done on GraphPad Prism version 10.4.1.

Coverglass functionalization, sample preparation and fluorescent wide-field imaging
DNA-protein complexes were deposited on functionalized microscope coverslips following published protocols49,80,81. Coverslips and cover glasses were washed by sonication in a 2% Hellmanex solution, rinsed 3 times with MilliQ (MQ) water, dried with N2-gas, rinsed with acetone, submerged in Allyltrimethoxysilane (ATMS, 95%, Merck), (3-aminopropyl)triethoxysilane (APTES, ≥98%, Merck), and Acetone (Merck) at a 1:1:100 ratio for 2h. Prior to loading a sample, the coverslips were rinsed with MQ water and dried with N2-gas. An 8μL sample was used per coverslip. A reaction consisting of TOP2A, MYC, and DNA in 50mM Tris pH 8, 150mM NaCl, 10mM MgCl2, 0.5mM DTT, and 30μg/mL BSA was set up by equilibrating buffer and protein on ice for 10min. After adding the DNA, the reaction was incubated at 37°C for 10min, and Sytox Orange (SYTOX™ Orange Nucleic Acid Stain, Invitrogen, S11368) was added. The sample was imaged immediately.

Images were taken with an inverted fluorescence microscope (Zeiss AxioObserver.Z1) equipped with a 63x oil immersion objective (NA=1.46, Zeiss), 1.6× optovar magnification changer, an iXon EMCCD camera (Andor) and an LDI-7 Laser Diode Illuminator (89 NORTH) was used. The sample was alternately excited with 640nm, 555nm, or 470nm light and filtered with Zeiss Filter set 50, 43, or 44, respectively. Images were processed with a custom Python script. Briefly, the images were flat-field corrected (FFC), filtered with a Gaussian and a top-hat filter and segmented by joining the result from a local thresholding algorithm and a difference-of-gaussian blob detector. The background was defined as the inverse of the puncta mask. Puncta statistics were extracted from the FFC images.

Glycerol gradients
K562 MYC-AID cells were treated with 0.1mM auxinole for 24h, to block MYC degradation, or 500μM auxin for 90min. Cells were counted using Countess 3 cell counter (Invitrogen), and 8 million cells were harvested, spun down for 3min at 300×g, washed once in PBS (Thermo Fisher, 14190169), and washed once in HWB (20mM HEPES pH 7.5, 137mM NaCl). Cells were then lysed in HLB (10mM HEPES pH 7.5, protease inhibitor tablet (cOmplete, EDTA-free protease inhibitor cocktail, Merck, 4693132001), 0.5mM AEBSF (4-(2-Aminoethyl)benzenesulfonyl fluoride hydrochloride, Merck, A8456), 10μM Leupeptin (Leupeptin trifluoroacetate salt, Merck, L2023), 1μM Pepstatin A (Merck, P5318), and 7mM NaF) and passed through a 20G needle 10 times to disrupt the cell membrane before being spun down for 5min at 800×g. The resulting pellet was washed again with HLB before being spun again and resuspended in 0.2% sarkosyl, 20mM HEPES pH 8, 133mM NaCl, 2mM MgCl2, 0.4mM EDTA. Chromatin was sheared through passage with a 25G needle 7 times, sonication for 5min, and treated for 20min with 250 units of benzonase (Merck, E8263) before being centrifuged to remove the remaining insoluble fraction. Samples were loaded into a 10–30% glycerol gradient (equal parts 10 or 30% glycerol, 20mM HEPES pH 8, 133mM NaCl, 2mM MgCl2, 0.4mM EDTA) created in Polyclear Open Top Ultracentrifuge Tubes (Biocomp Instruments, 151–514A) using a BioComp gradient master, and spun for 16h at 151263×g at 4°C in a Beckman Colter Optima L-90K ultracentrifuge fitted with a SW41 rotor. Gradients were manually fractionated into 24 fractions and precipitated using 0.18% DOC for 10min followed by the addition of 9% TCA for 30min. The fractions were centrifuged at 21130×g for 10min, washed twice with 25% acetone, and the protein pellet was resuspended in 1x Bolt LDS (Invitrogen, B007) with 5% β-mercaptoethanol.

Western blotting
Samples were loaded onto Bolt Bis-Tris Plus Mini Protein Gels (Invitrogen, NW04127BOX) alongside PageRuler Plus Prestained Protein Ladder (Thermo Fisher, 26619), run for 70min at 160V, and transferred onto nitrocellulose membrane overnight at 20V. The membrane was blocked in 3% BSA in TBS-T or 5% milk in TBS-T. Incubation with anti-TOP2A (Abcam, ab52934), anti-MYC (Abcam, ab32072), anti-H3 (Abcam, ab1791), anti-beta actin (Merck, A5441), or anti-TOP1 (Abcam, ab109374) primary antibodies was done in 3% BSA in TBS-T diluted 1:10,000 for 1h or overnight. Incubation with secondary antibodies (anti-rabbit Jackson ImmunoResearch, 211-032-171; or anti-mouse Jackson ImmunoResearch, 115-035-174) was done in 3% BSA in TBS-T diluted 1:35000 for 1h. The blot was imaged using SuperSignal West Femto Maximum Sensitivity Substrate ECL (Thermo Scientific, 34095) in a Biorad Chemidoc MP Imaging System. Quantification was done using Image Lab Version 6.1.0 build 7.

Coimmunoprecipitation of recombinant proteins
Coimmunoprecipitations (coIPs) with recombinant proteins were carried out by mixing 200ng of full length TOP2A or C-terminally truncated TOP2A (ΔCTD) with 100ng of MYC protein in PDB buffer (10mM Tris-HCl pH 7.5, 100M KCl, 0.5% NP40, 7.5% Glycerol, 200μM EDTA, 250μg/ml BSA, 1× protease inhibitor tablet (cOmplete, EDTA-free protease inhibitor cocktail, Merck, 4693132001), 0.5mM AEBSF (4-(2-Aminoethyl) benzenesulfonyl fluoride hydrochloride, Merck, A8456), 10μM Leupeptin (Leupeptin trifluoroacetate salt, Merck, L2023), and 1μM Pepstatin A (Merck, P5318)) on ice for 30min. 100ng of anti-TOP2A/B (Abcam, ab109524), anti-MYC (Abcam, ab32072) or IgG control (Santa Cruz, sc-2025) was added to the mixture, followed by incubation on ice for 30min. For each sample, 6μL Protein A/G beads (Thermo Fisher, 88803) were blocked in PDB buffer with 5% skim milk powder for 1h at 4°C, washed in PDB and added to the protein solution in 100μL PDB, followed by incubation for 1h at 4°C. Washes were performed twice with each of the following buffers: PDB buffer with 5% skim milk powder, high-salt PDB buffer (250mM KCl), and PDB buffer with added 0.2% Sarkosyl and 0.2% Sarkosyl and 5% skim milk powder. Final washes were performed once with 500μL PDB buffer and once with 40μL PDB. Proteins were eluted by incubating the beads at room temperature for 10min in 15μL of 1× Bolt LDS loading buffer (Invitrogen, B0007). After elution from beads, β-mercaptoethanol was added to a final concentration of 5%, and samples were heated at 70°C for 10min. Proteins samples were examined by western blotting.

Coimmunoprecipitation of whole cell extract
Protein A/G beads (Thermo Fisher, 88803) were washed in RIPA-IP 137 (137mM NaCl, 50mM Tris-HCl pH 7.5, 10% NP-40) and incubated in RIPA-IP 137 + 1% BSA for 30min at 4°C. Beads were then incubated in 1µg of either anti-TOP1 (Abcam, ab109374), anti-MYC (Abcam, ab32072), or anti-IgG (Cell Signaling Technology, 2729) primary antibodies in RIPA-IP 137 for 3h at 4°C. HCT116 cells were harvested, spun down and washed once in PBS (Thermo Fisher, 14190169). Cells were then lysed by sonication using Bioruptor (Diagenode) at high amplitude with 20 cycles of 30s ON and 30s OFF in native lysis buffer (50mM HEPES, 150mM NaCl, 1mM EDTA, 1% Triton X-100) supplemented with protease inhibitors (cOmplete, EDTA-free protease inhibitor cocktail (Merck, 4693132001), 0.5mM AEBSF (Merck, A8456), 10μM Leupeptin (Merck, L2023), and 1μM Pepstatin A (Merck, P5318)), before treating with 12.5 units of benzonase (Merck, E8263) for 15min. Next, cells were centrifuged to separate the cell debris from the resulting lysate. Lysate from 1 million cells was pre-cleared with blocked protein A/G beads without antibody for 1h at 4°C. Beads incubated with anti-TOP1 and anti-IgG antibodies were washed twice in RIPA-IP 137 before adding the pre-cleared lysate and incubating for 1h at 4°C. Supernatant from the resulting TOP1 IP was then incubated for 1h with anti-MYC bound beads at 4°C, while the supernatant from the IgG IP was incubated with another round of anti-IgG bound beads. Beads were washed twice with RIPA-IP 137, twice with RIPA-IP 137 0.2% sarkosyl (137mM NaCl, 50mM Tris-HCl pH 7.5, 0.2% sarkosyl) and twice with RIPA-IP 300 (300mM NaCl, 50mM Tris-HCl pH 7.5, 10% NP-40). All wash buffers were supplemented with the protease inhibitors. Proteins were eluted from beads at room temperature in 1× NuPage LDS sample buffer (Invitrogen, NP0007). After elution from beads, β-mercaptoethanol was added to a final concentration of 5% together with 0.2M DTT, and samples were heated at 70°C for 10min. Samples were probed using western blotting as described above.

Chromatin-bound protein harvest for western blot from Halo-TOP2A HCT116 TOP1-AID cells
Halo-TOP2A HCT116 TOP1-AID cells were treated with 0.1mM auxinole for 24h to block TOP1 degradation, or with 500μM auxin for 60 or 120min. Cells were counted using a Countess 3 cell counter (Invitrogen), and 1×106 cells were harvested per condition. For the TOP1 harvest in the chromatin fraction, the same protocol as for the glycerol gradients was followed.

Single molecule tracking (SMT)
Halo-TOP2A HCT116, Halo-TOP2A HCT116 MYC-AID or Halo-TOP2A HCT116 TOP1-AID cells were plated in 4-well Lab-Tek II Chamber slides (Nunc, 155382) in phenol-free high-glucose DMEM media (Thermo, 31053028) with 10% FBS and GlutaMAX to achieve 40-50% confluence upon imaging 48h later. To image nucleoli, we transfected with a 1:99 ratio of GFP-Nucleolin vector (Addgene, 28176) and an empty vector (pCDNA4/TO, Thermo, V102020) 24h after plating using Lipofectamine 3000 (Thermo, L3000008), according to the manufacturer’s protocol. The TOP2A was then labeled with 100nM photo-activatable Janelia Fluor (JF) 549 Halo ligand and 10nM JF-646 Halo ligand (both gifts from Luke Lavis) for 30min at 37°C in the cell culture incubator. The cells were then washed three times with warmed PBS and incubated for 15min in growth media. This washing process was repeated once before the media was replaced again with growth media to remove all excess Halo ligand. If cells were treated with 500μΜ auxin, the auxin was included during both 15min incubations and in the final media suspension to ensure knockdown had occurred for at least 30min for MYC degradation and 75min for TOP1 degradation before imaging. Treatment with 5μM triptolide (Merck, T3652), 10μM camptothecin (Merck, 208925) or 2,5% 1,6-hexanediol (Merck, 240117) was added in the final solution and imaging would begin after the requisite amount of time.

Cells were imaged using a custom-built microscope able to perform single-molecule imaging by HILO illumination as previously described32. Nuclear TOP2A distribution was determined from the JF-646 channel, enabling distinction between the nucleolus and the nucleoplasm based on the staining intensity. Photo-activation of the JF-549 ligand was achieved by tuning the power of a 405nm laser to ensure 2–5 molecules of JF-549 ligand were photo-active in each frame. For each video, 3000 frames were captured at 100 frames per second. Measurements for the nuclear, nucleolar, and nucleoplasmic regions were determined by only analyzing the region of interest after manually segmenting based on the TOP2A JF646 signal. The path of individual molecules from the SMT video was determined using the ImageJ Trackmate plugin82 without gaps being allowed and with 0.5–1μm maximum linking distance depending on track density. Tracks were classified into fast, slow, and bound molecules using the vbSPT algorithm34, excluding tracks shorter than 4 frames.

