Binding Specificity of ASHH2 CW Domain Toward H3K4me1 Ligand Is Coupled to Its Structural Stability Through Its α1-Helix

The CW domain binds to histone tail modifications found in different protein families involved in epigenetic regulation and chromatin remodeling. CW domains recognize the methylation state of the fourth lysine on histone 3 and could, therefore, be viewed as a reader of epigenetic information. The specificity toward different methylation states such as me1, me2, or me3 depends on the particular CW subtype. For example, the CW domain of ASHH2 methyltransferase binds preferentially to H3K4me1, and MORC3 binds to both H3K4me2 and me3 modifications, while ZCWPW1 is more specific to H3K4me3. The structural basis for these preferential bindings is not well understood, and recent research suggests that a more complete picture will emerge if dynamical and energetic assessments are included in the analysis of interactions. This study uses fold assessment by NMR in combination with mutagenesis, ITC affinity measurements, and thermal denaturation studies to investigate possible couplings between ASHH2 CW selectivity toward H3K4me1 and the stabilization of the domain and loops implicated in binding. The key elements of the binding site—the two tryptophans and the α1-helix form and maintain the binding pocket— were perturbed by mutagenesis and investigated. Results show that the α1-helix maintains the overall stability of the fold via the I915 and L919 residues and that the correct binding consolidates the loops designated as η1 and η3, as well as the C-terminal. This consolidation is incomplete for H3K4me3 binding to CW, which experiences a decrease in overall thermal stability on binding. Loop mutations not directly involved in the binding site, nonetheless, affect the equilibrium positions of the key residues.publishedVersio

Binding Specificity of ASHH2 CW Domain Toward H3K4me1 Ligand Is Coupled to Its Structural Stability Through Its α1-Helix

The CW domain binds to histone tail modifications found in different protein families involved in epigenetic regulation and chromatin remodeling. CW domains recognize the methylation state of the fourth lysine on histone 3 and could, therefore, be viewed as a reader of epigenetic information. The specificity toward different methylation states such as me1, me2, or me3 depends on the particular CW subtype. For example, the CW domain of ASHH2 methyltransferase binds preferentially to H3K4me1, and MORC3 binds to both H3K4me2 and me3 modifications, while ZCWPW1 is more specific to H3K4me3. The structural basis for these preferential bindings is not well understood, and recent research suggests that a more complete picture will emerge if dynamical and energetic assessments are included in the analysis of interactions. This study uses fold assessment by NMR in combination with mutagenesis, ITC affinity measurements, and thermal denaturation studies to investigate possible couplings between ASHH2 CW selectivity toward H3K4me1 and the stabilization of the domain and loops implicated in binding. The key elements of the binding site—the two tryptophans and the α1-helix form and maintain the binding pocket— were perturbed by mutagenesis and investigated. Results show that the α1-helix maintains the overall stability of the fold via the I915 and L919 residues and that the correct binding consolidates the loops designated as η1 and η3, as well as the C-terminal. This consolidation is incomplete for H3K4me3 binding to CW, which experiences a decrease in overall thermal stability on binding. Loop mutations not directly involved in the binding site, nonetheless, affect the equilibrium positions of the key residues

A quantitative map of human Condensins provides new insights into mitotic chromosome architecture

The two Condensin complexes in human cells are essential for mitotic chromosome structure. We used homozygous genome editing to fluorescently tag Condensin I and II subunits and mapped their absolute abundance, spacing, and dynamic localization during mitosis by fluorescence correlation spectroscopy (FSC)–calibrated live-cell imaging and superresolution microscopy. Although ∼35,000 Condensin II complexes are stably bound to chromosomes throughout mitosis, ∼195,000 Condensin I complexes dynamically bind in two steps: prometaphase and early anaphase. The two Condensins rarely colocalize at the chromatid axis, where Condensin II is centrally confined, but Condensin I reaches ∼50% of the chromatid diameter from its center. Based on our comprehensive quantitative data, we propose a three-step hierarchical loop model of mitotic chromosome compaction: Condensin II initially fixes loops of a maximum size of ∼450 kb at the chromatid axis, whose size is then reduced by Condensin I binding to ∼90 kb in prometaphase and ∼70 kb in anaphase, achieving maximum chromosome compaction upon sister chromatid segregation

