Nanoscale structural alteration in the nuclei of cells with the progression of carcinogenesis is due to the rearrangements of the basic building blocks in the cell such as DNA, RNA, lipids, etc. Although epigenetic modifications underlie the development of cancer, exposure to carcinogenic chemicals such as alcohol also enhances the development of cancer. We report the effects of chronic alcoholism

Microfluidic-based fluorescent exclusion method allows to tackle the issue of neuronal growth from a volume perspective. Based on this technology, we studied the two main actin-rich structures accompanying the early stages of neuron development, i.e. growth cones, located at the tip of growing neuronal processes, and propagative actin waves. Our work reveals that growth cones tend to loose volume during

Cell fate decision-making events involve the interplay of many molecular processes, ranging from signal transduction to genetic regulation, as well as a set of molecular and physiological feedback loops. Each aspect offers a rich field of investigation in its own right, but to understand the whole process, even in simple terms, we need to consider them together. Here we attempt to characterise this

Microbial range expansion experiments provide insight into the complex link between dynamic structure, pattern formation and evolutionary dynamics of growing populations. In this work, we develop a theoretical model in order to investigate the interplay of growth statistics and mechanical interactions which are implemented as division driven pushing and swapping of cells. For the case of the competitive

The nucleus of eukaryotic cells harbors active and out of equilibrium environments conducive to diverse gene regulatory processes. On a molecular scale, gene regulatory processes take place within hierarchically compartmentalized sub-nuclear bodies. While the impact of nuclear structure on gene regulation is widely appreciated, it has remained much less clear whether and how gene regulation is impacting

In the intracellular environment, the intrinsic dynamics of microtubule filaments is often hindered by the presence of barriers of various kind, such as kinetochore complexes and cell cortex, which impact their polymerisation force and dynamical properties such as catastrophe frequency. We present a theoretical study of the effect of a forced barrier, also subjected to thermal noise, on the statistics

Efficient nucleotide import is critical to fuel the reverse DNA synthesis that takes place within the HIV-1 capsid. However, the mechanism by which the HIV-1 capsid imports nucleotides is presently unclear. In this work, we carry out a series of Brownian diffusion simulations to elucidate the nucleotide import process through the hexamer pores of the HIV-1 capsid. Our simulations reveal a significant

Toxic abnormal aggregation of α-synuclein (α-Syn) is a feature of Parkinson’s disease. Several biochemical and biophysical studies have demonstrated that many post-translational modifications (PTM) of α-Syn could distinctly alleviate its oligomerization-mediated toxicity. Recently, a compelling link is emerging between the PTM O-GlcNAcylation (O-GlcNAc) and protein aggregation, yet the underlying molecular

Parkinson’s disease (PD) is a chronic, progressive neurodegenerative disease and represents the most common disease of this type, after Alzheimer’s dementia. It is characterized by motor and nonmotor features and by a long prodromal stage that lasts many years. Genetic research has shown that PD is a complex and multisystem disorder. To capture the molecular complexity of this disease we used a complex

The proper functions of tissues depend on the ability of cells to withstand stress and maintain shape. Central to this process is the cytoskeleton, comprised of three polymeric networks: F-actin, microtubules, and intermediate filaments (IFs). IF proteins are among the most abundant cytoskeletal proteins in cells; yet they remain some of the least understood. Their structure and function deviate from

We develop a lattice model of site-specific DNA-protein interactions under in vivo conditions where DNA is modelled as a self-avoiding random walk that is embedded in a cubic lattice box resembling the living cell. The protein molecule searches for its cognate site on DNA via a combination of three dimensional (3D) and one dimensional (1D) random walks. Hopping and intersegmental transfers occur depending

A significant challenge in the field of biomedicine is the development of methods to integrate the multitude of dispersed data sets into comprehensive frameworks to be used to generate optimal clinical decisions. Recent technological advances in single cell analysis allow for high-dimensional molecular characterization of cells and populations, but to date, few mathematical models have attempted to

Recent synthetic biology experiments reveal that signaling modules designed to target cell–cell adhesion enable self-organization of multicellular structures Toda et al (2018 Science 361 156–162). Changes in homotypic adhesion that arise through contact-dependent signaling networks result in sorting of an aggregate into two- or three-layered structures. Here we investigate the formation, maintenance

Cellular populations such as avascular tumors and microbial biofilms may ‘invade’ or grow into surrounding populations. The invading population is often comprised of a heterogeneous mixture of cells with varying growth rates. The population may also exhibit mutational instabilities, such as a heavy deleterious mutation load in a cancerous growth. We study the dynamics of a heterogeneous, mutating population

