The brain cells are affected by continuous fluid shear stress that is driven by varying hydrostatic and osmotic pressure conditions, depending on the brain's pathophysiological conditions. Although all brain cells are sensitive to the subtle changes in various physicochemical factors in the microenvironment, microglia, the resident brain immune cells, exhibit the most significant morphodynamic transformation. However, little is known about the phenotypic alterations in microglia in response to changes in fluid shear stress. In this study, we established a flow-controlled microenvironment to investigate the effects of shear flow on microglial phenotypes, including morphology, motility, and activation states. We observed two distinct morphologies of microglia in a static condition: bipolar cells that oscillate along their long axis and unipolar cells that migrate persistently. When exposed to flow, a significant fraction of bipolar cells showed unstable oscillation with an increased amplitude of oscillation and a decreased frequency, which consequently led to the phenotypic transformation of oscillating cells into migrating cells. Furthermore, we observed that the level of proinflammatory genes increased in response to shear stress, although there were no significant changes in the level of antiinflammatory genes. Our findings suggest that an interstitial fluid-level stimulus can cause a dramatic phenotypic shift in microglia toward proinflammatory states, shedding light on the pathological outbreaks of severe brain diseases. Given that the fluidic environment in the brain can be locally disrupted in pathological circumstances, the mechanical stimulus by fluid flow should also be considered a crucial element in regulating the immune activities of the microglia in brain diseases.

Fluorescent microscopy is the primary method to study DNA organization within cells. However, the variability and low signal/noise commonly associated with live-cell time-lapse imaging challenges quantitative measurements. In particular, obtaining quantitative or mechanistic insight often depends on the accurate tracking of fluorescent particles. Here, we present ★Track, an inference method that determines the most likely temporal tracking of replicating intracellular particles such DNA loci while accounting for missing, merged, and spurious detections. It allows the accurate prediction of particle copy numbers as well as the timing of replication events. We demonstrate ★Track's abilities and gain new insight into plasmid copy number control and the volume dependence of bacterial chromosome replication initiation. By enabling the accurate tracking of DNA loci, ★Track can help to uncover the mechanistic principles of chromosome organization and dynamics across a range of systems.

Segmenting cells within cellular aggregates in 3D is a growing challenge in cell biology due to improvements in capacity and accuracy of microscopy techniques. Here, we describe a pipeline to segment images of cell aggregates in 3D. The pipeline combines neural network segmentations with active meshes. We apply our segmentation method to cultured mouse mammary gland organoids imaged over 24 h with oblique plane microscopy, a high-throughput light-sheet fluorescence microscopy technique. We show that our method can also be applied to images of mouse embryonic stem cells imaged with a spinning disc microscope. We segment individual cells based on nuclei and cell membrane fluorescent markers, and track cells over time. We describe metrics to quantify the quality of the automated segmentation. Our segmentation pipeline involves a Fiji plugin that implements active mesh deformation and allows a user to create training data, automatically obtain segmentation meshes from original image data or neural network prediction, and manually curate segmentation data to identify and correct mistakes. Our active meshes-based approach facilitates segmentation postprocessing, correction, and integration with neural network prediction.

We develop a theory for inferring equilibrium transition rates from trajectories driven by a time-dependent force using results from stochastic thermodynamics. Applying the Kawasaki relation to approximate the nonequilibrium distribution function in terms of the equilibrium distribution function and the excess dissipation, we formulate a nonequilibrium transition state theory to estimate the rate enhancement over the equilibrium rate due to the nonequilibrium protocol. We demonstrate the utility of our theory in examples of pulling of harmonically trapped particles in one and two dimensions, as well as a semiflexible polymer with a reactive linker in three dimensions. We expect our purely thermodynamic approach will find use in both molecular simulation and force spectroscopy experiments.

