Water Hydrogen-Bond Mediated Layer by Layer Alignment of Lipid Rafts as a Precursor of Intermembrane Processes.

Lipid rafts, which are dynamic nanodomains in the plasma membrane, play a crucial role in intermembrane processes by clustering together and growing in size within the plane of the membrane while also aligning with each other across different membranes. However, the physical origin of layer by layer alignment of lipid rafts remains to be elucidated. Here, by using fluorescence imaging and synchrotron X-ray reflectivity in a phase-separated multilayer system, we find that the alignment of raft-mimicking Lo domains is regulated by the distance between bilayers. Molecular dynamics simulations reveal that the aligned state is energetically preferred when the intermembrane distance is small due to its ability to minimize the volume of surface water, which has fewer water hydrogen bonds (HBs) compared to bulk water. Our results suggest that water HB-driven alignment of lipid rafts plays a role as a precursor of intermembrane processes such as cell-cell fusion, virus entry, and signaling.

Glycolytic oscillations under periodic drivings.

In many living organisms displaying circadian rhythms, the intake of energy often occurs in a periodic manner. Glycolysis is a prototypical biochemical reaction that exhibits a self-sustained oscillation under continuous injection of glucose. Here we study the effect of periodic injection of glucose on the glycolytic oscillation from a dynamical systems perspective. In particular, we employ Goldbeter's allosteric model of phosphofructokinase as a model system for glycolytic oscillations, and explore the effect of periodic substrate influx of varying frequencies and amplitudes by building the phase diagrams of Lyapunov exponents and oscillatory periods. When the frequency of driving is tuned around the harmonic and sub/super-harmonic conditions of the natural frequency, the system is entrained to a frequency-locked state, forming an entrainment band that broadens with an increasing amplitude of driving. On the other hand, if the amplitude is substantial, the system may transition, albeit infrequent, to a chaotic state which defies prediction of dynamical behaviour. Our study offers in-depth understandings into the controllability of glycolytic oscillation as well as explaining physical underpinnings that enable the synchronous oscillations among a dense population of cells.

General Chemical Reaction Network Theory for Olfactory Sensing Based on G-Protein-Coupled Receptors: Elucidation of Odorant Mixture Effects and Agonist-Synergist Threshold.

This work presents a general chemical reaction network theory for olfactory sensing processes that employ G-protein-coupled receptors as olfactory receptors (ORs). The theory can be applied to general mixtures of odorants and an arbitrary number of ORs. Reactions of ORs with G-proteins, in both the presence and absence of odorants, are explicitly considered. A unique feature of the theory is the definition of an odor activity vector consisting of strengths of odorant-induced signals from ORs relative to those due to background G-protein activity in the absence of odorants. It is demonstrated that each component of the odor activity defined this way reduces to a Michaelis-Menten form capable of accounting for cooperation or competition effects between different odorants. The main features of the theory are illustrated for a two-odorant mixture. Known and potential mixture effects, such as suppression, shadowing, inhibition, and synergy, are quantitatively described. Effects of relative values of rate constants, basal activity, and G-protein concentration are also demonstrated.

TMAO Destabilizes RNA Secondary Structure via Direct Hydrogen Bond Interactions.

Trimethylamine N-oxide (TMAO) is an osmolyte that accumulates in cells in response to osmotic stress. TMAO stabilizes proteins by the entropic stabilization mechanism, which pictures TMAO as a nanocrowder that predominantly destabilizes the unfolded state. However, the mechanism of action of TMAO on RNA is much less understood. Here, we use all-atom molecular dynamics simulations to investigate how TMAO interacts with a 12-nt RNA hairpin with a high melting temperature, and an 8-nt RNA hairpin, which has a relatively fluid native basin in the absence of TMAO. The use of the two hairpins with different free energy of stabilization allows us to probe the origin of the destabilization effect of TMAO on RNA molecules without the possibility of forming tertiary interactions. We generated multiple trajectories using all-atom molecular dynamics (MD) simulations in explicit water by employing AMBER and CHARMM force fields, both in the absence and presence of TMAO. We observed qualitatively similar RNA-TMAO interaction profiles from the simulations using the two force fields. TMAO hydrogen bond interactions are largely depleted around the paired RNA bases and ribose sugars. In contrast, we show that the oxygen atom in TMAO, the hydrogen bond acceptor, preferentially interacts with the hydrogen bond donors in the solvent exposed bases, such as those in the stem-loop and the destabilized base stacks in the unfolded state, especially in the marginally stable 8-nt RNA hairpin. The predicted destabilization mechanism through TMAO-RNA hydrogen bond interactions could be tested using two-dimensional IR spectroscopy. Since TMAO does not significantly interact with the hydroxyl group of the ribose sugars, we predict that similar results must also hold for DNA.

