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Bacterial chromosome segregation, ensuring equal distribution of replicated DNA, is crucial for cell division. During fast growth, replication and segregation co-occur. Overlapping cycles of DNA replication and segregation require efficient segregation of the origin of replication (Ori), which is known to be orchestrated by the protein families SMC and ParAB. We used data-driven physical modeling to study the roles of these proteins in Ori segregation. Developing a polymer model of the Bacillus subtilis genome based on Hi-C data, we analyzed chromosome structures in wild-type cells and mutants lacking SMC or ParAB. Wild-type chromosomes showed clear Ori segregation, while the mutants lacked faithful segregation. The model suggests that the dual role of ParB proteins, loading SMCs near the Ori and interacting with ParA, is crucial for Ori segregation. ParB-loaded SMCs compact individual Ori and introduce an effective inter-sister repulsion that regulates the ParAB-activity to avoid the detrimental scenario of pulling both Ori to the same pole. The model makes testable predictions for sister-chromosome-resolved Hi-C experiments and proposes that replicated sister chromosomes segregate via mechanistic cooperation of SMC and ParAB activity. 

We compute the free energy of confinement F for a wormlike chain (WLC), with persistence length lp, that is confined to the surface of a cylinder of radius R under an external tension f using a mean field variational approach. For long chains, we analytically determine the behavior of the chain in a variety of regimes, which are demarcated by the interplay of lp, the Odijk deflection length (ld = (R2lp)1/3), and the Pincus length (lf = kBT/f, with kBT being the thermal energy). The theory accurately reproduces the Odijk scaling for strongly confined chains at f = 0, with F ∼ Ll−1/3p R−2/3. For moderate values of f, the Odijk scaling is discernible only when lp   R for strongly confined chains. Confinement does not significantly alter the scaling of the mean extension for sufficiently high tension. The theory is used to estimate unwrapping forces for DNA from nucleosomes. 

The human estrogen receptor α (hER α ) is involved in the regulation of growth, development, and tissue homeostasis. Agonists that bind to the receptor’s ligand-binding domain (LBD) lead to recruitment of coactivators and the enhancement of gene expression. In contrast, antagonists bind to the LBD and block the binding of coactivators thus decreasing gene expressions. In this work, we carry out simulations using the AWSEM (Associative memory, Water mediated, Structure and Energy Model)-Suite force field along with the 3SPN.2C force field for DNA to predict the structure of hER α and study its dynamics when binding to DNA and coactivators. Using simulations of antagonist-bound hER α and agonist-bound hER α by themselves and also along with bound DNA and coactivators, principal component analyses and free energy landscape analyses capture the pathway of domain–domain communication for agonist-bound hER α . This communication is mediated through the hinge domains that are ordinarily intrinsically disordered. These disordered segments manipulate the hinge domains much like the strings of a marionette as they twist in different ways when antagonists or agonists are bound to the ligand-binding domain. 

A prion-like RNA-binding protein, CPEB3, can regulate local translation in dendritic spines. CPEB3 monomers repress translation, whereas CPEB3 aggregates activate translation of its target mRNAs. However, the CPEB3 aggregates, as long-lasting prions, may raise the problem of unregulated translational activation. Here, we propose a computational model of the complex structure between CPEB3 RNA-binding domain (CPEB3-RBD) and small ubiquitin-like modifier protein 2 (SUMO2). Free energy calculations suggest that the allosteric effect of CPEB3-RBD/SUMO2 interaction can amplify the RNA-binding affinity of CPEB3. Combining with previous experimental observations on the SUMOylation mode of CPEB3, this model suggests an equilibrium shift of mRNA from binding to deSUMOylated CPEB3 aggregates to binding to SUMOylated CPEB3 monomers in basal synapses. This work shows how a burst of local translation in synapses can be silenced following a stimulation pulse, and explores the CPEB3/SUMO2 interplay underlying the structural change of synapses and the formation of long-term memories. 

The growth of a tissue, which depends on cell–cell interactions and biologically relevant processes such as cell division and apoptosis, is regulated by a mechanical feedback mechanism. We account for these effects in a minimal two-dimensional model in order to investigate the consequences of mechanical feedback, which is controlled by a critical pressure, p c . A cell can only grow and divide if its pressure, due to interaction with its neighbors, is less than p c . Because temperature is not a relevant variable, the cell dynamics is driven by self-generated active forces (SGAFs) that arise due to cell division. We show that even in the absence of intercellular interactions, cells undergo diffusive behavior. The SGAF-driven diffusion is indistinguishable from the well-known dynamics of a free Brownian particle at a fixed finite temperature. When intercellular interactions are taken into account, we find persistent temporal correlations in the force–force autocorrelation function (FAF) that extends over a timescale of several cell division times. The time-dependence of the FAF reveals memory effects, which increases as p c increases. The observed non-Markovian effects emerge due to the interplay of cell division and mechanical feedback and are inherently a non-equilibrium phenomenon. 

Actin networks are essential for living cells to move, reproduce, and sense their environments. The dynamic and rheological behavior of actin networks is modulated by actin-binding proteins such as α-actinin, Arp2/3, and myosin. There is experimental evidence that actin-binding proteins modulate the cooperation of myosin motors by connecting the actin network. In this work, we present an analytical mean field model, using the Flory-Stockmayer theory of gelation, to understand how different actin-binding proteins change the connectivity of the actin filaments as the networks are formed. We follow the kinetics of the networks and estimate the concentrations of actin-binding proteins that are needed to reach connectivity percolation as well as to reach rigidity percolation. We find that Arp2/3 increases the actomyosin connectivity in the network in a non-monotonic way. We also describe how changing the connectivity of actomyosin networks modulates the ability of motors to exert forces, leading to three possible phases of the networks with distinctive dynamical characteristics: a sol phase, a gel phase, and an active phase. Thus, changes in the concentration and activity of actin-binding proteins in cells lead to a phase transition of the actin network, allowing the cells to perform active contraction and change their rheological properties.