Chromosomes endure mechanical stresses throughout the cell cycle; for example, resulting from the pulling of chromosomes by spindle fibers during mitosis or deformation of the nucleus during cell migration. The response to physical stress is closely related to chromosome structure and function. Micromechanical studies of mitotic chromosomes have revealed them to be remarkably extensible objects and informed early models of mitotic chromosome organization. We use a data-driven, coarse-grained polymer modeling approach to explore the relationship between the spatial organization of individual chromosomes and their emergent mechanical properties. In particular, we investigate the mechanical properties of our model chromosomes by axially stretching them. Simulated stretching led to a linear force-extension curve for small strain, with mitotic chromosomes behaving about 10-fold stiffer than interphase chromosomes. Studying their relaxation dynamics, we found that chromosomes are viscoelastic solids with a highly liquid-like, viscous behavior in interphase that becomes solid-like in mitosis. This emergent mechanical stiffness originates from lengthwise compaction, an effective potential capturing the activity of loop-extruding SMC complexes. Chromosomes denature under large strains via unraveling, which is characterized by opening of large-scale folding patterns. By quantifying the effect of mechanical perturbations on the chromosome's structural features, our model provides a nuanced understanding of in vivo mechanics of chromosomes.

Cells in living organisms are subjected to mechanical strains caused by external forces like overcrowding, resulting in strong deformations that affect cell function. We study the interplay between deformation and crowding of red blood cells (RBCs) in dispersions of nonabsorbing rod-like viruses. We identify a sequence of configurational transitions of RBC doublets, including configurations that can only be induced by long-ranged attraction: highly fluctuating T-shaped and face-to-face configurations at low, and doublets approaching a complete spherical configuration at high, rod concentrations. Complementary simulations are used to explore different energy contributions to deformation as well as the stability of RBC doublet configurations. Our advanced analysis of 3D reconstructed confocal images of RBC doublets quantifies the depletion interaction and the resulting deformation energy. Thus, we introduce a noninvasive, high-throughput platform that is generally applicable to investigate the mechanical response of biological cells to external forces and characterize their mechanical properties.

Clustering of weakly interacting multivalent biomolecules underlies the formation of membraneless compartments known as condensates. As opposed to single-component (homotypic) systems, the concentration dependence of multicomponent (heterotypic) condensate formation is not well understood. We previously proposed the solubility product (SP), the product of monomer concentrations in the dilute phase, as a tool for understanding the concentration dependence of multicomponent systems. In this study, we further explore the limits of the SP concept using spatial Langevin dynamics and rule-based stochastic simulations. We show, for a variety of idealized molecular structures, how the maximum SP coincides with the onset of the phase transition, i.e., the formation of large clusters. We reveal the importance of intracluster binding in steering the free and cluster phase molecular distributions. We also show how structural features of biomolecules shape the SP profiles. The interplay of flexibility, length, and steric hindrance of linker regions controls the phase transition threshold. Remarkably, when SPs are normalized to nondimensional variables and plotted against the concentration scaled to the threshold for phase transition, the curves all coincide independent of the structural features of the binding partners. Similar coincidence is observed for the normalized clustering versus concentration plots. Overall, the principles derived from these systematic models will help guide and interpret in vitro and in vivo experiments on the biophysics of biomolecular condensates.

The molecular association of proteins with nucleic acids leading to the formation of macromolecular complexes is a crucial step in several biological processes. Stabilization of these complexes involves electrostatic interactions between ion pairs (salt bridges) of nucleic acid phosphates and protein side chains. The crenarchaeal DNA binding protein, Cren7 plays a key role in the regulation of chromosomal structure and gene expression in eukaryotic extremophiles. However, the molecular contacts that occur at the interface of protein-DNA complexes and their contribution to the electrostatic interaction have not been fully elucidated. This work presents a quantitative description of the mechanism of the electrostatic interaction between the protein and DNA. We have identified a few residues located at the Cren7-DNA interface that could potentially be responsible for the interaction. Structural studies using circular dichroism indicate mutation of these surface residues minimally affect their structure and stability. The binding affinity of these mutants for the DNA duplexes was examined from reverse titration, biolayer interferometry, and fluorescence anisotropy measurements with calf thymus DNA, polynucleotides, and small DNA oligonucleotides. The resulting kinetic parameters highlight a difference in electrostatic interactions potentials exhibited by residues positioned at different locations of the protein-DNA interface. Computational studies attribute this difference to their surrounding atmosphere and energetic stabilization parameters. The biophysical approach described here can be extended for other proteins that play a crucial role in DNA bending and compaction, to properly evaluate the role of specific residues on the mechanisms of DNA binding.