Modern single cell experiments have revealed unexpected heterogeneity in apparently functionally ‘pure’ cell populations. However, we are still lacking a conceptual framework to understand this heterogeneity. Here, we propose that cellular memories—changes in the molecular status of a cell in response to a stimulus, that modify the ability of the cell to respond to future stimuli—are an essential ingredient

We study the reported data from the SARS-CoV-2 pandemic outbreak in January–May 2020 in 119 countries. We observe that the time series of active cases in individual countries (the difference of the total number of confirmed infections and the sum of the total number of reported deaths and recovered cases) display a strong agreement with algebraic growth and at a later epidemic stage also with a combined

To cope with an extremely large or even infinite state space when solving the chemical master equation in biological problems, a potent strategy is to restrict to a finite state projection (FSP) and represent the transition matrix and probability vector in quantized tensor train (QTT) format, leading to savings in storage while retaining accuracy. In an earlier adaptive FSP–QTT algorithm, the multidimensional

The deluge of single-cell data obtained by sequencing, imaging and epigenetic markers has led to an increasingly detailed description of cell state. However, it remains challenging to identify how cells transition between different states, in part because data are typically limited to snapshots in time. A prerequisite for inferring cell state transitions from such snapshots is to distinguish whether

Budding yeast, Saccharomyces cerevisiae, serves as a prime biological model to study mechanisms underlying asymmetric growth. Previous studies have shown that prior to bud emergence, polarization of a conserved small GTPase Cdc42 must be established on the cell membrane of a budding yeast. Additionally, such polarization contributes to the delivery of cell wall remodeling enzymes and hydrolase from

Shelter-in-place and other confinement strategies implemented in the current COVID-19 pandemic have created stratified patterns of contacts between people: close contacts within households and more distant contacts between the households. The epidemic transmission dynamics is significantly modified as a consequence. We introduce a minimal model that incorporates these household effects in the framework

The global spread of coronavirus disease 2019 (COVID-19) is overwhelming many health-care systems. As a result, epidemiological models are being used to inform policy on how to effectively deal with this pandemic. The majority of existing models assume random diffusion but do not take into account differences in the amount of interactions between individuals, i.e. the underlying human interaction network

We argue that frequent sampling of the fraction of a priori non-symptomatic but infectious humans (either by random or cohort testing) significantly improves the management of the COVID-19 pandemic, when compared to intervention strategies relying on data from symptomatic cases only. This is because such sampling measures the incidence of the disease, the key variable controlled by restrictive measures

Eukaryotic cells face the challenging task of transporting a variety of particles through the complex intracellular milieu in order to deliver, distribute, and mix the many components that support cell function. In this review, we explore the biological objectives and physical mechanisms of intracellular transport. Our focus is on cytoplasmic and intra-organelle transport at the whole-cell scale. We

Bacteria across many scales are involved in a dynamic process of information exchange to coordinate activity and community structure within large and diverse populations. The molecular components bacteria use to communicate have been discovered and characterized, and recent efforts have begun to understand the potential for bacterial signal exchange to gather information from the environment and coordinate

The COVID-19 epidemic of the novel coronavirus (severe acute respiratory syndrome SARS-CoV-2) has spread around the world. While different containment policies using non-pharmaceutical interventions have been applied, their efficiencies are not known quantitatively. We show that the doubling time T d ( t ) with the success s factor , the characteristic time of the exponential growth of T d ( t ) in

A central question in eukaryotic cell biology asks, during cell division, how is the growth and distribution of organelles regulated to ensure each daughter cell receives an appropriate amount. For vacuoles in budding yeast, there are well described organelle-to-cell size scaling trends as well as inheritance mechanisms involving highly coordinated movements. It is unclear whether such mechanisms are

Fitting the probability mass functions from analytical solutions of stochastic models of gene expression to the single-cell count distributions of mRNA and protein molecules can yield valuable insights into mechanisms underlying gene expression. Solutions of chemical master equations are available for various kinetic schemes but, even for the basic ON–OFF genetic switch, they take complex forms with

Proteins interact with metabolites, nucleic acids, and other proteins to orchestrate the myriad catalytic, structural and regulatory functions that support life, from the simplest microbes to the most complex multicellular organisms. These molecular interactions are often exquisitely specific, but never perfectly so. Adventitious ‘promiscuous’ interactions are ubiquitous due to the thousands of macromolecules

