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. 2022 Jul 13;13(1):4070.
doi: 10.1038/s41467-022-31856-6.

Loop-extrusion and polymer phase-separation can co-exist at the single-molecule level to shape chromatin folding

Mattia Conte #  1 , Ehsan Irani #  2   3 , Andrea M Chiariello #  1 , Alex Abraham  1 , Simona Bianco  2 , Andrea Esposito  1 , Mario Nicodemi  4   5   6
Affiliations

Loop-extrusion and polymer phase-separation can co-exist at the single-molecule level to shape chromatin folding

Mattia Conte et al. Nat Commun. .

Abstract

Loop-extrusion and phase-separation have been proposed as mechanisms that shape chromosome spatial organization. It is unclear, however, how they perform relative to each other in explaining chromatin architecture data and whether they compete or co-exist at the single-molecule level. Here, we compare models of polymer physics based on loop-extrusion and phase-separation, as well as models where both mechanisms act simultaneously in a single molecule, against multiplexed FISH data available in human loci in IMR90 and HCT116 cells. We find that the different models recapitulate bulk Hi-C and average multiplexed microscopy data. Single-molecule chromatin conformations are also well captured, especially by phase-separation based models that better reflect the experimentally reported segregation in globules of the considered genomic loci and their cell-to-cell structural variability. Such a variability is consistent with two main concurrent causes: single-cell epigenetic heterogeneity and an intrinsic thermodynamic conformational degeneracy of folding. Overall, the model combining loop-extrusion and polymer phase-separation provides a very good description of the data, particularly higher-order contacts, showing that the two mechanisms can co-exist in shaping chromatin architecture in single cells.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Scheme of the investigated polymer models.
We used Molecular Dynamics simulations to investigate polymer models where folding is based on two different physical processes: (i) DNA loop-extrusion and (ii) polymer phase-separation, recapitulated respectively by the LE, and by the SBS models,. a Microscopy median distance and ENCODE CTCF data are shown for the studied 2 Mb wide locus in human IMR90 cells. b We considered a simple Loop-Extrusion (LE) model where active motors extrude polymer loops until encountering another motor or CTCF anchor points with opposite orientation, which are fixed and equal in all single-molecule simulations (anchor probability = 1). c We also considered an extended version of the LE (eLE) whose anchor site locations are optimized, independently of CTCF, to best reproduce Hi-C and average microscopy data. To represent the epigenetic heterogeneity of single cells, those anchor sites have a finite probability to be present in a model single molecule. d In the Strings and Binders (SBS) model, a chromatin filament is represented as a self-avoiding chain of beads including different types of binding sites (colors) for diffusing cognate binders that can bridge those sites. The model undergoes a phase-separation of the chain in distinct globules. The binding site locations are determined by the PRISMR method and correlate with different combinations of chromatin architecture factors including, but not limited to, CTCF and cohesin,. e We also considered a polymer model (LE + SBS) where in a single molecule both the eLE and SBS mechanisms act simultaneously.
Fig. 2
Fig. 2. Both loop-extrusion and phase-separation based models recapitulate bulk Hi-C and average microscopy data.
a Microscopy median distance and b bulk Hi-C data are compared to the corresponding model results in the IMR90 locus. The different models have high genomic distance-corrected Pearson correlations (r', reported below their matrix) with the experiments. c The model derived average distances are reported for three specific pairs of sites: (i) separated by a strong TAD boundary (yellow pair); (ii) connected in loops within a TAD (green) and (iii) across a TAD boundary (red). d The average genomic boundary probability across single-molecules and e the separation score are also well recapitulated by the models (error bars indicate 95% confidence intervals). n = 1000 independent single-molecule conformations for each model. Source data are provided as a Source Data file.
Fig. 3
Fig. 3. Single-cell chromatin conformations are well captured by the model 3D structures, especially by phase-separation based ones.
a Microscopy single-cell chromatin structures of the IMR90 locus (left) are associated to their best matching single-molecule conformation in each model via the minimum RMSD criterion. Here two examples of best match are shown for each model type. b Less than 5% of the best-matching experiment-model pairs have an RMSD above the 1st decile of the control distribution. c The variability of microscopy single-molecule structures is measured by the distribution of r' correlations between pairs of distance matrices and is compared to the variability of in-silico structures. The r' distribution of the SBS model is statistically indistinguishable from the experimental one (two-sided Mann–Whitney test p-value = 0.362). The boxplots represent the median, interquartile ranges, whiskers within 1.5 times the interquartile range. n = 1000 independent single-molecule conformations for each model. Source data are provided as a Source Data file.
Fig. 4
Fig. 4. Triple contact data are well described by the models, especially by the eLE and the LE+SBS.
Triple contact probability maps are shown in microscopy data (left) and in the models from three different viewpoints a, b, c, more viewpoints in Supplementary Fig. 19. d The mean relative squared difference (MRSD) between imaging and model triplet contact maps is the lowest in the LE + SBS model, which is statistically equivalent to the eLE model (two-sided Welch’s t-test p = 0.097). The control is made of randomly folded self-avoiding polymer chains with same number of beads and size than the experimental structures. Error bars represent SEM. n = 1000 independent single-molecule conformations for each model. Source data are provided as a Source Data file.
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