Major histocompatibility complex class II (MHC-II) plays an indispensable role in activating CD4+ T cell immune responses by presenting antigenic peptides on the cell surface for recognition by T cell receptors. The assembly of MHC-II and antigenic peptide is therefore a prerequisite for the antigen presentation. To date, however, the atomic-level mechanism underlying the peptide-loading dynamics for MHC-II is still elusive. Here, by constructing Markov state models based on extensive all-atom molecular dynamics simulations, we reveal the complete peptide-loading dynamics into MHC-II for one SARS-CoV-2 S-protein-derived antigenic peptide (235ITRFQTLLALHRSYL249). Our Markov state model identifies six metastable states (S1-S6) during the peptide-loading process and determines two dominant loading pathways. The peptide could potentially approach the antigen-binding groove via either its N- or C-terminus. Then, the consecutive insertion of several anchor residues into the binding pockets profoundly dictates the peptide-loading dynamics. Notably, the MHC-II αA52-E55 motif could guide the peptide loading into the antigen-binding groove via forming β-sheets conformation with the incoming peptide. The rate-limiting step, namely S5→S6, is mainly attributed to a considerable desolvation penalty triggered by the binding of the peptide C-terminus. Moreover, we further examined the conformational changes associated with the peptide exchange process catalyzed by the chaperon protein HLA-DM. A flipped-out conformation of MHC-II αW43 captured in S1-S3 is considered a critical anchor point for HLA-DM to modulate the structural dynamics. Our work provides deep structural insights into the key regulatory factors in MHC-II responsible for peptide recognition and guides future design for peptide vaccines against SARS-CoV-2.

Switch-like motifs are among the basic building blocks of biochemical networks. A common motif that can serve as an ultrasensitive switch consists of two enzymes acting antagonistically on a substrate, one making and the other removing a covalent modification. To work as a switch, such covalent modification cycles must be held out of thermodynamic equilibrium by continuous expenditure of energy. Here, we exploit the linear framework for timescale separation to establish tight bounds on the performance of any covalent-modification switch in terms of the chemical potential difference driving the cycle. The bounds apply to arbitrary enzyme mechanisms, not just Michaelis-Menten, with arbitrary rate constants and thereby reflect fundamental physical constraints on covalent switching.

Studies of biological transport frequently neglect the explicit statistical correlations among particle site occupancies (i.e., they use a mean-field approximation). Neglecting correlations sometimes captures biological function, even for out-of-equilibrium and interacting systems. We show that neglecting correlations fails to describe free energy transduction, mistakenly predicting an abundance of slippage and energy dissipation, even for networks that are near reversible and lack interactions among particle sites. Interestingly, linear charge transport chains are well described without including correlations, even for networks that are driven and include site-site interactions typical of biological electron transfer chains. We examine three specific bioenergetic networks: a linear electron transfer chain (as found in bacterial nanowires), a near-reversible electron bifurcation network (as in complex III of respiration and other recently discovered structures), and a redox-coupled proton pump (as in complex IV of respiration).

Single-particle electron cryo-microscopy (cryo-EM) has become an effective and straightforward approach to determine the structure of membrane proteins. However, obtaining cryo-EM grids of sufficient quality for high-resolution structural analysis remains a major bottleneck. One of the difficulties arises from the presence of detergents, which often leads to a lack of control of the ice thickness. Amphipathic polymers such as amphipols (APols) are detergent substitutes, which have proven to be valuable tools for cryo-EM studies. In this work, we investigate the physico-chemical behavior of APol- and detergent-containing solutions and show a correlation with the properties of vitreous thin films in cryo-EM grids. This study provides new insight on the potential of APols, allowing a better control of ice thickness while limiting protein adsorption at the air-water interface, as shown with the full-length mouse serotonin 5-HT3A receptor whose structure has been solved in APol. These findings may speed up the process of grid optimization to obtain high-resolution structures of membrane proteins.