Polymer Physics-Based Classification of Neurons.

Recognizing that diverse morphologies of neurons are reminiscent of structures of branched polymers, we put forward a principled and systematic way of classifying neurons that employs the ideas of polymer physics. In particular, we use 3D coordinates of individual neurons, which are accessible in recent neuron reconstruction datasets from electron microscope images. We numerically calculate the form factor, F(q), a Fourier transform of the distance distribution of particles comprising an object of interest, which is routinely measured in scattering experiments to quantitatively characterize the structure of materials. For a polymer-like object consisting of n monomers spanning over a length scale of r, F(q) scales with the wavenumber [Formula: see text] as [Formula: see text] at an intermediate range of q, where [Formula: see text] is the fractal dimension or the inverse scaling exponent ([Formula: see text]) characterizing the geometrical feature ([Formula: see text]) of the object. F(q) can be used to describe a neuron morphology in terms of its size ([Formula: see text]) and the extent of branching quantified by [Formula: see text]. By defining the distance between F(q)s as a measure of similarity between two neuronal morphologies, we tackle the neuron classification problem. In comparison with other existing classification methods for neuronal morphologies, our F(q)-based classification rests solely on 3D coordinates of neurons with no prior knowledge of morphological features. When applied to publicly available neuron datasets from three different organisms, our method not only complements other methods but also offers a physical picture of how the dendritic and axonal branches of an individual neuron fill the space of dense neural networks inside the brain.

Moderate activity of RNA chaperone maximizes the yield of self-spliced pre-RNA in vivo.

CYT-19 is a DEAD-box protein whose adenosine-triphosphate (ATP)-dependent helicase activity facilitates the folding of group I introns in precursor RNA (pre-RNA) of Neurospora crassa (N. crassa). In the process, they consume a substantial amount of ATP. While much of the mechanistic insight into CYT-19 activity has been gained through the studies on the folding of Tetrahymena group I intron ribozyme, the more biologically relevant issue, namely the effect of CYT-19 on the self-splicing of pre-RNA, remains largely unexplored. Here, we employ a kinetic network model, based on the generalized iterative annealing mechanism (IAM), to investigate the relation between CYT-19 activity, rate of ribozyme folding, and the kinetics of the self-splicing reaction. The network rate parameters are extracted by analyzing the recent biochemical data for CYT-19-facilitated folding of Tetrahymena ribozyme. We then build extended models to explore the metabolism of pre-RNA. We show that the timescales of chaperone-mediated folding of group I ribozyme and self-splicing reaction compete with each other. As a consequence, in order to maximize the self-splicing yield of group I introns in pre-RNA, the chaperone activity must be sufficiently large to unfold the misfolded structures, but not too large to unfold the native structures prior to the self-splicing event. We discover that despite the promiscuous action on structured RNAs, the helicase activity of CYT-19 on group I ribozyme gives rise to self-splicing yields that are close to the maximum.

Solvent Quality Dependent Osmotic Pressure of Polymer Solutions in Two Dimensions.

Confined in two-dimensional planes, polymer chains comprising dense monolayer solutions are segregated from each other because of topological interaction. Although the segregation is inherent in two dimensions (2D), the solution may display different properties depending on the solvent quality. Among others, it is well-known in both theory and experiment that the osmotic pressure (Π) in the semidilute regime displays solvent quality dependent increases with the area fraction (ϕ) (or monomer concentration, ρ), that is, Π âˆ¼ ϕ3 for good solvents and Π âˆ¼ ϕ8 for Θ solvents. The osmotic pressure can be associated with the Flory exponent (or the correlation length exponent) for the chain size and the pair distribution function of monomers; however, they do not necessarily offer a detailed microscopic picture leading to the difference. To gain microscopic understanding into the different surface pressure isotherms of polymer solutions under the two distinct solvent conditions, we study the chain configurations of the polymer solution based on our numerical simulations that semiquantitatively reproduce the expected scaling behaviors. Notably, at the same value of ϕ, polymer chains in a Θ solvent occupy the surface in a more inhomogeneous manner than the chains in good solvent, yielding on average a greater and more heterogeneous interstitial void size, which is related to the fact that the polymer in the Θ solvent has a greater correlation length. The polymer configurations and interstitial voids visualized and quantitatively analyzed in this study offer microscopic understanding to the origin of the solvent quality dependent osmotic pressure of 2D polymer solutions.