To calculate diffusional anisotropy, we removed bound track segments and calculated the angle between consecutive displacements. The anisotropy index was calculated as the ratio of the number of backward jumps (with an angle between jumps in the [150°, 210°] range) over the number of forward jumps (angles in the range [−30°, 30°]). Plotting the anisotropy index as a function of the distance run by the molecule allows discrimination between exploration modes. Error bars were calculated as the standard deviation from 100 random subsampling composed of 50% of the original data. Analysis of diffusion coefficients and fractions at the single cell level was performed by analyzing the distribution of displacements with a three-component diffusion model, as described previously32.

Cross-correlation analysis was performed as previously described32. Briefly, co-clustering between bound and diffusing molecules was evaluated by first identifying the centroid of each track segment corresponding to bound molecules, and then calculating the cross-correlation between these centroids and the positions of all the particles classified as either “slow diffusing” and “fast diffusing”. The resulting cross-correlation plots were then compared to those obtained from the distances between bound molecules and random positions in the nucleus.

The spectrum of diffusion coefficients was evaluated from SMT data using SASPT, a method that uses a Bayesian nonparametric approach to infer the posterior distribution of diffusion coefficients across an array of finite possible states (diffusion coefficients ranging from 10-2 to 102). SASPT was run with the following settings: focal depth 0.7µm, sample size 10000, likelihood type RBME. Mean posterior occupation across the population of tracked cells is displayed83.

Quadruple-trap (Q-TRAP) optical tweezers
Single-molecule TOP2A decatenation assays were performed using the Q-TRAP optical tweezers (Lumicks). Two molecules of lambda DNA with biotinylated ends (Lumicks, 00001) were each bound to two SPHERO streptavidin-coated polystyreneparticles (Spherotech, SVP-40–5) held by optical tweezers. These particles were manipulated to intertwine the two DNA molecules, forming five DNA crossovers. This structure was then moved into a channel that had been passivated overnight in passivation buffer (50mM Tris pH 8, 150mM NaCl, 10mM MgCl2, 0.5% pluronic, 0.1% BSA). This channel contained 10–50nM SNAP-TOP2A labeled with SNAP-647 ligand, 100–300nM MYC or equivalent BSA, 50mM Tris pH 8, 150mM NaCl, 10mM MgCl2, 450nM BSA, 0.5mM DTT, 50μΜ Sytox Orange, and 2mM ATP where required.

The exact time of entrance of the DNA crossover into the protein channel was determined by the background photon count in the TOP2A channel. The exact time of decatenation was determined by the change in the force acting on the polystyrene particles. Droplet formation at the crossover was measured by comparing the intensity of TOP2A at the DNA crossover, subtracting the background TOP2A signal surrounding the crossover and comparing this value to a threshold for TOP2A crossover binding.

Stimulated emission depletion (STED) microscopy
HCT116 cells were plated onto 18mm coverslips (Marienfeld, 630-2200) in 12-well plates and grown to 50-60% confluency. After the indicated treatment, cells were fixed in 3% paraformaldehyde (PFA, Pierce, 28908) in PBS for 5min at room temperature. After washing with PBS, cells were permeabilized in methanol for 3min at −20°C, before washing again in PBS and blocking in 2% BSA (Merck, A7906) in PBS for 30min at room temperature. Proteins were fluorescently labeled by sequential incubation with primary (1:200 dilution) and fluorescently labeled secondary (1:400 dilution) antibodies for 1h each in 0.5% BSA/PBS. These antibodies include anti-MED4 (Thermo Fisher, 67839-1-IG), anti-H3.3 (Active Motif, 91191-AF), anti-RPA194 (Santa Cruz, sc-46699), anti-nucleophosmin (Abcam, ab10530), anti-TOP2A (Abcam, ab52934), anti-mouse-AF555 (Thermo Fisher, A-21422), and anti-rabbit-647 (Thermo Fisher, A-21245). For triple protein labeling, the rabbit anti-fibrillarin conjugated to Alexa Fluor 488 (Abcam, ab184817) was used. To prevent binding of this antibody to other rabbit secondary antibodies, following the secondary antibody incubation and subsequent wash, the slides were incubated with rabbit IgG (Merck, 12–370, 1:200 dilution) to block free anti-rabbit secondary antibody binding sites. Then, the slides were incubated with anti-fibrillarin-488 (1:200), with DAPI if required. After washing, coverslips were mounted onto slides in a hard-setting ProLong Diamond Antifade Mountant (Thermo, P36970). In some cases, DAPI was not included to prevent bleed-through into other channels, since the nucleus was clearly visible by TOP2A/MED4 staining.

Multi-color STED imaging was performed on a Leica SP8X system, equipped with a tunable white-light laser (excitation 470–670nm), high-power green/orange/red depletion lasers (592, 660, 775nm), a chromatically optimized 100×/1.4 STED WHITE oil immersion objective, and single photon sensitive detectors (HyD-SMDs). Nuclear protein structures were imaged sequentially frame by frame (1024×1024 pixels) at a speed of 200 lines per second (4-line averages) with a pixel size of 25nm and pinhole settings of 0.9-1.0 Airy units. STED images were deconvoluted using the Huygens 24.10 software (Scientific Volume Imaging) before data analysis. Images were analyzed using custom Matlab scripts. Briefly, the central points of nucleoplasmic puncta were determined at a sub-pixel resolution. Then, the signal from the observed channel surrounding the detected puncta is averaged and plotted.

Airyscan microscopy
HCT116 cells were plated onto 18mm coverslips (Marienfeld, 630–2200) in 12-well plates and grown to 50% confluency and treated with 5% 1,6-hexanediol for 5min. After treatment, cells were fixed, permeabilized, blocked, and labeled for TOP2A and MED4 using the materials and methods as described for STED imaging. Cells were imaged using a Zeiss LSM900-Airy confocal microscope using the 63× magnification objective.

Quantitative PCR (q-PCR)
HCT116 cells were treated as indicated, then RNA was purified using NucleoSpin RNA columns (Macherey-Nagel, 740955) according to kit instructions. Equal amounts of RNA resuspended in 13ul H2O were mixed with 1ul of 10mM dNTP (10mM each of dATP, dCTP, dGTP, dTTP; Promega, U1205, U1215, U1225, U1235) and 0.5ul of random hexamers (Promega, C1181). This mixture was heated at 65°C for 5min, then put on ice for 1min. 4ul RT buffer, 0.3ul SuperScript IV Reverse Transcriptase (both Thermo, 18090200), 1ul 0.1M DTT (Merck, 43815) and 0.2ul of RNAsin Ribonuclease inhibitor (Promega, N2515) were added. The solution was incubated at room temperature for 10min, followed by 50°C for 30min to transcribe cDNA, and at 80°C for 10min to stop the reaction. The cDNA was diluted, and quantitative PCR was performed using Fast SYBR Green Master Mix (Thermo, 4385612) with previously published84 primers for the internal transcribed sequence (ITS) of the 47S pre-ribosomal RNA (F: CCGTGGCCTTAGCTGCTCGC, R: CCCACTTAACTATCTTGGGCTG) and beta-2-microglobulin (B2M; F: GAAACCTTCCGACCCCTCT, R: GCCAGACGAGACAGCAAAC). The ΔΔCt method was used to measure ITS expression relative to B2M, normalized to the control condition.

TOP2 covalent adduct detection coupled to sequencing (TOP2 CAD-seq)
3×107 (HCT116 MYC-AID) cells were treated (in biological triplicates) with auxin, followed by 10μM MG132 (Merck, 474790) for 30min and 100μM etoposide in the last 6min to trap TOP2cc. Cells were lysed in 4.5mL of M buffer (9.3mM Tris-HCl pH 6.5, 18.6mM EDTA, 5.59M guanidine thiocyanate, 0.93% DTT, 0.93% Sarcosyl, 3.72% Triton X-100) and briefly sonicated with Bandelin probe sonicator at 20% amplitude for 1s. DNA covalent adducts were precipitated with 50% EtOH at −20°C, centrifuged at 21130×g at 4°C and pellets were washed thrice in wash buffer (20mM Tris-HCl, pH 7.5, 50mM NaCl, 1mM EDTA, 50% EtOH). Ethanol leftovers were aspirated, and pellets were dried for 5min and resuspended in 1ml of EB-SDS 0.05% (10mM Tris-HCl, pH 8, 0.05% SDS). After 30min incubation by gentle agitation, 500μl of each sample was further fragmented with benzonase (0.02U/μg) at 37°C for 15min. The reaction was stopped with 50mM EDTA and 0.1% SDS. For the immunoprecipitation 3.5μg of a 1:1 mixture of anti-TOP2A (sc166934 and ab52934) antibodies were mixed with 25μl Protein A/G magnetic beads (Pierce, 88803) and incubated at 4°C for 4h with rotation. Beads were washed once with ice-cold PBS, and DNA covalent adducts from 1.5×107 cells were added to the Protein A/G-antibody complexes and incubated overnight at 4°C with rotation. Samples were washed once with RIPA buffer, once with RIPA buffer containing 300mM NaCl, once with LiCl-SDS 0.1% buffer (10mM Tris-HCl pH 8, 1mM EDTA pH 8, 250mM LiCl, 0.5% NP40, 0.5% Na-Deoxycholate, 0.1% SDS) and twice with TE-SDS 0.1% (10mM Tris-HCl pH 8, 1mM EDTA pH 8, 0.1% SDS). The beads were then resuspended in 100μl TE plus 0.5% SDS supplemented with proteinase K (500μg/ml) and incubated for 4h at 60°C. Samples were then purified using the QIAquick PCR Purification Kit.

Library preparation and sequencing of TOP2 CAD-seq
DNA from TOP2ACAD samples was quantified with the Qubit dsDNA HS Assay Kit (Thermo Fisher, Q33230). To cleave off covalently bound tyrosyl residues from TOP2A, the samples were additionally treated with Exo VII (NEB, M0379S) (0.5U per 10ng of DNA) and purified by PCR Purification Kit (QIAGEN, 28106). Sequencing libraries were created according to the ThruPLEX DNA-seq kit protocol (Takara, R400676). Size selection was performed in the range of 200–700bp with AMPure XP beads (Beckman, A63880) and confirmed using the Agilent High Sensitivity DNA Kit (Agilent, 5067–4626) on the Agilent 2100 Bioanalyzer. Libraries were pooled and sequenced using the NextSeq 1000/2000 P2 XLEAP-SBS Reagent Kit (100 Cycles) (Illumina, 20100987). The sequencing run was Pair End and Dual Index with 2×50bp reads.