The first barrier that a small molecule must overcome before trespassing into a living cell is the lipid bilayer surrounding the intracellular content. It is imperative, therefore, to understand how the structure of a small molecule influences its fate in this region. Through the use of second harmonic generation, we show how the differing degrees of ionic headgroups, conjugated system, and branched hydrocarbon tail disparities of a series of four styryl dye molecules influence the propensity to "flip-flop" or to be further organized in the outer leaflet by the membrane. We show here that initial adsorption experiments match previous studies on model systems; however, more complex dynamics are observed over time. Aside from probe molecule structure, these dynamics also vary between cell species and can deviate from trends reported based on model membranes. Specifically, we show here that the membrane composition is an important factor to consider for headgroup-mediated small-molecule dynamics. Overall, the findings presented here on how structural variability of small molecules impacts their initial adsorption and eventual destinations within membranes in the context of living cells could have practical applications in antibiotic and drug adjuvant design.

In the present work, we describe Martini3 coarse-grained models of polystyrene and carboxyl-terminated polystyrene functionalized carbon nanotubes (CNTs) and investigate their interactions with lipid bilayers with and without cholesterol (CHOL) using molecular dynamics simulations. By changing the polystyrene chain length and grafting density at the end ring of the CNTs at two different nanotube concentrations, we observe the translocation of nanoparticles as well as changes in the lipid bilayer properties. Our results show that all developed models passively diffuse into the membranes without causing any damage to the membrane integrity, although high concentrations of CNTs induce structural and elastic changes in lipid bilayers. In the presence of CHOL, increasing CNT concentration results in decreased rates of CHOL transmembrane motions. On the other hand, CNTs are prone to lipid and polystyrene blockage, which affects their equilibrated configurations, and tilting behavior within the membranes. Hence, we demonstrate that polystyrene-functionalized CNTs are promising drug-carrier agents. However, polystyrene chain length and grafting density are important factors to consider to enhance the efficiency of drug delivery.

Active microrheology was conducted in living cells by applying an optical-trapping force to vigorously fluctuating tracer beads with feedback-tracking technology. The complex shear modulus G(ω)=G'(ω)-iG″(ω) was measured in HeLa cells in an epithelial-like confluent monolayer. We found that G(ω)∝(-iω)1/2 over a wide range of frequencies (1 Hz < ω/2π < 10 kHz). Actin disruption and cell-cycle progression from G1 to S and G2 phases only had a limited effect on G(ω) in living cells. On the other hand, G(ω) was found to be dependent on cell metabolism; ATP-depleted cells showed an increased elastic modulus G'(ω) at low frequencies, giving rise to a constant plateau such that G(ω)=G0+A(-iω)1/2. Both the plateau and the additional frequency dependency ∝(-iω)1/2 of ATP-depleted cells are consistent with a rheological response typical of colloidal jamming. On the other hand, the plateau G0 disappeared in ordinary metabolically active cells, implying that living cells fluidize their internal states such that they approach the critical jamming point.

Cell surface properties of microorganisms provide abundant information for their physiological status and fate choice. However, current methods for analyzing cell surface properties require labeling or fixation, which can alter the cell activity. This study establishes a label-free, rapid, noninvasive, and quantitative analysis of cell surface properties, including the presence and the dimension of epistructure, down to the single-cell level and at the nanometer scale. Simultaneously, electrorotation provides dielectric properties of intracellular contents. With the combined information, the growth phase of microalgae cells can be identified. The measurement is based on electrorotation of single cells, and an electrorotation model accounting for the surface properties is developed to properly interpret experimental data. The epistructure length measured by electrorotation is validated by scanning electron microscopy. The measurement accuracy is satisfactory in particular in the case of microscale epistructures in the exponential phase and nanoscale epistructures in the stationary phase. However, the measurement accuracy for nanoscale epistructures on cells in the exponential phase is offset by the effect of a thick double layer. Lastly, a diversity in epistructure length distinguishes exponential phase from stationary phase.