Dissecting the cosegregation probability from genome architecture mapping.

Genome architecture mapping (GAM) is a recently developed methodology that offers the cosegregation probability of two genomic segments from an ensemble of thinly sliced nuclear profiles, enabling us to probe and decipher three-dimensional chromatin organization. The cosegregation probability from GAM binned at 1 Mb, which thus probes the length scale associated with the genomic separation greater than 1 Mb, is, however, not identical to the contact probability obtained from Hi-C, and its correlation with interlocus distance measured with fluorescence in situ hybridization is not so good as the contact probability. In this study, by using a polymer-based model of chromatins, we derive a theoretical expression of the cosegregation probability as well as that of the contact probability and carry out quantitative analyses of how they differ from each other. The results from our study, validated with in silico GAM analysis on three-dimensional genome structures from fluorescence in situ hybridization, suggest that to attain strong correlation with the interlocus distance, a properly normalized version of cosegregation probability needs to be calculated based on a large number of nuclear slices (n>103).

Olfactory responses of Drosophila are encoded in the organization of projection neurons.

The projection neurons (PNs), reconstructed from electron microscope (EM) images of the Drosophila olfactory system, offer a detailed view of neuronal anatomy, providing glimpses into information flow in the brain. About 150 uPNs constituting 58 glomeruli in the antennal lobe (AL) are bundled together in the axonal extension, routing the olfactory signal received at AL to mushroom body (MB) calyx and lateral horn (LH). Here we quantify the neuronal organization in terms of the inter-PN distances and examine its relationship with the odor types sensed by Drosophila. The homotypic uPNs that constitute glomeruli are tightly bundled and stereotyped in position throughout the neuropils, even though the glomerular PN organization in AL is no longer sustained in the higher brain center. Instead, odor-type dependent clusters consisting of multiple homotypes innervate the MB calyx and LH. Pheromone-encoding and hygro/thermo-sensing homotypes are spatially segregated in MB calyx, whereas two distinct clusters of food-related homotypes are found in LH in addition to the segregation of pheromone-encoding and hygro/thermo-sensing homotypes. We find that there are statistically significant associations between the spatial organization among a group of homotypic uPNs and certain stereotyped olfactory responses. Additionally, the signals from some of the tightly bundled homotypes converge to a specific group of lateral horn neurons (LHNs), which indicates that homotype (or odor type) specific integration of signals occurs at the synaptic interface between PNs and LHNs. Our findings suggest that before neural computation in the inner brain, some of the olfactory information are already encoded in the spatial organization of uPNs, illuminating that a certain degree of labeled-line strategy is at work in the Drosophila olfactory system.

Location of the TEMPO moiety of TEMPO-PC in phosphatidylcholine bilayers is membrane phase dependent.

The (2,2,6,6-tetramethylpiperidin-1-yl)oxyl (TEMPO) moiety tethered to the headgroup of phosphatidylcholine (PC) lipid is employed in spin labeling electron paramagnetic resonance spectroscopy to probe the water dynamics near lipid bilayer interfaces. Due to its amphiphilic character, however, TEMPO spin label could partition between aqueous and lipid phases, and may even be stabilized in the lipid phase. Accurate assessment of the TEMPO-PC configuration in bilayer membranes is essential for correctly interpreting the data from measurements. Here, we carry out all-atom molecular dynamics (MD) simulations of TEMPO-PC probe in single-component lipid bilayers at varying temperatures, using two standard MD force fields. We find that, for a dipalmitoylphosphatidylcholine (DPPC) membrane whose gel-to-fluid lipid phase transition occurs at 314 K, while the TEMPO spin label is stabilized above the bilayer interface in the gel phase, there is a preferential location of TEMPO below the membrane interface in the fluid phase. For bilayers made of unsaturated lipids, 1,2-Dioleoyl-sn-glycero-3-phosphocholine (DOPC) and 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC), which adopt the fluid phase at ambient temperature, TEMPO is unequivocally stabilized inside the bilayers. Our finding of membrane phase-dependent positioning of the TEMPO moiety highlights the importance of assessing the packing order and fluidity of lipids under a given measurement condition.

Origin of loose bound of the thermodynamic uncertainty relation in a dissipative two-level quantum system.