Error analysis and data visualization of positive COVID-19 cases in 27 countries have been performed up to August 8, 2020. This survey generally observes a progression from early exponential growth transitioning to an intermediate power-law growth phase, as recently suggested by Ziff and Ziff. The occurrence of logistic growth after the power-law phase with lockdowns or social distancing may be described

Different ways of calculating mortality during epidemics have yielded very different results, particularly during the current COVID-19 pandemic. For example, the ‘CFR’ has been interchangeably called the case fatality ratio, case fatality rate, and case fatality risk, often without standard mathematical definitions. The most commonly used CFR is the case fatality ratio , typically constructed using

Epidemiological models usually contain a set of parameters that must be adjusted based on available observations. Once a model has been calibrated, it can be used as a forecasting tool to make predictions and to evaluate contingency plans. It is customary to employ only point estimators of model parameters for such predictions. However, some models may fit the same data reasonably well for a broad

In the absence of other tools, monitoring the effects of protective measures, including social distancing and forecasting the outcome of outbreaks is of immense interest. Real-time data is noisy and very often hampered by systematic errors in reporting. Detailed epidemic models may contain a large number of empirical parameters, which cannot be determined with sufficient accuracy. In this paper, we

Single-cell technologies have revolutionized biomedical research by enabling scalable measurement of the genome, transcriptome, proteome, and epigenome of multiple systems at single-cell resolution. Now widely applied to cancer models, these assays offer new insights into tumour heterogeneity, which underlies cancer initiation, progression, and relapse. However, the large quantities of high-dimensional

Single-molecule force spectroscopy techniques allow for the measurement of several static and dynamic features of macromolecules of biological origin. In particular, atomic force microscopy, used with a variable pulling rate, provides valuable information on the folding/unfolding dynamics of proteins. We propose here two different models able to describe the out-of-equilibrium statistical mechanics

Trauma arising from landmines and improvised explosive devices promotes heterotopic ossification, the formation of extra-skeletal bone in non-osseous tissue. To date, experimental platforms that can replicate the loading parameter space relevant to improvised explosive device and landmine blast wave exposure have not been available to study the effects of such non-physiological mechanical loading on

Integral feedback control is commonly used in mechanical and electrical systems to achieve zero steady-state error following an external disturbance. Equivalently, in biological systems, a property known as robust perfect adaptation guarantees robustness to environmental perturbations and return to the pre-disturbance state. Previously, Briat et al proposed a biomolecular design for integral feedback

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More and more countries are showing a significant slowdown in the number of new COVID-19 infections due to effective governmentally instituted lockdown and social distancing measures. We have analyzed the growth behavior of the top 25 most affected countries by means of a local slope analysis and found three distinct patterns that individual countries follow depending on the strictness of the lockdown

Collective cell migration is crucial in many biological processes such as wound healing, tissue morphogenesis, and tumor progression. The leading front of a collective migrating epithelial cell layer often destabilizes into multicellular finger-like protrusions, each of which is guided by a leader cell at the fingertip. Here, we develop a subcellular-element-based model of this fingering instability

In order to maintain functional robustness and species integrity, organisms must ensure high fidelity of the genome duplication process. This is particularly true during early development, where cell division is often occurring both rapidly and coherently. By studying the extreme limits of suppressing DNA replication failure due to double fork stall errors, we uncover a fundamental constant that describes

We examined PC12 cell proliferation in environments with temporally varying epidermal growth factor concentrations by means of a microfluidic system. Our measurements revealed frequency-dependent cell behaviour over an observation period of three days. The cell population either increased, decreased or remained constant depending on the frequency of epidermal growth factor applied. A plot of the apparent

Cytoplasmic dynein is an important molecular motor involved in the transport of vesicular and macromolecular cargo along microtubules in cells, often in conjunction with kinesin motors. Dynein is larger and more complex than kinesin and the mechanism and regulation of its movement is currently the subject of intense research. While it was believed for a long time that dynein motors are relatively weak

Classically, gene expression is modeled as a chemical process with reaction rates dependent on the concentration of the reactants (typically, DNA loci, plasmids, RNA, enzymes, etc). Other variables like cell size are in general ignored. Size dynamics can become an important variable due to the low number of many of these reactants, imperfectly symmetric cell partitioning and molecule segregation. In

The interplay of small, noncoding microRNAs (miRNAs), mRNAs and proteins plays crucial roles in almost all cellular processes. MiR-124, widely known as a memory-related miRNA, can regulate LTM by binding to the mRNA of CREB1 stimulated with 5-HT. In this paper, we establish a regulatory network model of CREB1 and miR-124 stimulated by 5-HT, in which miR-124 inhibits CREB1, which in turn enhances miR-124