SLAM-seq
A modified version of SLAM-seq85 was used to measure nascent RNAs over the full transcript length. A total of 2×106 HCT116 MYC-AID cells were treated (in biological triplicates) with 500μM auxin for 90min or with 0.1mM auxinole for 24h before harvesting. 4-Thiouridine (S4U; 100μM) was added to the medium of all samples in the dark 75min before the harvest. Cells were washed twice with fresh medium and scraped stepwise in 2× 0.5ml of ice-cold TRIzol LS Reagent (Invitrogen, 10296010) and proceeded immediately to the next step. For RNA isolation, we followed the manufacturer’s instructions of SLAM-seq Kinetics Kit-Anabolic Kinetics Module (Lexogen, 061.24) except for the following modifications: Samples were incubated for 5min at 65°C and mixed with 200μl of chloroform:isoamyl alcohol mix (24:1) (Merck, 25666), before further incubation for 15min at 65°C under strong agitation (2000rpm) and repeated vortexing. RNA in the aqueous phase was separated by centrifugation at 16000g for 15min at 4°C, supplemented with the provided reducing agent and again extracted with one amount of chloroform:isoamyl alcohol mix (24:1) before precipitation overnight at −80°C. RNA was pelleted for 20min at 16000×g, washed twice with 1 and 0.18ml of 80% EtOH (plus reducing agent), respectively, and pelleted for 10min at 7500×g. Resuspension in the elution buffer (provided by the SLAM-seq Kinetics Kit) was facilitated by incubation for 15min at 55°C, 10min on ice and gentle pipetting to avoid fragmentation of RNA. RNA was quantified with the Qubit RNA HS Assay Kit (Invitrogen, Q32852) and its integrity was controlled using the RNA 6000 nano kit (Agilent, 5067–1511) on a Bioanalyzer 2100 (Agilent). To facilitate normalization of the sequencing reads, the isolated RNA was mixed with ERCC RNA Spike In-Mix (Invitrogen, 4456740). Specifically, RNA (4.5μg) was mixed with 2μl of 1:10 diluted ERCC RNA Spike In-Mix, and the elution buffer was added to fill up to 10μl. Next, 4.5μg RNA mixed with ERCC was taken, the elution buffer was added up to 15μl, and alkylation was performed by the addition of iodoacetamide following the manufacturer’s instructions. Once again Qubit RNA HS Assay Kit (Invitrogen, Q32852) was used to quantify the RNA, and RNA integrity was controlled using the RNA 6000 nano kit (Agilent, 5067–1511) on a Bioanalyzer 2100 (Agilent). Ribosomal RNAs (rRNAs) were depleted from 950ng of alkylated RNA using the RiboCop (HMR) kit (as part of the CORALL Total RNA Seq V2 12nt B1 UDI12B_0001-0024, Lexogen, 184.24) following the manufacturer’s instructions, except for increasing the volume for RNA elution to 16μl. Removal of rRNAs was confirmed using the RNA 6000 Pico Kit (Agilent, 5067–1513) on a Bioanalyzer 2100 (Agilent).

Library preparation and sequencing of SLAM-seq
To prepare cDNA libraries spanning the whole transcript length, the CORALL Total RNA Seq V2 12nt B1 UDI12B_0001-0024 (Lexogen, 184.24) was used, which includes reverse transcription with displacement stop primers. Ten microliters of the rRNA-depleted RNA were used as input material, and the final library was amplified by 15 PCR cycles as defined from the PCR Add-on and reamplification Kit V2 for Illumina (Lexogen, 208.96). DNA concentration and molarity were determined by Qubit dsDNA HS Assay Kit (Invitrogen, Q33231) and Bioanalyzer High Sensitivity DNA Kit (5067–4626) on a Bioanalyzer 2100 (Agilent), respectively. Libraries were pooled and sequenced using the NextSeq 1000/2000 P2 XLEAP-SBS Reagent Kit (100 Cycles) (Illumina, 20100987). The sequencing run was paired-end and dual index with 2×53bp reads.

TOP2 CAD-seq data analysis
The generated fastq files were quality controlled with FastQC (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) and MultiQC86, trimmed with cutadapt (http://journal.embnet.org/index.php/embnetjournal/article/view/200/479), aligned to the hg38 reference genome with bowtie287, deduplicated, sorted and indexed using Samtools88 and Picard (http://broadinstitute.github.io/picard). RPM normalized BigWig files were generated with bamCoverage89. The coverage matrices, profiles and heatmaps of short reads’ average distribution near TSSs and along normalized gene bodies of protein-coding genes were generated by deeptools commands computeMatrix and plotHeatmap. The expression of the genes was determined based on the SLAM-seq data12. The genes were ranked according to SLAM-seq spike-in normalized counts in descending order, and the top 1500 were selected for Fig. 5G, H. Peaks were called using Macs3 callpeak, and peak summits were used for plotting.

SLAM-seq data analysis
Nascent RNA reads from the SLAM-seq were processed using the established pipeline slamdunk90 (https://github.com/jkobject/slamdunk). Since the sample preparation deviated from the standard SLAM-seq method, for instance, in the library preparation, the pipeline was adapted accordingly. The quality of the FASTQ files was assessed with FastQC (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) and MultiQC86. UMI extraction was performed as in the CORALL analysis pipeline from Lexogen (https://github.com/Lexogen-Tools/corall_analysis) and adapter trimming of FASTQ using cutadapt (v.5.2, http://journal.embnet.org/index.php/embnetjournal/article/view/200/479). Read were aligned with NextGenMap (v0.5.5, https://github.com/Cibiv/NextGenMap) to the hg38 and ERCC reference genome, and the resulting files were sorted and indexed using Samtools91. After deduplication with UMI_tools92 (v1.1.6), slamdunk filter was run with hg38 expressed protein-coding genes or ERCC genes as opposed to just the 3′ untranslated regions, followed by single-nucleotide polymorphism detection via slamdunk snp. Nascent human reads with T>C conversions were counted using slamdunk count using a T>C conversion threshold of ≥2. Then, T>C conversions were separated from background reads using the alleyoop read-separator command from the slamdunk package. Human T>C counts were normalized to ERCC filtered reads for each sample by applying a spike-in-based scaling factor defined as (ERCC filtered reads in the lowest-ERCC sample)/(ERCC filtered reads in each sample). Spike-in normalized T>C counts per gene were then divided by gene length (kb) and log10-transformed after addition of a pseudocount (+1).

