Potential roles of condensin in genome organization and beyond in fission yeast

Contributions of transcriptional noise to leukaemia evolution: KAT2A as a case-study

Transcriptional noise is proposed to participate in cell fate changes, but contributions to mammalian cell differentiation systems, including cancer, remain associative. Cancer evolution is driven by genetic variability, with modulatory or contributory participation of epigenetic variants. Accumulation of epigenetic variants enhances transcriptional noise, which can facilitate cancer cell fate transitions. Acute myeloid leukaemia (AML) is an aggressive cancer with strong epigenetic dependencies, characterized by blocked differentiation. It constitutes an attractive model to probe links between transcriptional noise and malignant cell fate regulation. Gcn5/KAT2A is a classical epigenetic transcriptional noise regulator. Its loss increases transcriptional noise and modifies cell fates in stem and AML cells. By reviewing the analysis of KAT2A-depleted pre-leukaemia and leukaemia models, I discuss that the net result of transcriptional noise is diversification of cell fates secondary to alternative transcriptional programmes. Cellular diversification can enable or hinder AML progression, respectively, by differentiation of cell types responsive to mutations, or by maladaptation of leukaemia stem cells. KAT2A-dependent noise-responsive genes participate in ribosome biogenesis and KAT2A loss destabilizes translational activity. I discuss putative contributions of perturbed translation to AML biology, and propose KAT2A loss as a model for mechanistic integration of transcriptional and translational control of noise and fate decisions. This article is part of a discussion meeting issue 'Causes and consequences of stochastic processes in development and disease'.

Viral remodeling of the 4D nucleome

The dynamic spatial organization of genomes across time, referred to as the four-dimensional nucleome (4DN), is a key component of gene regulation and biological fate. Viral infections can lead to a reconfiguration of viral and host genomes, impacting gene expression, replication, latency, and oncogenic transformation. This review provides a summary of recent research employing three-dimensional genomic methods such as Hi-C, 4C, ChIA-PET, and HiChIP in virology. We review how viruses induce changes in gene loop formation between regulatory elements, modify chromatin accessibility, and trigger shifts between A and B compartments in the host genome. We highlight the central role of cellular chromatin organizing factors, such as CTCF and cohesin, that reshape the 3D structure of both viral and cellular genomes. We consider how viral episomes, viral proteins, and viral integration sites can alter the host epigenome and how host cell type and conditions determine viral epigenomes. This review consolidates current knowledge of the diverse host-viral interactions that impact the 4DN.

Brewing COFFEE: A Sequence-Specific Coarse-Grained Energy Function for Simulations of DNA-Protein Complexes

DNA-protein interactions are pervasive in a number of biophysical processes ranging from transcription and gene expression to chromosome folding. To describe the structural and dynamic properties underlying these processes accurately, it is important to create transferable computational models. Toward this end, we introduce Coarse-grained Force Field for Energy Estimation, COFFEE, a robust framework for simulating DNA-protein complexes. To brew COFFEE, we integrated the energy function in the self-organized polymer model with side-chains for proteins and the three interaction site model for DNA in a modular fashion, without recalibrating any of the parameters in the original force-fields. A unique feature of COFFEE is that it describes sequence-specific DNA-protein interactions using a statistical potential (SP) derived from a data set of high-resolution crystal structures. The only parameter in COFFEE is the strength (λDNAPRO) of the DNA-protein contact potential. For an optimal choice of λDNAPRO, the crystallographic B-factors for DNA-protein complexes with varying sizes and topologies are quantitatively reproduced. Without any further readjustments to the force-field parameters, COFFEE predicts scattering profiles that are in quantitative agreement with small-angle X-ray scattering experiments, as well as chemical shifts that are consistent with NMR. We also show that COFFEE accurately describes the salt-induced unraveling of nucleosomes. Strikingly, our nucleosome simulations explain the destabilization effect of ARG to LYS mutations, which do not alter the balance of electrostatic interactions but affect chemical interactions in subtle ways. The range of applications attests to the transferability of COFFEE, and we anticipate that it would be a promising framework for simulating DNA-protein complexes at the molecular length-scale.

Brewing COFFEE: A sequence-specific coarse-grained energy function for simulations of DNA-protein complexes

DNA-protein interactions are pervasive in a number of biophysical processes ranging from transcription, gene expression, to chromosome folding. To describe the structural and dynamic properties underlying these processes accurately, it is important to create transferable computational models. Toward this end, we introduce Coarse grained force field for energy estimation, COFFEE, a robust framework for simulating DNA-protein complexes. To brew COFFEE, we integrated the energy function in the Self-Organized Polymer model with Side Chains for proteins and the Three Interaction Site model for DNA in a modular fashion, without re-calibrating any of the parameters in the original force-fields. A unique feature of COFFEE is that it describes sequence-specific DNA-protein interactions using a statistical potential (SP) derived from a dataset of high-resolution crystal structures. The only parameter in COFFEE is the strength (λ D N A P R O ) of the DNA-protein contact potential. For an optimal choice of λ D N A P R O , the crystallographic B-factors for DNA-protein complexes, with varying sizes and topologies, are quantitatively reproduced. Without any further readjustments to the force-field parameters, COFFEE predicts the scattering profiles that are in quantitative agreement with SAXS experiments as well as chemical shifts that are consistent with NMR. We also show that COFFEE accurately describes the salt-induced unraveling of nucleosomes. Strikingly, our nucleosome simulations explain the destabilization effect of ARG to LYS mutations, which does not alter the balance of electrostatic interactions, but affects chemical interactions in subtle ways. The range of applications attests to the transferability of COFFEE, and we anticipate that it would be a promising framework for simulating DNA-protein complexes at the molecular length-scale.

BiFCo: visualizing cohesin assembly/disassembly cycle in living cells

Cohesin is a highly conserved, ring-shaped protein complex found in all eukaryotes. It consists of at least two structural maintenance of chromosomes (SMC) proteins, SMC1 and SMC3 in humans (Psm1 and Psm3 in fission yeast), and the kleisin RAD21 (Rad21 in fission yeast). Mutations in its components or regulators can lead to genetic syndromes, known as cohesinopathies, and various types of cancer. Studies in several organisms have shown that only a small fraction of each subunit assembles into complexes, making it difficult to investigate dynamic chromatin loading and unloading using fluorescent fusions in vivo because of excess soluble components. In this study, we introduce bimolecular fluorescent cohesin (BiFCo), based on bimolecular fluorescent complementation in the fission yeast Schizosaccharomyces pombe BiFCo selectively excludes signals from individual proteins, enabling the monitoring of complex assembly and disassembly within a physiological context throughout the entire cell cycle in living cells. This versatile system can be expanded and adapted for various genetic backgrounds and other eukaryotic models, including human cells.