Pulmonary surfactant is a lipid-protein complex that forms a thin film at the air-water surface of the lungs. This surfactant film defines the elastic recoil and respiratory mechanics of the lungs. One generally accepted rationale of using oxygenated perfluorocarbon (PFC) as a respiratory medium in liquid ventilation is to take advantage of its low surface tensions (14-18 mN/m), which was believed to make PFC an ideal replacement of the exogenous surfactant. Compared with the extensive studies of the phospholipid phase behavior of the pulmonary surfactant film at the air-water surface, its phase behavior at the PFC-water interface is essentially unknown. Here, we reported the first detailed biophysical study of phospholipid phase transitions in two animal-derived natural pulmonary surfactant films, Infasurf and Survanta, at the PFC-water interface using constrained drop surfactometry. Constrained drop surfactometry allows in situ Langmuir-Blodgett transfer from the PFC-water interface, thus permitting direct visualization of lipid polymorphism in pulmonary surfactant films using atomic force microscopy. Our data suggested that regardless of its low surface tension, the PFC cannot be used as a replacement of pulmonary surfactant in liquid ventilation where the air-water surface of the lungs is replaced with the PFC-water interface that features an intrinsically high interfacial tension. The pulmonary surfactant film at the PFC-water interface undergoes continuous phase transitions at surface pressures less than the equilibrium spreading pressure of 50 mN/m and a monolayer-to-multilayer transition above this critical pressure. These results provided not only novel biophysical insight into the phase behavior of natural pulmonary surfactant at the oil-water interface but also translational implications into the further development of liquid ventilation and liquid breathing techniques.

Telomeres, complexes of DNA and proteins, protect ends of linear chromosomes. In humans, the two shelterin proteins TRF1 and TIN2, along with cohesin subunit SA1, were proposed to mediate telomere cohesion. Although the ability of the TRF1-TIN2 and TRF1-SA1 systems to compact telomeric DNA by DNA-DNA bridging has been reported, the function of the full ternary TRF1-TIN2-SA1 system has not been explored in detail. Here, we quantify the compaction of nanochannel-stretched DNA by the ternary system, as well as its constituents, and obtain estimates of the relative impact of its constituents and their interactions. We find that TRF1, TIN2, and SA1 work synergistically to cause a compaction of the DNA substrate, and that maximal compaction occurs if all three proteins are present. By altering the sequence with which DNA substrates are exposed to proteins, we establish that compaction by TRF1 and TIN2 can proceed through binding of TRF1 to DNA, followed by compaction as TIN2 recognizes the previously bound TRF1. We further establish that SA1 alone can also lead to a compaction, and that compaction in a combined system of all three proteins can be understood as an additive effect of TRF1-TIN2 and SA1-based compaction. Atomic force microscopy of intermolecular aggregation confirms that a combination of TRF1, TIN2, and SA1 together drive strong intermolecular aggregation as it would be required during chromosome cohesion.

