SEARCH · Searcharxiv

Results for “q-bio.SC”

Search indexed arXiv papers on artificial intelligence, large language models, computer vision and robotics. Read source abstracts and follow links to arXiv.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 379 records · Page 21Linked to original sources

arXiv2017

Diverse spatial expression patterns emerge from common transcription bursting kinetics

In early development, regulation of transcription results in precisely positioned and highly reproducible expression patterns that specify cellular identities. How transcription, a fundamentally noisy molecular process, is regulated to achieve reliable embryonic patterning remains unclear. In particular, it is unknown how gene-specific regulation mechanisms affect kinetic rates of transcription, and whether there are common, global features that govern these rates across a genetic network. Here, we measure nascent transcriptional activity in the gap gene network of early Drosophila embryos and characterize the variability in absolute activity levels across expression boundaries. We demonstrate that boundary formation follows a common transcriptional principle: a single control parameter determines the distribution of transcriptional activity, regardless of gene identity, boundary position, or enhancer-promoter architecture. By employing a minimalist model of transcription, we infer kinetic rates of transcriptional bursting for these patterning genes; we find that the key regulatory parameter is the fraction of time a gene is in an actively transcribing state, while the rate of Pol II loading appears globally conserved. These results point to a universal simplicity underlying the apparently complex transcriptional processes responsible for early embryonic patterning and indicate a path to general rules in transcriptional regulation.

q-bio.SC↗

arXiv2018

Protein Pattern Formation

Protein pattern formation is essential for the spatial organization of many intracellular processes like cell division, flagellum positioning, and chemotaxis. A prominent example of intracellular patterns are the oscillatory pole-to-pole oscillations of Min proteins in \textit{E. coli} whose biological function is to ensure precise cell division. Cell polarization, a prerequisite for processes such as stem cell differentiation and cell polarity in yeast, is also mediated by a diffusion-reaction process. More generally, these functional modules of cells serve as model systems for self-organization, one of the core principles of life. Under which conditions spatio-temporal patterns emerge, and how these patterns are regulated by biochemical and geometrical factors are major aspects of current research. Here we review recent theoretical and experimental advances in the field of intracellular pattern formation, focusing on general design principles and fundamental physical mechanisms.

physics.bio-ph↗

arXiv2018

G protein-coupled receptor-mediated calcium signaling in astrocytes

Astrocytes express a large variety of G~protein-coupled receptors (GPCRs) which mediate the transduction of extracellular signals into intracellular calcium responses. This transduction is provided by a complex network of biochemical reactions which mobilizes a wealth of possible calcium-mobilizing second messenger molecules. Inositol 1,4,5-trisphosphate is probably the best known of these molecules whose enzymes for its production and degradation are nonetheless calcium-dependent. We present a biophysical modeling approach based on the assumption of Michaelis-Menten enzyme kinetics, to effectively describe GPCR-mediated astrocytic calcium signals. Our model is then used to study different mechanisms at play in stimulus encoding by shape and frequency of calcium oscillations in astrocytes.

q-bio.SC↗

arXiv2018

Generalizing Gillespie's direct method to enable network-free simulations

Gillespie's direct method for stochastic simulation of chemical kinetics is a staple of computational systems biology research. However, the algorithm requires explicit enumeration of all reactions and all chemical species that may arise in the system. In many cases, this is not feasible due to the combinatorial explosion of reactions and species in biological networks. Rule-based modeling frameworks provide a way to exactly represent networks containing such combinatorial complexity, and generalizations of Gillespie's direct method have been developed as simulation engines for rule-based modeling languages. Here, we provide both a high-level description of the algorithms underlying the simulation engines, termed network-free simulation algorithms, and how they have been applied in systems biology research. We also define a generic rule-based modeling framework and describe a number of technical details required for adapting Gillespie's direct method for network-free simulation. Finally, we briefly discuss potential avenues for advancing network-free simulation and the role they continue to play in modeling dynamical systems in biology.

q-bio.QM↗

arXiv2018

In silico evolution of signaling networks using rule-based models: bistable response dynamics