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The manuscript by Cameron and colleagues studies the intranuclear trafficking of TOP2A, its partitioning between the nucleolus and the nucleoplasm, its diffusion, its association with MYC, and its relationship to transcription. The data, the results, and discussion are interesting and generally well-done ,and they suggest the importance of regulating intranuclear diffusion. Nevertheless, there are several major and minor issues that if addressed would improve the presentation so that it would merit presentation to the broad community of biophysicists, biochemists, and cancer biologists.\nMajor issues:\nPrevious work from this group has shown that MYC combines with TOP2A and TOP1 in a “topoisome”. The current work does not provide any context for discriminating the actions and trafficking of a TOP2A-MYC complex versus a topoisome. (Incidentally it is unclear to this reviewer if the previously defined topoisome is the same as the currently described TOPOisome. If they are the same, then the previous term “topoisome” should be retained for simplicity. As the previous term has been used already in reviews and other papers, there is no need to complicate the terminology by introducing a new term.) The authors focus on diffusion by TOP2A-MYC complexes and do not address the issue of distinguishing these bimolecular complexes from topoisomes. What are the relative abundances of TOP2A-MYC versus topoisomes? If TOP1 were to be doped into the TOP2A condensates in vitro, how would the rates of diffusion vary? How would the addition of a TOP1 poison (i.e. CPT) influence the diffusion rate of TOP2A?\nLine 283. It is not clear to me that condensates are forming on the ionically immobilized-DNAs rather than polymer encagement TOP2A molecules. The authors assert that because the sizes of spots vary, proves that multiple TOP2As must be included—this assertion doesn’t hold water in my view. The sizes of the interstices of the tangled DNA molecules that encage a single TOP2A would be expected to vary considerably, and if so then, so to would the excursions of the trapped molecules vary accordingly. But, if the number of molecules per cage varied, then the brightness would be expected to change incrementally. So, the relative immobility of the TOP2A and its occurrence at very concentrations may not be a result of phase separation but may reflect entrapment within a DNA matrix due to a high local concentration of binding sites.\nLine 394. The authors claim that there is no general downregulation of transcription after auxin-depletion of MYC. Therefore, the loss of TOPSAcc’s at promoters was not due to decreased transcription. But they make this assessment using whole cell fluorescence after EU incorporation. At the cellular level rRNA accounts for the vast majority of RNA synthesis. So, without some measure of ongoing RNAPII activity, the authors cannot be certain that transcription is unimpaired. In fact, wouldn’t ongoing transcription be expected to decline when MYC is degraded?\nMinor issues:\nLine 84: co-localization, yes, but on what basis is this a condensate?\nLine 234: relieve, not relief\nLine 247: The authors have an interesting result upon which they make no comment. Triptolide actually increased TOP2A mobility in all cases. This should be mentioned. Does the inhibition of ERCC3 by the drug inhibit PIC formation or does it release previously recruited TOP2A?\nLine 262 how does this compare with in vivo concentration?", "reviewer_2": "Topoisomerases are essential proteins that resolve DNA supercoiling and entanglements, thereby relieving topological stress. In a previous study, the authors’ group showed that the oncoprotein MYC stimulates topoisomerases to remove DNA entanglements generated by oncogenic transcription. In the present study, the authors claim that TOP2A in human cells exists in a dynamic equilibrium between sequestration in the nucleolus, substrate searching in transcription condensates, and active engagement on chromatin (three distinct diffusion states). Using single-molecule approaches, they suggest that MYC regulates TOP2A activity by affecting the diffusion state of TOP2A-containing complexes (“TOPOisomes”).\nInterestingly, MYC accelerated the diffusion of TOP2A in the nucleoplasm, potentially by limiting the size of protein complexes containing TOP2A. This may enhance TOP2A’s substrate-searching ability, thereby increasing its activity at transcribed regions. While the authors’ story is intriguing, several points are missing to support their main conclusion, and some aspects of data interpretation and presentation are also weak. My specific comments are as follows.\nMajor points:\n1) Fig. 1. As the authors mention, TOP2A expression increases during S-phase, peaks in mitosis, and is subsequently degraded (Refs. 48, 49). The nucleolar accumulation of TOP2A during the cell cycle should be presented.\nIn addition, did the total TOP2A level in the nucleus change after either TOP1 depletion or ICRF treatment? It is important to rule out the possibility that the decrease in the nucleolar/nucleoplasmic ratio is due to changed TOP2A levels rather than translocation.\n2) Fig. 2I–J. Although the authors claim that the slowly diffusing TOP2A corresponds to molecules diffusing in transcriptional condensates, direct evidence appears to be lacking. The data only show that the TOP2A inhibitor ICRF-193 reduces the accumulation of TOP2A at MED4 puncta, whereas the slow fraction remains unchanged following ICRF treatment (Fig. 2C).\n3) Fig. 5E. I wonder whether TOP2A can form liquid droplets under the buffer conditions used in the Q-trap assay. The buffer used in the droplet assay contained 20% glycerol, which may be required for TOP2A–DNA droplet formation. The buffer for the Q-trap assay, however, did not contain glycerol. If TOP2A does not form droplets under the Q-trap assay conditions, how can MYC accelerate the binding events of TOP2A at DNA crossovers?\n4) Overall, the quality of data presentation is low. For instance, in Fig. 2I and Extended Data Fig. 3A, are the scale bars accurate? The TOP2A puncta appear to be around 5 µm in size, which seems too large.\n5) Extended Data Fig. 6g. This figure indicates that the cell population with low EU increased after MYC depletion. This appears to conflict with the authors’ interpretation (Line 396).\nMinor points:\n1) Fig. 1A. This panel is confusing. DAPI staining is needed to visualize the nuclear structure.\n2) Line 95. It is known that RNAPI transcription inhibitors alter the nucleolar structure (nucleolar cap formation).\n3) Which MYC subtype did the authors use? Please specify in the Methods section.\n4) Line 222. Structured illumination light sheet microscopy (SIM)?\n5) Code availability: The provided codes (https://github.com/don-cameron/Cameron-et-al.-2025/tree/main) have empty “readme.md” files for pixel correlation plotting and for the general instructions for the entire dataset!", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_4": "This is very interesting and strong work built on the previous finding from some co-authors as well as an existing literature. It provides a step forward in the understanding of MYC function which is a big and important question in Mutiple fields. Study used an impressive set of biophysical, biochemical and cell-based methods.\nBelow is my review:\nThe manuscript of Cameron an co-authors uncover one of the mechanisms of how MYC boosts transcription. They provided data that TOP2A exists in cells in a balanced distribution between nucleolar and nucleoplasm. In nucleoplasm, TOP2A is distributed between different states depending on its diffusion coefficients: a bound fraction interacting or catalytically engaged with chromatin, a slow fraction enriched in transcription condensates, and a fast fraction diffusing through the nucleoplasm. They then showed that degradation of MYC reduced TOP2A diffusion rates in slow and fast fractions. They showed that MYC promotes TOP2A mobility via reducing the size of TOP2A droplets in cell free conditions and TOP2A complexes in cells. This allows faster search of targets by TOP2A and more efficient resolution of supercoiling needed for transcription.\nThis is very strong and rigor study using multiple experimental approaches, as well as accurately and clearly written. I just have several questions/comments, which I hope authors can clarify.\nLines 78-79: “was lost along with nucleolar protein fibrillarin upon further treatment with RNase A (Fig. 1b and Extended Data Fig. 1d), suggesting its association with nucleolar structures was maintained by ribosomal RNA” . Was the mechanism of TOP2A association with rRNA already known? Please provide refs or explain.\nContradictory impression between image Fig 1B vs quantitation Fig. S1D. Control image shows signal from nucleolus and nucleoplasm, CSK image – only nucleolar signal, RNAse image – only nucleoplasm. Quantitation shows that control = RNAse. Please explain.\nFigure 1E and F and all other plots of the same type show very few dots while more around thousand cells were measured and mentioned in the legend. What do dots represent?\nLines 123 – 125: “ We observed an increase in DNA damage only after TOP1 degradation by auxin and etoposide treatment” and Fig.1F, ext Fig,2A and B. It is unclear why the gammaH2AX signal increased only after TOP1 degradation. Etoposide interactions with TOP2A should be independent on TOP1. Also based on presented images – without TOP1 degradation, it is decreased in response to etoposide treatment in ext fig 2A, and increased in ext fig 2b.\nLines 151-153: “Notably, TOP2B distribution across the nucleus was much more homogeneous as compared to TOP2A, although ICRF-193 also caused a slight re-localization nucleolus-to-nucleoplasm (Extended Data Fig. 2f,g) suggesting it may also be responsive to similar stimuli to TOP2A, although the TOP2A response was more pronounced.” Is there enough structural difference between two tomoisomerases to explain why this mechanism is much more pronounced in TOP2A vs TOP2B. It may be good to discuss.\nLine 163 “we found that nuclear TOP2A diffusion could be categorized into three distinct populations.” It would be good to show the actual distribution of diffusion coefficients, like histogram or in some other way.\nFigure 2G is unclear. Should it contain colored lines according to the colors of FAST and SLOW? What exactly is the black line?\nLine 198: “If the slow TOP2A fraction reflects TOP2A localized in transcription condensates and the bound fraction corresponds to TOP2A interacting with chromatin,” Should not the slow and bound overlap, since bound should perform its activity within transcriptional condensates.\n“transcribed chromatin labelled with H3.3” – H3.3 is not a very specific mark of transcription, since although in general it is enriched in transcribed regions, these transcribed regions are not transcribed all the time, taking into account transcription bursts, and transcription of many genes in a time-dependent manner (e.g., cell cycle). More accurate marks of the presence of transcription can be used, like EU incorporation.\nLine 242: “we found that although the proportion of TOP2A found in the fast, slow, and bound fractions were largely unchanged”… do you mean the amount or just the ratio between fractions? Then, was the amount changed?\n“MYC mutant containing only residues 200-320 (MYC200-320)” why this form of myc is important? It was mentioned later that it does not bind TOP2A, but it should be better to explain at the first instance.\nFig.4H “average of six experiments”: what four data points represent?\nWhy did they use K562 MYC-AID cells in just one section of the manuscript if they already made HCT116 MYC-AID cells?\nFig. 5A: Was the exposure for the control and auxin the same? It looks like the amount of TOP2A in the auxin condition has been increased. Some of the replicates in the extended data provide a better illustration of the author’s interpretation.\nCrossover experiment: what was visualized and quantified? Individual TOP2A molecules or droplets.\nFig. 5H: Does degradation of MYC lead to reduced transcription? Total EU incorporation was not reduced, but gene expression is a minor fraction of total transcription. How about these 1500 genes?\nLine 461-463: “TOP2A molecules decrease by approximately 10%-15%. According to the Stokes-Einstein relationship, in first approximation, diffusion coefficients would scale as the cubic root of the diffusing complex, thus corresponding to roughly 30% to 50% larger complexes upon MYC degradation”. Math here is unclear. Cubic root of 30 and 50 are around 3 and 3.6 and not 10-15."}, "author_response": "Response to Reviewers\nWe greatly appreciate the helpful comments and suggestions from the three Reviewers.\nWe have carefully considered each comment and taken comprehensive actions to\naddress them. These comments prompted us to conduct many new experiments and\nperform several new analyses. The results of these experiments and analyses have\nprovided new insights and further strengthened the original conclusions of the manuscript.\nBelow, we start with a summary of significant changes to the main Figures and Extended\nData Figures. This is followed by a detailed, point-by-point response to each comment\nfrom the three Reviewers, with each comment (red) followed by our response (black). In\nthe resubmission, we have included a version of the manuscript where the changes are\nindicated in red.\nSummary of Significant Figure Changes:\n1. Reviewer #1 requested a clearer distinction between the topoisome and the\nTOP2A-MYC complex in terms of relative abundances, as well as clarifications\nof TOP1’s contribution to TOP2-MYC dynamics. In the past 3 months we have\nworked intensely on this comment. Through co-IP experiments, we now\nestimate that approximately 10% of TOP2A interacts with MYC as part of the\ntopoisome, while 4% forms distinct TOP2A–MYC complexes (Extended Data\nFig. 4c-e). We also performed droplet assays to investigate the colocalization\nof TOP1 with TOP2A and MYC and to determine whether TOP1 influences\nTOP2A droplet behavior. We had not previously worked with TOP1 in these\nassays, therefore enabling these experiments first required the purification and\ncharacterization of human recombinant SNAP-tagged TOP1. We found that\nTOP1 colocalizes with the TOP2-MYC droplets and that MYC reduces droplet\nsize both in the presence and absence of TOP1 (Fig 4g,l and Ext Data Fig.