The fusion of lipid membranes progresses through a series of hemifusion intermediates with two significant energy barriers related to the formation of stalk and fusion pore, respectively. These energy barriers determine the speed and success rate of many critical biological processes, including the fusion of highly curved membranes, for example synaptic vesicles and enveloped viruses. Here we use continuum elastic theory of lipid monolayers to determine the relationship between membrane shape and energy barriers to fusion. We find that the stalk formation energy decreases with curvature by up to 31 kBT in a 20-nm-radius vesicle compared with planar membranes and by up to 8 kBT in the fusion of highly curved, long, tubular membranes. In contrast, the fusion pore formation energy barrier shows a more complicated behavior. Immediately after stalk expansion to the hemifusion diaphragm, the fusion pore formation energy barrier is low (15-25 kBT) due to lipid stretching in the distal monolayers and increased tension in highly curved vesicles. Therefore, the opening of the fusion pore is faster. However, these stresses relax over time due to lipid flip-flop from the proximal monolayer, resulting in a larger hemifusion diaphragm and a higher fusion pore formation energy barrier, up to 35 kBT. Therefore, if the fusion pore fails to open before significant lipid flip-flop takes place, the reaction proceeds to an extended hemifusion diaphragm state, which is a dead-end configuration in the fusion process and can be used to prevent viral infections. In contrast, in the fusion of long tubular compartments, the surface tension does not accumulate due to the formation of the diaphragm, and the energy barrier for pore expansion increases with curvature by up to 11 kBT. This suggests that inhibition of polymorphic virus infection could particularly target this feature of the second barrier.

The ability to sense transmembrane voltage underlies most physiological roles of voltage-gated sodium (Nav) channels. Whereas the key role of their voltage-sensing domains (VSDs) in channel activation is well established, the molecular underpinnings of voltage coupling remain incompletely understood. Voltage-dependent energetics of the activation process can be described in terms of the gating charge that is defined by coupling of charged residues to the external electric field. The shape of the electric field within VSDs is therefore crucial for the activation of voltage-gated ion channels. Here, we employed molecular dynamics simulations of cardiac Nav1.5 and bacterial NavAb, together with our recently developed tool g_elpot, to gain insights into the voltage-sensing mechanisms of Nav channels via high-resolution quantification of VSD electrostatics. In contrast to earlier low-resolution studies, we found that the electric field within VSDs of Nav channels has a complex isoform- and domain-specific shape, which prominently depends on the activation state of a VSD. Different VSDs vary not only in the length of the region where the electric field is focused but also differ in their overall electrostatics, with possible implications in the diverse ion selectivity of their gating pores. Due to state-dependent field reshaping, not only translocated basic but also relatively immobile acidic residues contribute significantly to the gating charge. In the case of NavAb, we found that the transition between structurally resolved activated and resting states results in a gating charge of 8e, which is noticeably lower than experimental estimates. Based on the analysis of VSD electrostatics in the two activation states, we propose that the VSD likely adopts a deeper resting state upon hyperpolarization. In conclusion, our results provide an atomic-level description of the gating charge, demonstrate diversity in VSD electrostatics, and reveal the importance of electric-field reshaping for voltage sensing in Nav channels.

Cell division during early embryogenesis is linked to key morphogenic events such as embryo symmetry breaking and tissue patterning. It is thought that the physical surrounding of cells together with cell intrinsic cues act as a mechanical "mold," guiding cell division to ensure these events are robust. To quantify how cell division is affected by the mechanical and geometrical environment, we present a novel computational mechanical model of cytokinesis, the final phase of cell division. Simulations with the model reproduced experimentally observed furrow dynamics and describe the volume ratio of daughter cells in asymmetric cell divisions, based on the position and orientation of the mitotic spindle. For dividing cells in geometrically confined environments, we show how the orientation of confinement relative to the division axis modulates the volume ratio in asymmetric cell division. Further, we quantified how cortex viscosity and surface tension determine the shape of a dividing cell and govern bubble-instabilities in asymmetric cell division. Finally, we simulated the formation of the three body axes via sequential (a)symmetric divisions up until the six-cell stage of early C. elegans development, which proceeds within the confines of an eggshell. We demonstrate how model input parameters spindle position and orientation provide sufficient information to reliably predict the volume ratio of daughter cells during the cleavage phase of development. However, for egg geometries perturbed by compression, the model predicts that a change in confinement alone is insufficient to explain experimentally observed differences in cell volume. This points to an effect of the compression on the spindle positioning mechanism. Additionally, the model predicts that confinement stabilizes asymmetric cell divisions against bubble-instabilities.