One of the ultimate goals in biology is to understand the design principles of biological systems. Such principles, if they exist, can help us better understand complex, natural biological systems and guide the engineering of de novo ones. Towards deciphering design principles, in silico evolution of biological systems with proper abstraction is a promising approach. Here, we demonstrate the application of in silico evolution combined with rule-based modelling for exploring design principles of cellular signaling networks. This application is based on a computational platform, called BioJazz, which allows in silico evolution of signaling networks with unbounded complexity. We provide a detailed introduction to BioJazz architecture and implementation and describe how it can be used to evolve and/or design signaling networks with defined dynamics. For the latter, we evolve signaling networks with switch-like response dynamics and demonstrate how BioJazz can result in new biological insights on network structures that can endow bistable response dynamics. This example also demonstrated both the power of BioJazz in evolving and designing signaling networks and its limitations at the current stage of development.

q-bio.MN↗

arXiv2018

Fidelity of bacterial translation initiation: a stochastic kinetic model

During the initiation stage of protein synthesis, a ribosomal initiation complex (IC) is assembled on a messenger RNA (mRNA) template. In bacteria, the speed and accuracy of this assembly process are regulated by the complementary activities of three essential initiation factors (IFs). Selection of an authentic N-formylmethionyl-transfer RNA (fMet-tRNA\textsuperscript{fMet}) and the canonical, triplet-nucleotide mRNA start codon are crucial events during assembly of a canonical, ribosomal 70S IC. Mis-initiation due to the aberrant selection of an elongator tRNA or a non-canonical start codon are rare events that result in the assembly of a pseudo 70S IC or a non-canonical 70S IC, respectively. Here, we have developed a theoretical model for the stochastic kinetics of canonical-, pseudo-, and non-canonical 70S IC assembly that includes all of the major steps of the IC assembly process that have been observed and characterized in ensemble kinetic-, single-molecule kinetic-, and structural studies of the fidelity of translation initiation. Specifically, we use the rates of the individual steps in the IC assembly process and the formalism of first-passage times to derive exact analytical expressions for the probability distributions for the assembly of canonical-, pseudo- and non-canonical 70S ICs. In order to illustrate the power of this analytical approach, we compare the theoretically predicted first-passage time distributions with the corresponding computer simulation data. We also compare the mean times required for completion of these assemblies with experimental estimates. In addition to generating new, testable hypotheses, our theoretical model can also be easily extended as new experimental 70S IC assembly data become available, thereby providing a versatile tool for interpreting these data and developing advanced models of the mechanism and regulation of translation initiation.

physics.bio-ph↗

arXiv2018

PEBP1/RKIP: from multiple functions to a common role in cellular processes

PEBPs (PhosphatidylEthanolamine Binding Proteins) form a protein family widely present in the living world since they are encountered in microorganisms, plants and animals. In all organisms PEBPs appear to regulate important mechanisms that govern cell cycle, proliferation, differentiation and motility. In humans, three PEBPs have been identified, namely PEBP1, PEBP2 and PEBP4. PEBP1 and PEBP4 are the most studied as they are implicated in the development of various cancers. PEBP2 is specific of testes in mammals and was essentially studied in rats and mice where it is very abundant. A lot of information has been gained on PEBP1 also named RKIP (Raf Kinase Inhibitory protein) due to its role as a metastasis suppressor in cancer. PEBP1 was also demonstrated to be implicated in Alzheimers disease, diabetes and nephropathies. Furthermore, PEBP1 was described to be involved in many cellular processes, among them are signal transduction, inflammation, cell cycle, proliferation, adhesion, differentiation, apoptosis, autophagy, circadian rhythm and mitotic spindle checkpoint. On the molecular level, PEBP1 was shown to regulate several signaling pathways such as Raf/MEK/ERK, NFkB, PI3K/Akt/mTOR, p38, Notch and Wnt. PEBP1 acts by inhibiting most of the kinases of these signaling cascades. Moreover, PEBP1 is able to bind to a variety of small ligands such as ATP, phospholipids, nucleotides, flavonoids or drugs. Considering PEBP1 is a small cytoplasmic protein (21kDa), its involvement in so many diseases and cellular mechanisms is amazing. The aim of this review is to highlight the molecular systems that are common to all these cellular mechanisms in order to decipher the specific role of PEBP1. Recent discoveries enable us to propose that PEBP1 is a modulator of molecular interactions that control signal transduction during membrane and cytoskeleton reorganization.