\n5m). Lastly, we performed SMT experiments to probe the effects of TOP1\ndepletion (by CPT or by auxin-mediated acute degradation) on TOP2A\ndiffusion. The results (shown in Extended Data Fig. 4f-h) indicate that\ninhibition or loss of TOP1 increases TOP2A diffusion. Since the TOP2A-MYC\ninteraction persists without TOP1 (Extended Data Fig. 4c,e), these results\nsupport the conclusion that MYC limits TOP2A complex size to promote\ndiffusion.\n2. Reviewer #1 requested stronger evidence for Mediator and TOP2 enrichment\nin transcriptional condensates, and Reviewer #2 questioned whether the slow-\ndiffusing fraction of TOP2A corresponds to molecules within transcriptional\ncondensates. Regarding the latter comment, direct SMT co-tracking is\ntechnically unfeasible, as intranuclear SMT is performed in a sparse labelling\nregime, strongly reducing the probability of observing correlated motion\n1\nbetween two differently labelled proteins. However, we now provide additional\nevidence linking TOP2A to Mediator-containing condensates, and that those\nare likely associated with the TOP2A slow fraction. Specifically, 1,6-hexanediol\n(HD), which disrupts Mediator-containing transcriptional condensates1, triggers\nTOP2A relocation to the nucleolar compartment (Extended Data Fig. 1d) and\nreduces the persistence of TOP2A puncta in the nucleoplasm (Fig. 1d,e).\nConsistent with these microscopy results, HD treatment also weakens the\nspatial cross-correlation between slow-diffusing and bound TOP2A molecules,\nwith a two-folds reduction relative to the control, indicative of decreased\nproximity. These new results are now shown as part of Extended Data Fig.\n3a-c.\n3. Reviewers #1, #2, and #3 requested more quantitative assessment of\ntranscriptional changes following MYC degradation. We therefore quantified\nnascent transcript levels across the genome using SLAM-seq2 after 90 minutes\nof auxin-induced MYC degradation. This short-term depletion had essentially\nno effects on the transcriptional output of the cells, nor did it alter the\ntranscription levels of the top 1500 transcribed genes (Extended Data Fig. 6\ng,h and Fig.5 h). These findings further strengthen the interpretation that the\nchanges in TOP2A activity result from direct regulation by MYC rather than\nsecondary transcriptional effects (Fig. 5g).\n4. Reviewer #1 suggested that the TOP2A puncta form as a result of polymer\nentrapment, where multiple TOP2A molecules could be connected by binding\nthe same DNA molecule. We ruled out this possibility by showing that TOP2A\npuncta are observed independently of DNA, indicating that their formation does\nnot rely on DNA bridging (Extended Data Fig. 5d).\n5. Reviewer #3 suggested labelling newly transcribed RNA with EU instead of\nusing H3.3 staining. While we agree that this approach is, in principle, more\nappropriate, we identified several technical limitations that, in our view, make it\nunsuitable for inclusion in the manuscript. Please see our discussion of this\npoint and Rebuttal Figure 3.\n6. We have included new control experiments, refined quantitative analyses, and\ncorrected several inaccuracies in data presentation—particularly within the\nmicroscopy datasets—to improve robustness and clarity of the results.\nReviewer #1 (Remarks to the Author):\nits partitioning between the nucleolus and the nucleoplasm, its diffusion, its association\nwith MYC, and its relationship to transcription. The data, the results, and discussion are\ninteresting and generally well-done ,and they suggest the importance of regulating\nintranuclear diffusion. Nevertheless, there are several major and minor issues that if\naddressed would improve the presentation so that it would merit presentation to the broad\ncommunity of biophysicists, biochemists, and cancer biologists.\nWe thank Reviewer 1 for their positive appraisal of our work. We have designed and\nperformed a range of experiments which we believe addresses their issues, and we\nbelieve that this has significantly improved the presentation of the data and strengthened\nthe underlying message. Specifically:\nMajor issues:\n1) Previous work from this group has shown that MYC combines with TOP2A and TOP1\nin a “topoisome”. The current work does not provide any context for discriminating the\nactions and trafficking of a TOP2A-MYC complex versus a topoisome.\nWe agree with the Reviewer. At present, it is technically challenging to discriminate\ntopoisome-associated TOP2A from other TOP2A by single molecule tracking given that\nwe do not have the capability to label more than one protein type. In addition, the sparse\nlabeling required for SMT means that typically only 5-10 proteins are fluorescently\nemitting at any timepoint. Even if both TOP2A and TOP1 could be simultaneously labeled\nand tracked, the chance that we could visualize two molecules diffusing together is\nnegligible, given there are upwards of 100,000 molecules of each protein in every cell.\nNonetheless, we have addressed this point indirectly, using other methods, including\nthose helpfully suggested by the reviewer below.\n2) (Incidentally it is unclear to this reviewer if the previously defined topoisome is the same\nas the currently described TOPOisome. If they are the same, then the previous term\n“topoisome” should be retained for simplicity. As the previous term has been used already\nin reviews and other papers, there is no need to complicate the terminology by introducing\na new term.)\nWe apologize for the confusion. We have changed all mentions to “topoisome” as the\nreviewer suggests.\n3) The authors focus on diffusion by TOP2A-MYC complexes and do not address the\nissue of distinguishing these bimolecular complexes from topoisomes. What are the\nrelative abundances of TOP2A-MYC versus topoisomes?\ndistinguishing bimolecular TOP2A-MYC complexes from topoisomes in live cells is\nchallenging. To address this point, we performed co-immunoprecipitation (co-IP)\nexperiments using lysate from HCT116 cells, which were employed throughout the\nmanuscript. Building on our previous findings3 that TOP1 immunoprecipitates TOP2A\nonly in the presence of MYC (and vice versa), thereby forming the “topoisome,” we\ndesigned an experimental strategy to estimate the relative proportions of TOP2A in the\ntopoisome versus in bimolecular complexes with MYC. Lysates were subjected to two\nsequential co-IPs: the first using anti-TOP1 antibodies, and the second—applied to the\nsupernatant from the first IP—using anti-MYC antibodies. The immunoprecipitated\nsamples were analyzed by Western blotting together with the input material, and the\nfraction of TOP2A in each complex was quantified relative to the input (Extended Data\nFig. 4c). Based on these analyses, we estimate that approximately 10% of TOP2A\ninteracts with MYC as part of the topoisome, in line with our previous estimation in U2OS\ncells under MYC overexpression3, while 4% forms TOP2A–MYC complexes (Extended\nData Fig. 4d,e). We note, however, that these values should be regarded as approximate,\nas they depend on antibody efficiency and IP stringency conditions. These new results\nare now shown as part of the revised manuscript.\n4) If TOP1 were to be doped into the TOP2A condensates in vitro, how would the rates\nof diffusion vary?\nLike the Reviewer, we were also curious to determine whether TOP1 changes TOP2A\ndynamics in relation to MYC. While measuring the diffusion of individual proteins within\nTOP2A condensates (either in vitro or in cells) is technically challenging, we approached\nthis request in three different but complementary ways.\nFirstly, we generated a recombinant SNAP-tagged TOP1 protein to include in our TOP2A\ndroplet assays and visualize how TOP1 partitions with the TOP2A-MYC condensates.\nPlease note that there have been no prior in vitro investigations of TOP1 in the context of\ncondensate formation. Prior to these experiments, we purified and biochemically\nvalidated the SNAP-tagged TOP1 protein, confirming that the tag does not alter TOP1\nenzymatic activity. We then measured whether TOP1 forms droplets on its own, whether\nit co-LOCALIZES with TOP2A droplets +/- MYC, and whether its addition affects the droplets\ndynamics. We found that fluorescently labeled TOP1 colocalizes into TOP2A\ncondensates both in the presence or absence of MYC, whereas only a few droplets form\nwith TOP1 + DNA as compared to TOP2A + DNA (Extended Data Fig. 5h). Quantification\nof the average droplet size revealed that MYC induced a decrease in TOP2A droplet size\neven in the presence of 500 nM TOP1. Thus, MYC’s ability to reduce TOP2A condensate\nsize and sedimentation likely extends to the entire topoisome. These new results are\nincluded in the revised Fig. 4g,l, and Extended Data Fig. 5m\ncamptothecin (CPT)—to trap TOP1 on the DNA and deplete free TOP1 from the\ntopoisome—and then measured TOP2A diffusion by SMT. TOP1 inhibition increased\nTOP2A diffusion across all fractions (Extended Data Fig. 4h). Since the MYC–TOP2A\ninteraction persists in the absence of TOP1, these results suggest that MYC limits\ncomplex size to promote TOP2A diffusion. However, because CPT also inhibits\ntranscription4, the increased diffusion across all the fractions might be partly a result of\ntranscriptional inhibition. Therefore, we engineered the HCT116 Halo-TOP2A with a\nTOP1 degron tag to monitor TOP2A diffusion after 2h of auxin-induced TOP1\ndegradation5 (Extended Data Fig. 4f) Under these conditions, the diffusion coefficient of\nTOP2A increased specifically in the slow and bound fractions, while no significant change\nwas observed in the fast fraction. These findings support the notion that in the absence\nof TOP1, the TOP2A-MYC complex is smaller and that the topoisome likely occurs\npredominantly in the transcription condensates and on the chromatin. All these new\nresults are now included in the revised Extended Data Fig. 4f-h.\n5) How would the addition of a TOP1 poison (i.e. CPT) influence the diffusion rate of\nTOP2A?\nWe have performed this experiment. Please, see the previous point.\n6) Line 283. It is not clear to me that condensates are forming on the ionically immobilized-\nDNAs rather than polymer encagement TOP2A molecules. The authors assert that\nbecause the sizes of spots vary, proves that multiple TOP2As must be included—this\nassertion doesn’t hold water in my view. The sizes of the interstices of the tangled DNA\nmolecules that encage a single TOP2A would be expected to vary considerably, and if so\nthen, so to would the excursions of the trapped molecules vary accordingly. But, if the\nnumber of molecules per cage varied, then the brightness would be expected to change\nincrementally. So, the relative immobility of the TOP2A and its occurrence at very\nconcentrations may not be a result of phase separation but may reflect entrapment within\na DNA matrix due to a high local concentration of binding sites.\nWe thank the reviewer for this thoughtful feedback and for offering an alternative\ninterpretation regarding the nature of the observed TOP2A puncta. We have carefully\nconsidered this explanation. However, we respectfully disagree with the interpretation that\nthe observed structures arise from polymer entrapment within a DNA matrix, and we find\nstronger support for the hypothesis that the TOP2A puncta represent condensates. Our\ninterpretation is based on several independent lines of evidence, as detailed below.\nFirst, if the observed puncta were due solely to DNA entrapment, one would expect to\nobserve DNA aggregates or puncta in the absence of TOP2A. However, when imaging\nDNA alone under the same conditions, we observe isolated DNA molecules without\n5\nclustering. This indicates that DNA itself does not spontaneously form larger\nclusters/structures and that the presence of TOP2A is required to organize DNA into\npuncta. In other words, it is TOP2A that recruits and organizes DNA, not vice versa\n(Rebuttal Figure 1).\nRebuttal Figure 1 Representative images from experiments with and without TOP2A. The images show\nthe fluorescently labeled DNA without (left) and with (right) TOP2A. The results show how DNA, on its own,\nis dispersed evenly across the functionalised glass surface, while in the presence of TOP2A it is found in\ndifferently sized puncta.\nSecond, we also detect TOP2A puncta under conditions where DNA is absent. This\ndirectly addresses the reviewer’s concern: if polymer encagement were the only\nmechanism, such puncta should not form without DNA. The presence of TOP2A puncta\nin DNA-free environments supports the idea that self-association or multivalent\ninteractions among TOP2A molecules contribute to puncta formation, consistent with\nphase separation or percolation (Rebuttal Figure 2, Extended Data Fig. 5d and Fig 4a,\ntop panel).\nDNA. The image showcases how TOP2A spontaneously organizes in puncta.\nFinally, regarding the reviewer’s expectation of discrete brightness steps, we agree that\nfor an ideal, perfectly labeled and photostable fluorophore this might be observed.\nHowever, in practice, fluorophore blinking, photobleaching, and sub-stoichiometric\nlabeling all contribute to variability in signal intensity. These factors are well-known\nlimitations in single-molecule fluorescence and explain why puncta brightness does not\nappear in discrete increments. We have revised the manuscript to include these\nclarifications and additional supporting data to make our reasoning more explicit.\n7) Line 394. The authors claim that there is no general downregulation of transcription\nafter auxin-depletion of MYC. Therefore, the loss of TOPSAcc’s at promoters was not due\nto decreased transcription. But they make this assessment using whole cell fluorescence\nafter EU incorporation. At the cellular level rRNA accounts for the vast majority of RNA\nsynthesis. So, without some measure of ongoing RNAPII activity, the authors cannot be\ncertain that transcription is unimpaired. In fact, wouldn’t ongoing transcription be expected\nto decline when MYC is degraded?\nThe reviewer is correct that MYC degradation would ultimately lead to a global reduction\nin transcription. However, we do not expect this effect to occur within the 90-minute time\nframe of auxin treatment. Nevertheless, following the reviewer’s suggestion, we quantified\nnascent transcription genome-wide using SLAM-seq, a method based on metabolic\nlabeling of newly synthesized RNA2. The data show that transcriptomic profiles are\nessentially unchanged upon 90min of auxin-induced MYC degradation indicating that the\nchanges in TOP2A activity are attributable to the direct effect of MYC on TOP2A dynamics\n(Fig. 5g,h and Extended Data Fig. 6g,h).