ChromoTrace: Computational reconstruction of 3D chromosome configurations for super-resolution microscopy

<div><p>The 3D structure of chromatin plays a key role in genome function, including gene expression, DNA replication, chromosome segregation, and DNA repair. Furthermore the location of genomic loci within the nucleus, especially relative to each other and nuclear structures such as the nuclear envelope and nuclear bodies strongly correlates with aspects of function such as gene expression. Therefore, determining the 3D position of the 6 billion DNA base pairs in each of the 23 chromosomes inside the nucleus of a human cell is a central challenge of biology. Recent advances of super-resolution microscopy in principle enable the mapping of specific molecular features with nanometer precision inside cells. Combined with highly specific, sensitive and multiplexed fluorescence labeling of DNA sequences this opens up the possibility of mapping the 3D path of the genome sequence in situ. Here we develop computational methodologies to reconstruct the sequence configuration of all human chromosomes in the nucleus from a super-resolution image of a set of fluorescent in situ probes hybridized to the genome in a cell. To test our approach, we develop a method for the simulation of DNA in an idealized human nucleus. Our reconstruction method, ChromoTrace, uses suffix trees to assign a known linear ordering of in situ probes on the genome to an unknown set of 3D in-situ probe positions in the nucleus from super-resolved images using the known genomic probe spacing as a set of physical distance constraints between probes. We find that ChromoTrace can assign the 3D positions of the majority of loci with high accuracy and reasonable sensitivity to specific genome sequences. By simulating appropriate spatial resolution, label multiplexing and noise scenarios we assess our algorithms performance. Our study shows that it is feasible to achieve genome-wide reconstruction of the 3D DNA path based on super-resolution microscopy images.</p></div

Reconstruction performance for the main simulations.

<p>The reconstruction algorithms performance is shown in terms of the relationship between precision and recall given the number of colors in the probe design. (A) Recall against precision genome wide (triangles) and for chromosome 20 (circles). Precision is good for both genome and chromosome scale regions for all the different probe designs whereas recall is much more dependent on the number of available colors and improves as the number of colors is increased. (B) Total number of contacts in 100 kb windows against the area under the precision-recall curve given the number of colors in the probe design.</p

Suffix tree of the sequence <i>BGRY</i> <i>BGRY</i> <i>BGRY</i>.

<p>Every subsequence of the sequence is spelled out on edges from the root, at the top of the tree, to a leaf node, at the bottom of the tree.</p

Differences in simulation packing densities.

<p>Reconstruction performance when decreasing the packing density of the simulations. (A-B) For all positions across the simulations, the proportion of directly adjacent spaces that are occupied for the new (blue) and original (red) simulations respectively. The distribution is left shifted for the new simulations compared to the original and the median number of occupied spaces is reduced reflecting a decrease in density. (C) Genome wide performance of the reconstruction algorithm for the new (triangles) and original (circles) simulations in terms of precision and recall given the number of colors in the probe design.</p

Segmented simulated LE profiles.

<p>(A) The reconstruction performance, recall versus precision when running ChromoTrace for whole genome and individual chromosomes. (B) The percent of missing probes across all 100 simulations for all of the polymer chains and a single chain. (C) The percent of LE’s that were clustered into the wrong locus for the whole genome and chromosome 20. (D) the percent of clusters that contained LE’s from multiple starting loci.</p

Illustration of the ChromoTrace algorithm.

<p>(A) The 3D coordinates that would be obtained from super-resolution microscope imaging are converted into an distance graph. Given the pre-specified linear labeling sequence of green-red-blue-blue-green a trivial path is detected. Note that in the microscopy image the connection between points is unknown and only the colors remain. (B) Diagram of the extension algorithm exploring the ambiguous extension phase.</p

Robustness to missing and mislabeled probes.

<p>Relationship between amount of error for two different modes (missing and mislabeled probes) and the overall reconstruction performance given the number of colors in the probe design is displayed in panels A through D. The number of colors in the probe design is indicated using different shades of black-blue. Panels A and C show the proportion of error against precision for mislabeled and missing probe errors respectively and panels B and D show the proportion of error against recall.</p