q-bio.SC↗

arXiv2018

Existence and stability of periodic solutions of an impulsive differential equation and application to CD8 T-cell differentiation

Unequal partitioning of the molecular content at cell division has been shown to be a source of heterogeneity in a cell population. We propose to model this phenomenon with the help of a scalar, nonlinear impulsive differential equation (IDE). In a first part, we consider a general autonomous IDE with fixed times of impulse and a specific form of impulse function. We establish properties of the solutions of that equation, most of them obtained under the hypothesis that impulses occur periodically. In particular, we show how to investigate the existence of periodic solutions and their stability by studying the flow of an autonomous differential equation. A second part is dedicated to the analysis of the convexity of this flow. Finally, we apply those results to an IDE describing the concentration of the protein Tbet in a CD8 T-cell, where impulses are associated to cell division, to study the effect of molecular partitioning at cell division on the effector/memory cell-fate decision in a CD8 T-cell lineage. We show that the degree of asymmetry in the molecular partitioning can affect the process of cell differentiation and the phenotypical heterogeneity of a cell population.

math.DS↗

arXiv2018

Single-molecular and Ensemble-level Oscillations of Cyanobacterial Circadian Clock

When three cyanobacterial proteins, KaiA, KaiB, and KaiC, are incubated with ATP in vitro, the phosphorylation level of KaiC hexamers shows stable oscillation with approximately 24 h period. In order to understand this KaiABC clockwork, we need to analyze both the macroscopic synchronization of a large number of KaiC hexamers and the microscopic reactions and structural changes in individual KaiC molecules. In the present paper, we explain two coarse-grained theoretical models, the many-molecule (MM) model and the single-molecule (SM) model, to bridge the gap between macroscopic and microscopic understandings. In the simulation results with these models, ATP hydrolysis drives oscillation of individual KaiC hexamers and ATP hydrolysis is necessary for synchronizing oscillations of a large number of KaiC hexamers. Sensitive temperature dependence of the lifetime of the ADP bound state in the CI domain of KaiC hexamers makes the oscillation period temperature insensitive. ATPase activity is correlated to the frequency of phosphorylation oscillation in the single molecule of KaiC hexamer, which should be the origin of the observed ensemble-level correlation between the ATPase activity and the frequency of phosphorylation oscillation. Thus, the simulation results with the MM and SM models suggest that ATP hydrolysis randomly occurring in each CI domain of individual KaiC hexamers is a key process for oscillatory behaviors of the ensemble of many KaiC hexamers.

q-bio.MN↗

arXiv2018

Universal kinetics for engagement of mechanosensing pathways in cell adhesion

When plated onto substrates, cell morphology and even stem cell differentiation are influenced by the stiffness of their environment. Stiffer substrates give strongly spread (eventually polarized) cells with strong focal adhesions, and stress fibers; very soft substrates give a less developed cytoskeleton, and much lower cell spreading. The kinetics of this process of cell spreading is studied extensively, and important universal relationships are established on how the cell area grows with time. Here we study the population dynamics of spreading cells, investigating the characteristic processes involved in cell response to the substrate. We show that unlike the individual cell morphology, this population dynamics does not depend on the substrate stiffness. Instead, a strong activation temperature dependence is observed. Different cell lines on different substrates all have long-time statistics controlled by the thermal activation over a single energy barrier dG=19 kcal/mol, while the early-time kinetics follows a power law $t^5$. This implies that the rate of spreading depends on an internal process of adhesion-mechanosensing complex assembly and activation: the operational complex must have 5 component proteins, and the last process in the sequence (which we believe is the activation of focal adhesion kinase) is controlled by the binding energy dG.