\nMinor issues:\n8) Line 84: co-localization, yes, but on what basis is this a condensate?\nThis assumption is based on recent evidence from the Cissé Lab. Mediator was found to\nform stable clusters that associate with chromatin, display properties consistent with\nphase-separated condensates, and are sensitive to 1,6-hexanediol (HD)1. These clusters\ninteract with Pol II clusters within transcriptional condensates in vivo. Since Mediator and\nTOP2A clusters co-localize and exhibit similar size-distribution, we infer that TOP2A\nclusters may likewise correspond to transcriptional condensates. If this interpretation is\ncorrect, TOP2A clusters should similarly dissolve upon treatment with HD. To test this\npossibility, we examined (1) the persistence of TOP2A puncta and (2) the dynamics of\nTOP2A following HD treatment. Results confirm that HD disrupts Mediator-containing\ntranscriptional condensates (Extended Data Fig. 1d), in line with previous findings6 and,\nmore importantly, reduces the persistence of TOP2A puncta in the nucleoplasm (Fig.\n7\n1d,e). Consistent with these microscopy results, HD treatment also diminishes the spatial\ncross-correlation between slow-diffusing and bound TOP2A molecules, with a two-folds\nreduction relative to the control, indicative of decreased proximity (Extended Data Fig.\n3a-c). Together with our previous observation that HD induced TOP2A relocation to the\nnucleolar compartment (also shown in Extended Data Fig. 1d), the result provides\nadditional evidence linking TOP2A to Mediator-containing condensates, and that those\nare likely associated with TOP2A slow fraction (please, see also point 30 of this Response\nLetter).\nHowever, we acknowledge that these results do not constitute direct evidence. Additional\nexperiments, such as tagging Mediator in HCT116 TOP2A–Halo cells and performing\nlight-sheet imaging, would be required to strengthen this conclusion. Given the limited\ntime frame for resubmission, these experiments fall outside the scope of the current\nrevision. We have accordingly revised the text (lines 84–85) to clarify this point.\n9) Line 234: relieve, not relief\nWe thank the reviewer for the suggestion. We have checked with our native English-\nspeaking colleagues and the correct term should be “relief”.\n10) Line 247: The authors have an interesting result upon which they make no comment.\nTriptolide actually increased TOP2A mobility in all cases. This should be mentioned. Does\nthe inhibition of ERCC3 by the drug inhibit PIC formation or does it release previously\nrecruited TOP2A?\nWe thank the reviewer for drawing attention to this observation. We did not intend to\ndownplay its relevance; in fact, we view this control experiment as key evidence\nsupporting the direct effect of MYC on TOP2A dynamics, independent of MYC ability to\nregulate transcription.\nRegarding the effect of triptolide on TOP2A mobility, the most straightforward\ninterpretation is that triptolide, by inhibiting the helicase activity of XPB7, blocks\ntranscription initiation and elongation, thereby reducing the generation of transcription-\ninduced supercoiling8. As a result, TOP2A activity becomes less required, and the protein\nis less engaged with DNA, leading to an overall increase in its diffusion. Importantly, the\nabsence of a significant change in the diffusion coefficient of the fast fraction upon\ntriptolide treatment (Extended Data Fig. 4b), further indicates that the size of the freely\ndiffusing TOP2A complex remains unaltered. We have revised the test to include this\ninterpretation.\n11) Line 262 how does this compare with in vivo concentration?\nin vivo concentration of TOP2A with that used in our droplet assays.\nReports of cellular TOP2A concentration vary widely depending on the cell type and\nmethod of measurement. Quantitative mass spectrometry (MS) in Hela cells calculated\nthat an average cell contained approximately one million monomers of TOP2A equating\nto approximately 900nM/cell9. At the other end of the spectrum, a similar MS experiment\nin HCT116 cells calculated 188pmol of TOP2A per gram of protein, which equates to\napprox. 2.3x104 monomers of TOP2A, or 20mM/cell10. It is known that TOP2A varies\ngreatly depending on cell confluency11, which could partially explain the variance. Note\nthat these measurements are per cell, so the nuclear concentration could be 2-3 times\nhigher. Therefore, the predicted physiological nuclear concentration could vary between\n40nM-3μM, which agrees well with the concentrations used throughout this manuscript.\nWe have acknowledged in the text that the range of TOP2A concentrations used in this\nreport aligns with the reported physiological concentrations.\nReviewer #2 (Remarks to the Author):\nTopoisomerases are essential proteins that resolve DNA supercoiling and\nentanglements, thereby relieving topological stress. In a previous study, the authors’\ngroup showed that the oncoprotein MYC stimulates topoisomerases to remove DNA\nentanglements generated by oncogenic transcription. In the present study, the authors\nclaim that TOP2A incells exists in a dynamic equilibrium between sequestration in the\nnucleolus, substrate searching in transcription condensates, and active engagement on\nchromatin (three distinct diffusion states). Using single-molecule approaches, they\nsuggest that MYC regulates TOP2A activity by affecting the diffusion state of TOP2A-\ncontaining complexes (“TOPOisomes”). Interestingly, MYC accelerated the diffusion of\nTOP2A in the nucleoplasm, potentially by limiting the size of protein complexes containing\nTOP2A. This may enhance TOP2A’s substrate-searching ability, thereby increasing its\nactivity at transcribed regions. While the authors’ story is intriguing, several points are\nmissing to support their main conclusion, and some aspects of data interpretation and\npresentation are also weak. My specific comments are as follows.\nWe appreciate the reviewer’s thoughtful assessment and recognition of the significance\nof our study. Many of the reviewer’s comments request additional evidence supporting\nour conclusions. We thank the reviewer for the opportunity to clarify and strengthen these\nkey points in the revised manuscript.\nMajor points:\n12) Fig. 1. As the authors mention, TOP2A expression increases during S-phase, peaks\nin mitosis, and is subsequently degraded (Refs. 48, 49). The nucleolar accumulation of\nTOP2A during the cell cycle should be presented.\naccumulation over the course of the cell cycle, we treated HCT116 cells with EdU prior to\nfixation to label S-phase cells, and used DAPI nuclear intensity to distinguish G1 and G2\npopulations, in line with previous reports12. We then calculated TOP2A\nnucleolar:nucleoplasmic ratio as performed elsewhere in the manuscript. We did not\ndetect significant differences in overall nucleolar:nucleoplasmic ratio across G1, S, and\nG2 phase despite a significant increase in TOP2A levels in G2 phase. This suggests that\nthe equilibrium persists independently of TOP2A expression, at least with respect to the\ncell cycle. These new data are now included in Extended Data Fig. 1f,g of the updated\nmanuscript.\nIn addition, did the total TOP2A level in the nucleus change after either TOP1 depletion\nor ICRF treatment? It is important to rule out the possibility that the decrease in the\nnucleolar/nucleoplasmic ratio is due to changed TOP2A levels rather than translocation.\nThis is a valid point, and we thank the reviewer for raising it. Based on the quantification\nof TOP2A intensity from the microscopy pictures, we have not found that the overall\nTOP2A levels in the nucleus change upon either ICRF treatment nor TOP1 degradation.\nThese data are now included in Extended Data Fig. 2c,d of the updated manuscript.\n13) Fig. 2I–J. Although the authors claim that the slowly diffusing TOP2A corresponds to\nmolecules diffusing in transcriptional condensates, direct evidence appears to be lacking.\nThe data only show that the TOP2A inhibitor ICRF-193 reduces the accumulation of\nTOP2A at MED4 puncta, whereas the slow fraction remains unchanged following ICRF\ntreatment (Fig. 2C).\nWe thank the Reviewer for this insightful comment, which is related to a similar point\nraised by Reviewer #1. The Reviewer is correct that we do not have direct evidence\ndemonstrating that the slow-diffusing fraction of TOP2A corresponds to molecules moving\nwithin transcriptional condensates. It is technically unfeasible to address this directly by\nsingle-molecule tracking (SMT), as intranuclear SMT is performed in a sparse labelling\nregime, strongly reducing the probability of observing correlated motion between two\ndifferently labelled proteins.\nNevertheless, we observe that the slow fraction of TOP2A displays several features\nconsistent with proteins localized within transcriptional condensates, including (1)\nretention within a discrete compartment and (2) an average diffusional anisotropy greater\nthan 1, restricted to regions of approximately 150 nm, consistent with the reported\ndimensions of transcriptional condensates13.\nIn response to the Reviewer’s comment, we have also sought to provide additional\nevidence supporting this hypothesis. Mediator complexes are known to form stable,\nchromatin-associated clusters that exhibit hallmarks of phase-separated condensates6.\nHCT116 cells with HD and examined (1)the persistence of TOP2A puncta and (2) the\nbehavior of TOP2A by SMT analysis. The results show that HD disrupts Mediator-\ncontaining transcriptional condensates (Extended Data Fig. 1d), confirming previous\nfindings6 and, more importantly, reduces the persistence of TOP2A puncta in the\nnucleoplasm (Fig. 1d,e). Consistent with these microscopy results, HD treatment also\ndiminishes the cross-correlation between slow-diffusing and bound TOP2A molecules,\nwith a two-folds reduction relative to the control, indicative of decreased proximity.\nTogether with our previous observation that HD induced TOP2A relocation to the\nnucleolar compartment (also shown in Extended Data Fig. 1d), the result provides\nadditional evidence linking TOP2A to Mediator-containing condensates, and that those\nare likely associated with TOP2A slow fraction (please, see also point 30 of this Response\nLetter).\nTo prevent any potential misunderstanding, we have rephrased the sections of the text to\nclearly state that we lack direct evidence for TOP2A localization within transcriptional\ncondensates. We also note that further experiments, such as tagging Mediator in HCT116\nTOP2A–Halo cells and performing light-sheet imaging, would be required to conclusively\naddress this question. However, given the limited time frame for resubmission, such\nexperiments fall outside the scope of the current revision.\nFinally, regarding the Reviewer’s observation that “the slow fraction remains unchanged\nfollowing ICRF treatment (Fig. 2C)”, we would like to clarify that ICRF-193 treatment alters\nthe entire distribution of molecular displacements, resulting in a change of the measured\ndiffusion coefficients for each of the three species (bound, slow diffusing and fast\ndiffusing). The apparent lack of change in the slow fraction might thus depend on such\nclassification into three species. In addition, we now analyzed the SMT data in CTRL and\nICRF-193 treated cells using SASPT, a method that allows to compute the full distribution\nof diffusion coefficients observed (shown in the new Fig. 2b). The analysis confirms the\npresence of three peaks in the spectra of diffusion coefficients, and reveals that upon\nICRF-193 the peak corresponding to fast diffusing molecules is slightly shifted towards\nlarger diffusion coefficients (and is largely reduced in size), while slow moving molecules\nmove slightly slower.\n14) Fig. 5E. I wonder whether TOP2A can form liquid droplets under the buffer conditions\nused in the Q-trap assay. The buffer used in the droplet assay contained 20% glycerol,\nwhich may be required for TOP2A–DNA droplet formation. The buffer for the Q-trap\nassay, however, did not contain glycerol. If TOP2A does not form droplets under the Q-\ntrap assay conditions, how can MYC accelerate the binding events of TOP2A at DNA\ncrossovers?\nbuffer used for the droplet assay performed on the functionalized substrate (see Fig. 4d,e\nand Extended Data Fig. 5j) did not contain glycerol, yet TOP2A droplets were still readily\ndetectable under these conditions. Therefore, we have no reason to believe that TOP2A\nwould be unable to form droplets under the Q-trap assay conditions.\n15) Overall, the quality of data presentation is low. For instance, in Fig. 2I and Extended\nData Fig. 3A, are the scale bars accurate? The TOP2A puncta appear to be around 5 µm\nin size, which seems too large.\nWe apologize for the inaccuracy. We realize that our microscope puncta average images\nwere labeled incorrectly. We have now corrected the scale bars to be 200 nm for Fig. 1c,\nFig. 2i and Extended Data Fig. 3c, and double-checked all other scale bars.\n16) Extended Data Fig. 6g. This figure indicates that the cell population with low EU\nincreased after MYC depletion. This appears to conflict with the authors’ interpretation\n(Line 396).\nWe observe only a non-significant change in the cell population with low EU levels\nfollowing MYC depletion. However, since all Reviewers expressed concerns regarding\nthe EU assay, we have re-evaluated transcriptional activity using an orthogonal genomic-\nbased approach. Specifically, we quantified nascent transcription by SLAM-seq, a method\nbased on metabolic labeling of newly synthesized RNA2. The results show that\ntranscriptomic profiles are essentially unchanged upon 90min of auxin-induced MYC\ndegradation, nor MYC depletion altered the transcription levels of the top 1500\ntranscribed genes, indicating that the changes in TOP2A activity are attributable to the\ndirect effect of MYC on TOP2A dynamics (Fig. 5h and Extended Data Fig. 6g,h).\nMinor points:\n17) Fig. 1A. This panel is confusing. DAPI staining is needed to visualize the nuclear\nstructure.\nWe agree with the reviewer that including DAPI staining would be optimal to visualize the\nnuclear structure. Due to a technical consideration—to avoid DAPI signal bleed-through\nto other channels—we chose to omit it. This limitation is now explicitly mentioned in the\nMethods section.\n18) Line 95. It is known that RNAPI transcription inhibitors alter the nucleolar structure\n(nucleolar cap formation).