Thermodynamic uncertainty relations (TURs), originally discovered for classical systems, dictate the tradeoff between dissipation and fluctuations of irreversible current, specifying a minimal bound that constrains the two quantities. In a series of efforts to extend the relation to the one under more generalized conditions, it has been noticed that the bound is less tight in open quantum processes. To study the origin of the loose bounds, we consider an external field-driven transition dynamics of a two-level quantum system weakly coupled to the bosonic bath as a model of an open quantum system. The model makes it explicit that the imaginary part of quantum coherence, which contributes to dissipation to the environment, is responsible for loosening the TUR bound by suppressing the relative fluctuations in the irreversible current of transitions, whereas the real part of the coherence tightens it. Our study offers a better understanding of how quantum nature affects the TUR bound.

Extracting multi-way chromatin contacts from Hi-C data.

There is a growing realization that multi-way chromatin contacts formed in chromosome structures are fundamental units of gene regulation. However, due to the paucity and complexity of such contacts, it is challenging to detect and identify them using experiments. Based on an assumption that chromosome structures can be mapped onto a network of Gaussian polymer, here we derive analytic expressions for n-body contact probabilities (n > 2) among chromatin loci based on pairwise genomic contact frequencies available in Hi-C, and show that multi-way contact probability maps can in principle be extracted from Hi-C. The three-body (triplet) contact probabilities, calculated from our theory, are in good correlation with those from measurements including Tri-C, MC-4C and SPRITE. Maps of multi-way chromatin contacts calculated from our analytic expressions can not only complement experimental measurements, but also can offer better understanding of the related issues, such as cell-line dependent assemblies of multiple genes and enhancers to chromatin hubs, competition between long-range and short-range multi-way contacts, and condensates of multiple CTCF anchors.

Cost-precision trade-off relation determines the optimal morphogen gradient for accurate biological pattern formation.

Spatial boundaries formed during animal development originate from the pre-patterning of tissues by signaling molecules, called morphogens. The accuracy of boundary location is limited by the fluctuations of morphogen concentration that thresholds the expression level of target gene. Producing more morphogen molecules, which gives rise to smaller relative fluctuations, would better serve to shape more precise target boundaries; however, it incurs more thermodynamic cost. In the classical diffusion-depletion model of morphogen profile formation, the morphogen molecules synthesized from a local source display an exponentially decaying concentration profile with a characteristic length λ. Our theory suggests that in order to attain a precise profile with the minimal cost, λ should be roughly half the distance to the target boundary position from the source. Remarkably, we find that the profiles of morphogens that pattern the Drosophila embryo and wing imaginal disk are formed with nearly optimal λ. Our finding underscores the cost-effectiveness of precise morphogen profile formation in Drosophila development.

Polymer brush-induced depletion interactions and clustering of membrane proteins.

We investigate the effect of mobile polymer brushes on proteins embedded in biological membranes by employing both Asakura-Oosawa type of theoretical model and coarse-grained molecular dynamics simulations. The brush polymer-induced depletion attraction between proteins changes non-monotonically with the size of brush. The depletion interaction, which is determined by the ratio of the protein size to the grafting distance between brush polymers, increases linearly with the brush size as long as the polymer brush height is shorter than the protein size. When the brush height exceeds the protein size, however, the depletion attraction among proteins is slightly reduced. We also explore the possibility of the brush polymer-induced assembly of a large protein cluster, which can be related to one of many molecular mechanisms underlying recent experimental observations of integrin nanocluster formation and signaling.

Extreme parsimony in ATP consumption by 20S complexes in the global disassembly of single SNARE complexes.

Fueled by ATP hydrolysis in N-ethylmaleimide sensitive factor (NSF), the 20S complex disassembles rigid SNARE (soluble NSF attachment protein receptor) complexes in single unraveling step. This global disassembly distinguishes NSF from other molecular motors that make incremental and processive motions, but the molecular underpinnings of its remarkable energy efficiency remain largely unknown. Using multiple single-molecule methods, we found remarkable cooperativity in mechanical connection between NSF and the SNARE complex, which prevents dysfunctional 20S complexes that consume ATP without productive disassembly. We also constructed ATP hydrolysis cycle of the 20S complex, in which NSF largely shows randomness in ATP binding but switches to perfect ATP hydrolysis synchronization to induce global SNARE disassembly, minimizing ATP hydrolysis by non-20S complex-forming NSF molecules. These two mechanisms work in concert to concentrate ATP consumption into functional 20S complexes, suggesting evolutionary adaptations by the 20S complex to the energetically expensive mechanical task of SNARE complex disassembly.

Thermodynamic Optimality of Glycolytic Oscillations.