q-bio.SC↗

arXiv2018

Curvature-sensitive kinesin binding can explain microtubule ring formation and reveals chaotic dynamics in a mathematical model

Microtubules are filamentous tubular protein polymers which are essential for a range of cellular behaviour, and are generally straight over micron length scales. However, in some gliding assays, where microtubules move over a carpet of molecular motors, individual microtubules can also form tight arcs or rings, even in the absence of crosslinking proteins. Understanding this phenomenon may provide important explanations for similar highly curved microtubules which can be found in nerve cells undergoing neurodegeneration. We propose a model for gliding assays where the kinesins moving the microtubules over the surface induce ring formation through differential binding, substantiated by recent findings that a mutant version of the motor protein kinesin applied in solution is able to lock-in microtubule curvature. For certain parameter regimes, our model predicts that both straight and curved microtubules can exist simultaneously as stable steady-states, as has been seen experimentally. Additionally, unsteady solutions are found, where a wave of differential binding propagates down the microtubule as it glides across the surface, which can lead to chaotic motion. Whilst this model explains two-dimensional microtubule behaviour in an experimental gliding assay, it has the potential to be adapted to explain pathological curling in nerve cells.

q-bio.SC↗

arXiv2018

Dynamics of the Selkov oscillator

A classical example of a mathematical model for oscillations in a biological system is the Selkov oscillator, which is a simple description of glycolysis. It is a system of two ordinary differential equations which, when expressed in dimensionless variables, depends on two parameters. Surprisingly it appears that no complete rigorous analysis of the dynamics of this model has ever been given. In this paper several properties of the dynamics of solutions of the model are established. With a view to studying unbounded solutions a thorough analysis of the Poincaré compactification of the system is given. It is proved that for any values of the parameters there are solutions which tend to infinity at late times and are eventually monotone. It is shown that when the unique steady state is stable any bounded solution converges to the steady state at late times. When the steady state is unstable it is shown that for given values of the parameters either there is a unique periodic solution to which all bounded solutions other than the steady state converge at late times or there is no periodic solution and all solutions other than the steady state are unbounded. In the latter case each unbounded solution which tends to infinity is eventually monotone and each unbounded solution which does not tend to infinity has the property that each variable takes on arbitrarily large and small values at arbitrarily late times.

q-bio.SC↗

arXiv2018

Kinetics of Protein-DNA Interactions: First-Passage Analysis

All living systems can function only far away from equilibrium, and for this reason chemical kinetic methods are critically important for uncovering the mechanisms of biological processes. Here we present a new theoretical method of investigating dynamics of protein-DNA interactions, which govern all major biological processes. It is based on a first-passage analysis of biochemical and biophysical transitions, and it provides a fully analytic description of the processes. Our approach is explained for the case of a single protein searching for a specific binding site on DNA. In addition, the application of the method to investigations of the effect of DNA sequence heterogeneity, and the role multiple targets and traps in the protein search dynamics are discussed.

q-bio.SC↗

arXiv2018

Visualizing mitochondrial FoF1-ATP synthase as the target of the immunomodulatory drug Bz-423

Targeting the mitochondrial enzyme FoF1-ATP synthase and modulating its catalytic activities with small molecules is a promising new approach for treatment of autoimmune diseases. The immuno-modulatory compound Bz-423 is such a drug that binds to subunit OSCP of the mitochondrial FoF1-ATP synthase and induces apoptosis via increased reactive oxygen production in coupled, actively respiring mitochondria. Here we review the experimental progress to reveal the binding of Bz-423 to the mitochondrial target and discuss how subunit rotation of FoF1-ATP synthase is affected by Bz-423. Briefly, we report how Förster resonance energy transfer (FRET) can be employed to colocalize the enzyme and the fluorescently tagged Bz-423 within the mitochondria of living cells with nanometer resolution.