\nThe Reviewer is correct that RNAPI transcription inhibitors can alter nucleolar structure\nand induce nucleolar cap formation. However, under our treatment conditions and time\npoints, we did not observe such pronounced changes in fibrillarin staining, a well-\n12\nestablished marker of nucleolar organization. We have rephrased the corresponding text\nin the manuscript to clarify this point as follows: “under our experimental conditions”.\n19) Which MYC subtype did the authors use? Please specify in the Methods section.\nWe apologize for the inaccuracy. It is the c-MYC isoform. We have included this\ninformation in the text.\n20) Line 222. Structured illumination light sheet microscopy (SIM)?\nThanks for requesting clarification. We have updated the text to describe the precise\nmethod used—multifocus SIM (mSIM)—and referenced the appropriate paper.\n21) Code availability: The provided codes (https://github.com/don-cameron/Cameron-et-\nal.-2025/tree/main) have empty “readme.md” files for pixel correlation plotting and for the\ngeneral instructions for the entire dataset!\nWe thank the reviewer for pointing this out to us. We have updated the readme files on\nGithub to provide a short explanation of the code.\nReviewer #3 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports.\nThis is part of the Nature Communications initiative to facilitate training in peer review and\nto provide appropriate recognition for Early Career Researchers who co-review\nmanuscripts.\nReviewer #3 (Remarks on code availability):\nI co-reviewed the code with one of the reviewers who provided the listed reports.\nReviewer #4 (Remarks to the Author):\nThis is very interesting and strong work built on the previous finding from some co-authors\nas well as an existing literature. It provides a step forward in the understanding of MYC\nfunction which is a big and important question in Mutiple fields. Study used an impressive\nset of biophysical, biochemical and cell-based methods.\nBelow is my review:\nThe manuscript of Cameron an co-authors uncover one of the mechanisms of how MYC\nboosts transcription. They provided data that TOP2A exists in cells in a balanced\ndistribution between nucleolar and nucleoplasm. In nucleoplasm, TOP2A is distributed\nbetween different states depending on its diffusion coefficients: a bound fraction\ninteracting or catalytically engaged with chromatin, a slow fraction enriched in\ntranscription condensates, and a fast fraction diffusing through the nucleoplasm. They\n13\nthen showed that degradation of MYC reduced TOP2A diffusion rates in slow and fast\nfractions. They showed that MYC promotes TOP2A mobility via reducing the size of\nTOP2A droplets in cell free conditions and TOP2A complexes in cells. This allows faster\nsearch of targets by TOP2A and more efficient resolution of supercoiling needed for\ntranscription.\nThis is very strong and rigor study using multiple experimental approaches, as well as\naccurately and clearly written. I just have several questions/comments, which I hope\nauthors can clarify.\nWe sincerely thank the reviewer for the encouraging and positive assessment of our work.\nWe also appreciate the recognition of the technical challenges and the significance of our\nfindings. Many of the reviewer’s comments focus on clarifying aspects of the presented\nresults, and we are grateful for the opportunity to address these points and further\nstrengthen the manuscript.\n22) Lines 78-79: “was lost along with nucleolar protein fibrillarin upon further treatment\nwith RNase A (Fig. 1b and Extended Data Fig. 1d), suggesting its association with\nnucleolar structures was maintained by ribosomal RNA” . Was the mechanism of TOP2A\nassociation with rRNA already known? Please provide refs or explain.\nThank you for the opportunity to clarify this point. To our current knowledge, there are no\nreports of TOP2A specifically binding to ribosomal RNA. However, proteome screening\nhas shown human TOP2A binding to mRNA14,15 which may suggest a general RNA-\nbinding property of TOP2A. As we mention in the discussion, the rat TOP2A CTD contains\na region that is essential for nucleolar localization and also confers sensitivity to RNA-\nmediated inhibition of TOP2A activity16, though this has not yet been validated with human\nTOP2A. Nevertheless, this suggests that high levels of RNA can repress TOP2A activity,\nwhich agrees with our general hypothesis that the RNA-rich nucleolus can sequester\nTOP2A.\nSince investigation of the mechanism behind TOP2A’s association with the rRNA was\nsomewhat outside the scope of the manuscript, we kept speculation about the role of\nribosomal RNA on TOP2A activity and sequestration to the discussion. However, in light\nof the Reviewer's question, we have included a sentence mentioning this research in the\nrelevant Results section.\n23) Contradictory impression between image Fig 1B vs quantitation Fig. S1D. Control\nimage shows signal from nucleolus and nucleoplasm, CSK image – only nucleolar signal,\nRNAse image – only nucleoplasm. Quantitation shows that control = RNAse.\nPlease explain.\nthe Nucleolar:Nucleoplasmic TOP2A ratio is not feasible in the CSK+RNAse condition\nbecause this treatment removes fibrillarin, which we use to define the nucleolar\ncompartment. As a result, the apparent agreement between Nucleolar:Nucleoplasmic\nTOP2A ratio in the control and RNase conditions in the previous quantification (old\nExtended Data Fig. 1d) was an artifact of this limitation. To avoid misinterpretation, we\nhave removed the full graph and replaced it with representative images from the four\nbiological replicates (Fig. 1b and Extended Data Fig. 1b)\n24) Figure 1E and F and all other plots of the same type show very few dots while more\naround thousand cells were measured and mentioned in the legend. What do dots\nrepresent?\nWe thank the reviewer for giving us the opportunity to clarify this point. The plot shows\nthe average of independent replicates, with each experiment representing the mean of\napproximately 1,000 cells. We have added this information to the figure legend.\n25) Lines 123 – 125: “ We observed an increase in DNA damage only after TOP1\ndegradation by auxin and etoposide treatment” and Fig.1F, ext Fig,2A and B. It is unclear\nwhy the gammaH2AX signal increased only after TOP1 degradation. Etoposide\ninteractions with TOP2A should be independent on TOP1.\nWe thank the reviewer for giving us the opportunity to clarify this point. Because\ntopoisomerases can partially compensate for each other’s function, degradation or\ninhibition of one enzyme (in this case, TOP1) is expected to trigger a compensatory\nincrease in DNA supercoiling. This, in turn, promotes enhanced engagement of TOP2A\non DNA to relieve the accumulated torsional stress. Such compensatory behavior has\nbeen previously documented by others17. In our experimental setup, we selectively\ndegrade TOP1 and apply a low dose of etoposide. The observed increase in γH2AX\nsignal—used here as a proxy for TOP2A activity—occurs only upon combined auxin and\netoposide treatment. This suggests that the elevated supercoiling resulting from TOP1\nloss is resolved by TOP2A, leading to its increased activity and consequent DNA damage\nsignaling. We have clarified this point better in the text.\n26) Also based on presented images – without TOP1 degradation, it is decreased in\nresponse to etoposide treatment in ext fig 2A, and increased in ext fig 2b.\nWe believe the reviewer is referring to the comparison between Extended Data Fig. 2c\nand Extended Data Fig. 2d, where γH2AX staining is shown. We apologize for selecting\nthe wrong image. We have replaced the old Extended Data Fig. 2c (new Extended Data\nFig. 2e) with a more representative example that accurately reflects the underlying data.\nPlease note that a low dose of etoposide was intentionally used in these experiments, as\nit is not expected to induce detectable DNA damage under normal DNA topology\n15\nconditions. Accordingly, the differences observed between CTRL, CTRL + Eto, and auxin\ntreatments are not statistically significant and represent background γH2AX signal levels.\n27) Lines 151-153: “Notably, TOP2B distribution across the nucleus was much more\nhomogeneous as compared to TOP2A, although ICRF-193 also caused a slight re-\nlocalization nucleolus-to-nucleoplasm (Extended Data Fig. 2f,g) suggesting it may also\nbe responsive to similar stimuli to TOP2A, although the TOP2A response was more\npronounced.” Is there enough structural difference between two tomoisomerases to\nexplain why this mechanism is much more pronounced in TOP2A vs TOP2B. It may be\ngood to discuss.\nThis is an excellent point. Like the reviewer, we are intrigued by the distinct behavior of\nTOP2B compared with TOP2A. Please note that TOP2B forms a different topoisome\n(including MYCN and TOP1) as compared to TOP2A (including c-MYC and TOP1)3.\nAlthough TOP2A and TOP2B share 77% of overall homology18, this is largely confined to\nthe N-terminal three quarters of the proteins, which contains the catalytic core. In contrast,\ntheir intrinsically disordered C-terminal domains (CTDs) show only ~46% sequence\nconservation. The CTDs are known to contribute substantially to functional divergence\nbetween the two enzymes. For instance, CTDs of TOP2A and TOP2B differently affect\ntheir interaction with DNA, catalytic activity19, their ability to phase separate20, accumulate\nwithin the nucleus, and bind RNA21. Thus, it is reasonable to speculate that the molecular\ndifferences between the CTDs, including their distinct distributions of charged amino\nacids and isoelectric points20, may underlie the more pronounced nucleolar-to-\nnucleoplasmic redistribution observed for TOP2A compared with TOP2B. Further\nexperiments in which the CTDs of TOP2A and TOP2B are swapped may be required to\ndirectly test this hypothesis. We have included this point in the Discussion.\n28) Line 163 “we found that nuclear TOP2A diffusion could be categorized into three\ndistinct populations.” It would be good to show the actual distribution of diffusion\ncoefficients, like histogram or in some other way.\nWe thank the reviewer for this helpful suggestion. Following this comment, we applied the\nSASPT algorithm (see Methods section for details) to extract and visualize the full\nspectrum of diffusion coefficients from the SMT data. The results are consistent with our\nprevious analysis (old Fig. 2b), highlighting a broad distribution of diffusion coefficients,\nwith three peaks, corresponding to bound (~0.01 µm2/s), slow diffusing (~ 0.1 µm2/s) and\nfast diffusing molecules (~1 µm2/s) and confirming that upon ICRF the fraction of fast-\ndiffusing TOP2A molecules is largely reduced, and that slow-diffusing molecules are\nfurther slowed down. The new data are now included in the revised manuscript (new Fig.\n2b).\n16\n29) Figure 2G is unclear. Should it contain colored lines according to the colors of FAST\nand SLOW? What exactly is the black line?\nWe thank the reviewer for the opportunity to clarify this point. The black line represents\nthe combined anisotropy values of both the fast and slow fractions. We considered adding\ncolored lines to distinguish the two populations; however, this made the graph visually\ncluttered. Therefore, we opted to indicate “Combined FAST and SLOW” anisotropy values\nat the top of the panel and in the figure legend for clarity.\n30) Line 198: “If the slow TOP2A fraction reflects TOP2A localized in transcription\ncondensates and the bound fraction corresponds to TOP2A interacting with chromatin,”\nShould not the slow and bound overlap, since bound should perform its activity within\ntranscriptional condensates.\nThis is a reasonable comment and below we have highlighted our rationale supporting\nthe idea that slow and bound represent two functionally separate populations of TOP2A\nmolecules.\nOur interpretation builds on the pioneering work of the Cissé group showing that\ntranscription condensates only transiently associate with gene loci6. In fact, transcriptional\nburst size and frequency are enhanced when the condensate approaches within ~1 μm\nof the target gene. The authors therefore propose a “three-way kissing” model whereby\nthe condensate interacts transiently with gene locus and regulatory DNA elements to\ncontrol gene bursting.\nAdditionally, we would like to clarify that the slow and bound fractions are derived from\nthe vbSPT algorithm that classifies single-molecule tracks based on their diffusion\ncoefficients. By definition, these states are non-overlapping, each molecule at any given\ntime point is assigned to a specific state. Moreover, given the state-transitions analysis\n(see arrows in Fig. 2c), it is notable that slow-to-bound transitions are substantially more\nfrequent than fast-bound transitions, suggesting the TOP2A molecules must pass through\nthe slow state before becoming chromatin-bound.\nThis observation prompted us to test whether slow and bound fractions have higher\nlikelihood to be found close to each other compared to fast and bound fractions. To probe\nspatial proximity between bound and diffusing molecules, we performed a spatial “cross-\ncorrelation” analysis, as previously done in22. Consistent with our hypothesis, slow\ndiffusing molecules were more likely to be found in proximity of bound molecules than\nfast diffusing ones. The scale of the observed decay is around 250nm, i.e. it is likely to\nfind slow molecules within 250 nm from bound ones. Treatment with 1,6-hexanediol HD,\nwhich disrupts Mediator-containing transcriptional condensates (Extended Data Fig. 1d),\nreduced the cross-correlation between slow-diffusing and bound TOP2A molecules, with\n17\na two-folds reduction relative to the control, indicative of decreased proximity. We have\nincluded this analysis in Extended Data Fig 3a-c.\nTogether, these observations suggest that the slow fraction represents TOP2A molecules\ntransiently engaging in the vicinity of chromatin, prior to stable binding, analogous to the\ndynamic approach of transcriptional condensates toward active gene loci.\n31) “transcribed chromatin labelled with H3.3” – H3.3 is not a very specific mark of\ntranscription, since although in general it is enriched in transcribed regions, these\ntranscribed regions are not transcribed all the time, taking into account transcription\nbursts, and transcription of many genes in a time-dependent manner (e.g., cell cycle).\nMore accurate marks of the presence of transcription can be used, like EU incorporation.\nWe completely agree with the Reviewer that directly visualizing transcribed DNA loci by\nlabelling newly transcribed RNA with EU would be ideal. However, while optimizing and\nperforming this assay, we identified multiple technical issues with this approach which we\nfeel makes it unsuitable for inclusion in the manuscript.