Temporal order in living matters reflects the self-organizing nature of dynamical processes driven out of thermodynamic equilibrium. Because of functional reasons, the period of a biochemical oscillation must be tuned to a specific value with precision; however, according to the thermodynamic uncertainty relation (TUR), the precision of the oscillatory period is constrained by the thermodynamic cost of generating it. After reviewing the basics of chemical oscillations using the Brusselator as a model system, we study the glycolytic oscillation generated by octameric phosphofructokinase (PFK), which is known to display a period of several minutes. By exploring the phase space of glycolytic oscillations, we find that the glycolytic oscillation under the cellular condition is realized in a cost-effective manner. Specifically, over the biologically relevant range of parameter values of glycolysis and octameric PFK, the entropy production from the glycolytic oscillation is minimal when the oscillation period is (5-10) min. Furthermore, the glycolytic oscillation is found at work near the phase boundary of limit cycles, suggesting that a moderate increase of glucose injection rate leads to the loss of oscillatory dynamics, which is reminiscent of the loss of pulsatile insulin release resulting from elevated blood glucose level.

Thermodynamic uncertainty relation to assess biological processes.

We review the trade-offs between speed, fluctuations, and thermodynamic cost involved with biological processes in nonequilibrium states and discuss how optimal these processes are in light of the universal bound set by the thermodynamic uncertainty relation (TUR). The values of the uncertainty product Q of TUR, which can be used as a measure of the precision of enzymatic processes realized for a given thermodynamic cost, are suboptimal when the substrate concentration is at the Michaelis constant, and some of the key biological processes are found to work around this condition. We illustrate the utility of Q in assessing how close the molecular motors and biomass producing machineries are to the TUR bound, and for the cases of biomass production (or biological copying processes), we discuss how their optimality quantified in terms of Q is balanced with the error rate in the information transfer process. We also touch upon the trade-offs in other error-minimizing processes in biology, such as gene regulation and chaperone-assisted protein folding. A spectrum of Q recapitulating the biological processes surveyed here provides glimpses into how biological systems are evolved to optimize and balance the conflicting functional requirements.

A unified framework for inferring the multi-scale organization of chromatin domains from Hi-C.

Chromosomes are giant chain molecules organized into an ensemble of three-dimensional structures characterized with its genomic state and the corresponding biological functions. Despite the strong cell-to-cell heterogeneity, the cell-type specific pattern demonstrated in high-throughput chromosome conformation capture (Hi-C) data hints at a valuable link between structure and function, which makes inference of chromatin domains (CDs) from the pattern of Hi-C a central problem in genome research. Here we present a unified method for analyzing Hi-C data to determine spatial organization of CDs over multiple genomic scales. By applying statistical physics-based clustering analysis to a polymer physics model of the chromosome, our method identifies the CDs that best represent the global pattern of correlation manifested in Hi-C. The multi-scale intra-chromosomal structures compared across different cell types uncover the principles underlying the multi-scale organization of chromatin chain: (i) Sub-TADs, TADs, and meta-TADs constitute a robust hierarchical structure. (ii) The assemblies of compartments and TAD-based domains are governed by different organizational principles. (iii) Sub-TADs are the common building blocks of chromosome architecture. Our physically principled interpretation and analysis of Hi-C not only offer an accurate and quantitative view of multi-scale chromatin organization but also help decipher its connections with genome function.

Revisiting the organization of Polycomb-repressed domains: 3D chromatin models from Hi-C compared with super-resolution imaging.

The accessibility of target gene, a factor critical for gene regulation, is controlled by epigenetic fine-tuning of chromatin organization. While there are multiple experimental techniques to study change of chromatin architecture with its epigenetic state, measurements from them are not always complementary. A qualitative discrepancy is noted between recent super-resolution imaging studies, particularly on Polycomb-group protein repressed domains in Drosophila cell. One of the studies shows that Polycomb-repressed domains are more compact than inactive domains and are segregated from neighboring active domains, whereas Hi-C and chromatin accessibility assay as well as the other super-resolution imaging studies paint a different picture. To examine this issue in detail, we analyzed Hi-C libraries of Drosophila chromosomes as well as distance constraints from one of the imaging studies, and modeled different epigenetic domains by employing a polymer-based approach. According to our chromosome models, both Polycomb-repressed and inactive domains are featured with a similar degree of intra-domain packaging and significant intermixing with adjacent active domains. The epigenetic domains explicitly visualized by our polymer model call for extra attention to the discrepancy of the super-resolution imaging with other measurements, although its precise physicochemical origin still remains to be elucidated.