q-bio.SC↗

arXiv2018

Stress-dependent amplification of active forces in nonlinear elastic media

The production of mechanical stresses in living organisms largely relies on localized, force-generating active units embedded in filamentous matrices. Numerical simulations of discrete fiber networks with fixed boundaries have shown that buckling in the matrix dramatically amplifies the resulting active stresses. Here we extend this result to a bucklable continuum elastic medium subjected to an arbitrary external stress, and derive analytical expressions for the active, nonlinear constitutive relations characterizing the full active medium. Inserting these relations into popular "active gel" descriptions of living tissues and the cytoskeleton will enable investigations into nonlinear regimes previously inaccessible due to the phenomenological nature of these theories.

physics.bio-ph↗

arXiv2018

Fiber plucking by molecular motors yields large emergent contractility in stiff biopolymer networks

The mechanical properties of the cell depend crucially on the tension of its cytoskeleton, a biopolymer network that is put under stress by active motor proteins. While the fibrous nature of the network is known to strongly affect the transmission of these forces to the cellular scale, our understanding of this process remains incomplete. Here we investigate the transmission of forces through the network at the individual filament level, and show that active forces can be geometrically amplified as a transverse motor-generated force force "plucks" the fiber and induces a nonlinear tension. In stiff and densely connnected networks, this tension results in large network-wide tensile stresses that far exceed the expectation drawn from a linear elastic theory. This amplification mechanism competes with a recently characterized network-level amplification due to fiber buckling, suggesting that that fiber networks provide several distinct pathways for living systems to amplify their molecular forces.

cond-mat.soft↗

arXiv2018

Saikosaponins with similar structures but different mechanisms lead to combined hepatotoxicity

Radix Bupleuri is a hepatoprotective traditional Chinese medicine (TCM) used for thousands of years in clinical, which was reported to be linked with liver damage. Previous studies have revealed that saikosaponins are the major types of components that contribute to the hepatotoxicity of Radix Bupleuri. However the underlying molecular mechanism is far from being understood. In order to clarify whether these structural analogues exert toxicity effects through the same molecular targets, a systematic comparison study was done in this paper. The effects of SSa, b2, c, and d on isolated rat liver mitochondria and human hepatocyte L02 cells were explored, respectively. The collective results indicated that although saikosaponins share the similar structures but they have quite different mechanisms. SSb2 and SSd showed most serious damage on the function of mitochondria and survival rate of cell, respectively. SSb2 could cause mitochondrial permeability transition pore (mPTP) opening and collapse of mitochondrial membrane potential (ΔΨm) by impairing the mitochondrial respiratory chain complex III. While SSd destroyed plasma membrane and led to the release of lactate dehydrogenase (LDH) mainly through activating caspase-1. Furthermore, the combine index (CI) demonstrated that the combined hepatotoxicity of SSb2 and SSd could be additive. This finding might yield more in depth understanding of hepatotoxicity of Radix Bupleuri possess many different saikosaponins.

q-bio.SC↗

arXiv2018

Computational mechanisms in genetic regulation by RNA

The evolution of the genome has led to very sophisticated and complex regulation. Because of the abundance of non-coding RNA (ncRNA) in the cell, different species will promiscuously associate with each other, suggesting collective dynamics similar to artificial neural networks. Here we present a simple mechanism allowing ncRNA to perform computations equivalent to neural network algorithms such as Boltzmann machines and the Hopfield model. The quantities analogous to the neural couplings are the equilibrium constants between different RNA species. The relatively rapid equilibration of RNA binding and unbinding is regulated by a slower process that degrades and creates new RNA. The model requires that the creation rate for each species be an increasing function of the ratio of total to unbound RNA. Similar mechanisms have already been found to exist experimentally for ncRNA regulation. With the overall concentration of RNA regulated, equilibrium constants can be chosen to store many different patterns, or many different input-output relations. The network is also quite insensitive to random mutations in equilibrium constants. Therefore one expects that this kind of mechanism will have a much higher mutation rate than ones typically regarded as being under evolutionary constraint.

q-bio.MN↗