\nSpecifically, we performed STED microscopy of HCT116 cells treated with ICRF and ActD\nas described before, but this time including a pulse with EU for 10, 30 and 60 minutes\nbefore harvesting. We fluorescently labelled the EU by click chemistry, and stained for\nTOP2A (Rebuttal Figure 3).\nICRF-193 treatment for the indicated time. 1389-3671 puncta per condition. Right, Average EU enrichment\nat TOP2A puncta across two independent experiments (EU pulse for 10 minutes).\nFrom these data, we observe that the EU signal only co-localized with TOP2A puncta\nafter 10 minutes, but not 30 minutes. After 60 minutes, the signal is in fact anti-correlated,\nsuggesting that at longer timepoints, EU signal that was initially associated with\ntranscribed loci is processed away from the site of transcription, quickly overwhelming the\ntranscription-associated signal. This suggests that only the 10 minutes treatment would\nbe suitable for labelling transcribed DNA loci.\nEncouragingly, the 10 minutes results were in agreement with our H3.3 data, where\nTOP2A increases after ICRF treatment, but not after ActD treatment. However, due to the\nextremely low level of labelled EU after only a 10 minute pulse, the resulting signal is very\nweak and less robust than the H3.3 data. Furthermore, because the EU signal is so faint,\nTOP2A puncta. In contrast, the H3.3 staining in the original manuscript produced a clear\nsignal, enabling us to measure TOP2A signal at H3.3 puncta, arguably the more relevant\nmeasurement to make.\nFor these reasons, we have decided not to include these EU results in the manuscript.\nHowever, in light of the reviewer’s concern, we have reworded the description of H3.3-\nassociated chromatin from “transcribed” to “open” to avoid confusion. We hope that this\nchange satisfactorily addresses the Reviewer’s comment.\n32) Line 242: “we found that although the proportion of TOP2A found in the fast,\nslow,\nand bound fractions were largely unchanged”… do you mean the amount or just the ratio\nbetween fractions? Then, was the amount changed?\nWe apologize for being unclear. This line refers to Fig. 3b where there are no significant\ndifferences between the CTRL and Auxin conditions with respect to the proportion of\ntracks classified either as fast, slow or bound. In this instance, the raw amount of tracks\nis not informative as this is entirely dependent on how many fluorophores are activated\nduring SMT imaging, and not at all to do with any biological differences between the two\nconditions. To clarify this point, we have changed the wording in the updated manuscript.\n33) “MYC mutant containing only residues 200-320 (MYC200-320)” why this form of myc\nis important? It was mentioned later that it does not bind TOP2A, but it should be better\nto explain at the first instance.\nWe thank the reviewer for the opportunity to clarify this point. We used the MYC200-320 as\nnegative control in the droplet assay, as we have previously shown that this mutant is\nunable to interact with TOP2A in co-IP experiments3. We have clarified this point in the\ntext.\n34) Fig.4H “average of six experiments”: what four data points represent?\nThanks for pointing this out to us. We apologize for the inaccuracy. It should be “average\nof four experiments”. We have corrected the typos.\n35) Why did they use K562 MYC-AID cells in just one section of the manuscript if they\nalready made HCT116 MYC-AID cells?\nWe thank the reviewer for the opportunity to clarify this point. We chose to work with the\nK562-MYC degron cells for the gradient experiment because its growth in suspension\nallows for more rapid and homogeneous cell lysis, besides enabling a more accurate\nestimation of cell number, a critical factor for the reproducibility of this assay. Moreover,\nusing multiple cell lines ensures that our findings are not cell line–specific, thereby\nstrengthening the generality of the observed trend.\n20\n36) Fig. 5A: Was the exposure for the control and auxin the same? It looks like the amount\nof TOP2A in the auxin condition has been increased. Some of the replicates in the\nextended data provide a better illustration of the author’s interpretation.\nYes, the exposure settings for the control and auxin-treated samples are identical. To\nimprove clarity, we have now moved all western blots from the gradient experiment to\nExtended Data Fig. 6, grouping them together so that the results can be more easily\ncompared across conditions and replicates.\n37) Crossover experiment: what was visualized and quantified? Individual TOP2A\nmolecules or droplets.\nWe thank the Reviewer for raising this point. To determine whether a single dimer or\nmultiple molecules are binding the DNA crossover, we would need to bleach the droplets\nand count the number of bleaching steps. However, in this instance it is not possible\nbecause TOP2A is continually associating and dissociating from the DNA crossover (see\ntrace in Fig. 5d). There is also high background signal due to free, fluorescently labeled\nTOP2A in the solute making it difficult to distinguish individual binding events.\nNonetheless, we expect that the majority of the binding events are TOP2A droplets given\nthe variance in peak intensity of TOP2A signal at the crossover (Fig. 5d). This is also\nsupported by our new data in Extended Data Fig. 5d (described also in comment 6 of\nthis Response Letter), where we can see droplets of multiple TOP2A molecules existing\nat similar TOP2A concentrations in the absence of DNA. We have edited the text for\nclarity.\n38) Fig. 5H: Does degradation of MYC lead to reduced transcription? Total EU\nincorporation was not reduced, but expression is a minor fraction of total transcription.\nHow about these 1500 genes?\nThis point was raised by all the reviewers; therefore we quantified nascent transcripts\nlevels across the genome using SLAM-seq after 90 minutes of auxin-induced MYC\ndegradation. This short-term depletion had essentially no effects on the transcriptional\noutput of the cells (Extended Data Fig. 6 g,h), either globally or among the top 1500\nmost expressed genes (Fig. 5h). These findings further strengthen the interpretation that\nthe changes in TOP2A activity result from direct regulation by MYC rather than secondary\ntranscriptional effects (Fig. 5g).\n39) Line 461-463: “TOP2A molecules decrease by approximately 10%-15%. According\nto the Stokes-Einstein relationship, in first approximation, diffusion coefficients would\nscale as the cubic root of the diffusing complex, thus corresponding to roughly 30% to\n50% larger complexes upon MYC degradation”. Math here is unclear. Cubic root of 30\nand 50 are around 3 and 3.6 and not 10-15.\nclear. The relative fold change of TOP2A diffusion coefficients observed upon MYC\ndegradation is:\n𝐷𝑛𝑜𝑀𝑌𝐶\n= 0.85-0.9\n𝐷𝑀𝑌𝐶\nAccording to the Stokes-Einstein relationship, the diffusion coefficient scales as the\ninverse of the molecule hydrodynamic radius, 𝑟. For globular proteins, the radius is, in\nfirst approximation, proportional to the cubic root of the molecular weight 𝑀. Thus:\n𝑀𝑛𝑜𝑀𝑌𝐶\n≈ ( 𝑟𝑛𝑜𝑀𝑌𝐶) 3\n= ( 𝐷𝑀𝑌𝐶\n) 3\n= 1.37x to 1.62x\n𝑀𝑀𝑌𝐶 𝑟𝑀𝑌𝐶 𝐷𝑛𝑜𝑀𝑌𝐶\nIn other words, TOP2A complexes upon MYC degradation should roughly be 30-50%\nlarger.\nReferences\n1. Cho, W.-K. et al. Mediator and RNA polymerase II clusters associate in transcription-\ndependent condensates. Science 361, 412–415 (2018).\n2. Muhar, M. et al. SLAM-seq defines direct gene-regulatory functions of the BRD4-\nMYC axis. Science (New York, N.Y.) 360, 800–805 (2018).\n3. Das, S. K. et al. MYC assembles and stimulates topoisomerases 1 and 2 in a\n“topoisome.” Mol Cell 82, 140-158.e12 (2022).\n4. Pommier, Y. Topoisomerase I inhibitors: camptothecins and beyond. Nature reviews.\nCancer 6, 789–802 (2006).\n5. Wiegard, A. et al. Topoisomerase 1 activity during mitotic transcription favors the\ntransition from mitosis to G1. Mol. Cell 81, 5007-5024.e9 (2021).\n6. Du, M. et al. Direct observation of a condensate effect on super-enhancer controlled\ngene bursting. Cell 187, 331-344.e17 (2024).\n7. Titov, D. V. et al. XPB, a subunit of TFIIH, is a target of the natural product triptolide.\nNat. Chem. Biol. 7, 182–188 (2011).\n8. Chen, F., Gao, X. & Shilatifard, A. Stably paused genes revealed through inhibition of\ntranscription initiation by the TFIIH inhibitor triptolide. Genes Dev. 29, 39–47 (2015).\n9. Hein, M. Y. et al. A Human Interactome in Three Quantitative Dimensions Organized\nby Stoichiometries and Abundances. Cell 163, 712–723 (2015).\n10. Wiśniewski, J. R., Koepsell, H., Gizak, A. & Rakus, D. Absolute protein\nquantification allows differentiation of cell-specific metabolic routes and functions.\nPROTEOMICS 15, 1316–1325 (2015).\n11. Padget, K., Pearson, A. & Austin, C. Quantitation of DNA topoisomerase IIα and β in\nhuman leukaemia cells by immunoblotting. Leukemia 14, 1997–2005 (2000).\n22\n12. Roukos, V., Pegoraro, G., Voss, T. C. & Misteli, T. Cell cycle staging of individual\ncells by fluorescence microscopy. Nature protocols 10, 334–348 (2015).\n13. Muñoz-Gil, G. et al. Stochastic particle unbinding modulates growth dynamics and\nsize of transcription factor condensates in living cells. Proc. Natl. Acad. Sci. 119,\ne2200667119 (2022).\n14. Baltz, A. G. et al. The mRNA-Bound Proteome and Its Global Occupancy Profile on\nProtein-Coding Transcripts. Mol. Cell 46, 674–690 (2012).\n15. Castello, A. et al. Insights into RNA Biology from an Atlas of Mammalian mRNA-\nBinding Proteins. Cell 149, 1393–1406 (2012).\n16. Yasuda, K., Kato, Y., Ikeda, S. & Kawano, S. Regulation of catalytic activity and\nnucleolar localization of rat DNA topoisomerase IIα through its C-terminal domain.\nGenes Genet Syst 95, 291–302 (2020).\n17. Miao, Z.-H. et al. Nonclassic Functions of Human Topoisomerase I: Genome-Wide\nand Pharmacologic Analyses. Cancer Res. 67, 8752–8761 (2007).\n18. Austin, C. A., Sng, J.-H., Patel, S. & Fisher, L. M. Novel HeLa topoisomerase II is\nthe IIβ isoform: complete coding sequence and homology with other type II\ntopoisomerases. Biochim. Biophys. Acta (BBA) - Gene Struct. Expr. 1172, 283–291\n(1993).\n19. Broeck, A. V. et al. Structural basis for allosteric regulation of Human\nTopoisomerase IIα. Nat Commun 12, 2962 (2021).\n20. Jeong, J., Lee, J. H., Carcamo, C. C., Parker, M. W. & Berger, J. M. DNA-\nStimulated Liquid-Liquid phase separation by eukaryotic topoisomerase ii modulates\ncatalytic function. Elife 11, e81786 (2022).\n21. Onoda, A. et al. Nuclear dynamics of topoisomerase IIβ reflects its catalytic activity\nthat is regulated by binding of RNA to the C-terminal domain. Nucleic acids research 42,\n9005–9020 (2014).\n22. Mazzocca, M. et al. Chromatin organization drives the search mechanism of nuclear\nfactors. Nat. Commun. 14, 6433 (2023).\nLaura Baranello\nLaura.baranello@ki.se\nLeia Judge, PhD\nSenior Editor\nNature Communications\nDear Dr. Judge,\nThank you very much for your guidance throughout the review and editorial process.\nYour clear direction has been invaluable in helping us improve the manuscript, which\nwe believe will be of broad interest to the biomedical research community.\nWe are pleased that reviewers 1 and 4 expressed appreciation for our revised\nmanuscript and found it to be appropriate for publication in Nature Communications.\nWe have carefully addressed the remaining concerns of reviewer 2 as outlined below:\n1. Extended Data Fig. 3a–c: I wondered whether these data include the slow and\nbound particles localized in nucleoli, since most of the slow/bound particles\nwere located in nucleoli, which are not linked to transcriptional condensates.\nWe thank the reviewer for pointing this out. The cross-correlation analysis\nwas performed exclusively on the nucleoplasmic fast and slow fractions\nof TOP2A. We have now explicitly clarified this in the figure legend.\n2. Fig. 2a: Representative movies of the single-particle tracking data should be\npresented to aid the readers’ understanding.\nWe thank the reviewer for this suggestion. We have now included two\nrepresentative movies of the SMT data (Supplementary video 1 and 2)."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have done a scholarly job responding to all of the reviews. I have no further criticisms or suggestions.", "reviewer_2": "The authors have addressed most of my comments, and the revised manuscript has been considerably improved. There are a few remaining issues that should be addressed. After that, the paper will be ready for publication in Nature Communications.\n1. Extended Data Fig. 3a–c: I wondered whether these data include the slow and bound particles localized in nucleoli, since most of the slow/bound particles were located in nucleoli, which are not linked to transcriptional condensates.\n2. Fig. 2a: Representative movies of the single-particle tracking data should be presented to aid the readers’ understanding.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_4": "Authors addressed all my comments and questions and I do not have any further requests. I am very impressed with their additional work."}, "author_response": "Department of Cell and molecular biology\nLaura Baranello\nLaura.baranello@ki.se\nLeia Judge, PhD\nSenior Editor\nNature Communications\nDear Dr. Judge,\nThank you very much for your guidance throughout the review and editorial process.\nYour clear direction has been invaluable in helping us improve the manuscript, which\nwe believe will be of broad interest to the biomedical research community.\nWe are pleased that reviewers 1 and 4 expressed appreciation for our revised\nmanuscript and found it to be appropriate for publication in Nature Communications.\nWe have carefully addressed the remaining concerns of reviewer 2 as outlined below:\n1. Extended Data Fig. 3a–c: I wondered whether these data include the slow and\nbound particles localized in nucleoli, since most of the slow/bound particles\nwere located in nucleoli, which are not linked to transcriptional condensates.\nWe thank the reviewer for pointing this out. The cross-correlation analysis\nwas performed exclusively on the nucleoplasmic fast and slow fractions\nof TOP2A. We have now explicitly clarified this in the figure legend.\n2. Fig. 2a: Representative movies of the single-particle tracking data should be\npresented to aid the readers’ understanding.\nWe thank the reviewer for this suggestion. We have now included two\nrepresentative movies of the SMT data (Supplementary video 1 and 2)."}]

Decision letter