Biological cells are complex environments that are densely packed with macromolecules and subdivided by membranes, both of which affect the rates of chemical reactions. It is well known that crowding reduces the volume available to reactants, which increases reaction rates, and also inhibits reactant diffusion, which decreases reaction rates. This work investigates these effects quantitatively using

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The majority of chronic infections are caused by biofilms, which have higher levels of antibiotic resistance than planktonic growth. Violet-blue 405 nm light has recently emerged as a novel bactericide, but limited studies have been conducted on its effectiveness against biofilms. We found that in response to 405 nm light both Pseudomonas aeruginosa and Bacillus subtilis biofilms exhibited cell dispersal

The aggregation of intrinsically disordered proteins is a hallmark of neurodegenerative diseases, such as Alzheimer's, Parkinson's and Huntington's disease. Although we currently have a good molecular level understanding on how protein aggregation occurs in vitro, the details of its self-assembly in live cells are still mainly unknown. During the last ten years, we have witnessed the rapid development

Understanding how much solvents influence the structures and dynamics of proteins is important to understand functional mechanisms of solvated proteins. We propose a solvated potential model that approximates the potential energy of a solvated protein by projecting the solvent information into the protein structure. Using the model, we derive three properties of the solvent. First, the influence of

We propose a biomechanical model for the extravasation of a tumor cell (TC) through the endothelium of a blood vessel. Based on prior in vitro observations, we assume that the TC extends a protrusion between adjacent endothelial cells (ECs) that adheres to the basement membrane via focal adhesions (FAs). As the protrusion grows in size and branches out, the actomyosin contraction along the stress fibers

A cluster of neural crest cells (NCCs) may chemotax up a shallow external gradient to which a single cell is unresponsive. To explain this intriguing 'group advantage', we propose a chemo-mechanical model based on the signaling proteins Rac1 and RhoA. We represent each cell as a polygon with nodes connected by elastic membranes. Via reaction-diffusion on the membrane and exchange with their cytosolic

Messenger RNAs (mRNAs) consist of a coding region (open reading frame (ORF)) and two untranslated regions (UTRs), 5'UTR and 3'UTR. Ribosomes travel along the coding region, translating nucleotide triplets (called codons) to a chain of amino acids. The coding region was long believed to mainly encode the amino acid content of proteins, whereas regulatory signals reside in the UTRs and in other genomic

Cells are complex machines with tremendous potential for applications in medicine and biotechnology. Although much effort has been devoted to engineering the metabolic, genetic, and signaling pathways of cells, methods for systematically engineering the physical structure of cells are less developed. Here we consider how coarse-grained models for cellular geometry at the organelle level can be used

Understanding nanoscale structural changes can provide information about the physical state of cells/tissues. It has now been shown that increases in nanoscale structural alterations are associated with the progress of carcinogenesis in most cancer cases, including early carcinogenesis. Anti-cancerous therapies are designed to inhibit the growth of cancer cells; however, it is challenging to detect

In this paper, we aim to detect trapping areas (equivalently microdomains or confinement areas) within cells, corresponding to regions where molecules are trapped and thereby undergo subdiffusion. We propose an original computational approach that takes as input a set of molecule trajectories estimated by appropriate tracking methods. The core of the algorithm is based on a combination of clustering

The process by which actin polymerization generates pulling forces in cellular processes such as endocytosis is less well understood than pushing-force generation. To clarify the basic mechanisms of pulling-force generation, we perform stochastic polymerization simulations for a square array of polymerizing semiflexible actin filaments, having different interactions with the membrane. The filaments

During morphogenesis, epithelial tubes elongate. In the case of the mammalian lung, biased elongation has been linked to a bias in cell shape and cell division, but it has remained unclear whether a bias in cell shape along the axis of outgrowth is sufficient for biased outgrowth and how it arises. Here, we use our 2D cell-based tissue simulation software [Formula: see text] to investigate the conditions

We develop a method for solving mathematical models of messenger RNA (mRNA) translation based on the totally asymmetric simple exclusion process (TASEP). Our main goal is to demonstrate that the method is versatile and applicable to realistic models of translation. To this end we consider the TASEP with codon-dependent elongation rates, premature termination due to ribosome drop-off and translation

How bacteria sense local chemical gradients and decide to move has been a fascinating area of recent study. Chemotaxis of bacterial populations has been traditionally modeled using either individual-based models describing the motion of a single bacterium as a velocity jump process, or macroscopic PDE models that describe the evolution of the bacterial density. In these models, the hydrodynamic interaction