arXiv subjects

Bartlomiej Waclaw

Publications and source records attributed to Bartlomiej Waclaw.

At least 19 recordsLinked to original sources

arXiv2026

An Affordable Fiducial Marker Strategy for Reliable Autofocus in Long-Term Live Microscopy

Long-term time-lapse imaging of biological samples requires correcting for focal drift, which would otherwise gradually push the sample out of focus. We present a software-based method that eliminates this time-dependent blur using only a motorized Z-drive, with no additional hardware. The method relies on imaging marks made on the side of the coverslip opposite to the sample. We provide a Beanshell script implementation, evaluate its performance across multiple objectives, and benchmark it against a hardware autofocus system, finding comparable results. Finally, we demonstrate its effectiveness in live imaging of growing bacterial colonies.

physics.bio-ph↗

arXiv2025

Phase separation in a mixture of proliferating and motile active matter

Proliferation and motility are ubiquitous drivers of activity in biological systems. Here, we study a dense binary mixture of motile and proliferating particles with exclusively repulsive interactions, where homeostasis in the proliferating subpopulation is maintained by pressure-induced removal. Using computer simulations, we show that phase separation emerges naturally in this system at high density and weak enough self-propulsion. We show that condensation is caused by interactions between motile particles induced by the growing phase, and recapitulate this behavior in an effective model of only motile particles with attractive interactions. Our results establish a new type of phase transition and pave a way to reinterpret the physics of dense cellular populations, such as bacterial colonies or tumors, as systems of mixed active matter.

cond-mat.soft↗

arXiv2023

Substrate geometry affects population dynamics in a bacterial biofilm

Biofilms inhabit a range of environments, such as dental plaques or soil micropores, often characterized by intricate, non-even surfaces. However, the impact of surface irregularities on the population dynamics of biofilms remains elusive as most biofilm experiments are conducted on flat surfaces. Here, we show that the shape of the surface on which a biofilm grows influences genetic drift and selection within the biofilm. We culture E. coli biofilms in micro-wells with an undulating bottom surface and observe the emergence of clonal sectors whose size corresponds to that of the undulations, despite no physical barrier separating different areas of the biofilm. The sectors are remarkably stable over time and do not invade each other; we attribute this stability to the characteristics of the velocity field within the growing biofilm, which hinders mixing and clonal expansion. A microscopically-detailed computer model fully reproduces these findings and highlights the role of mechanical (physical) interactions such as adhesion and friction in microbial evolution. The model also predicts clonal expansion to be severely limited even for clones with a significant growth advantage - a finding which we subsequently confirm experimentally using a mixture of antibiotic-sensitive and antibiotic-resistant mutants in the presence of sub-lethal concentrations of the antibiotic rifampicin. The strong suppression of selection contrasts sharply with the behavior seen in bacterial colonies on agar commonly used to study range expansion and evolution in biofilms. Our results show that biofilm population dynamics can be controlled by patterning the surface, and demonstrate how a better understanding of the physics of bacterial growth can pave the way for new strategies in steering microbial evolution.

q-bio.PE↗

arXiv2023

Evolutionary adaptation is facilitated by the presence of lethal genotypes

The adaptation rate in theoretical models of biological evolution increases with the mutation rate but only to a point when mutations into lethal states cause extinction. One would expect that removing such states should be beneficial for evolution. We show here that, counter-intuitively, lethal mutations speed up adaptation on rugged fitness landscapes with many fitness maxima and minima, if strong competition for resources exist. We consider a modified stochastic version of the quasispecies model with two types of genotypes, viable and lethal, and show that increasing the rate of lethal mutations decreases the time to evolve the best-fit genotype. This can be explained by an increased rate of crossing fitness valleys, facilitated by reduced selection against less-fit variants.

q-bio.PE↗

arXiv2023

Resonant noise amplification in a predator-prey model with quasi-discrete generations

Predator-prey models have been shown to exhibit resonance-like behaviour, in which random fluctuations in the number of organisms (demographic noise) are amplified when their frequency is close to the natural oscillatory frequency of the system. This behaviour has been traditionally studied in models with exponentially distributed replication and death times. Here we consider a biologically more realistic model, in which organisms replicate quasi-synchronously such that the distribution of replication times has a narrow maximum at some $T>0$ corresponding to the mean doubling time. We show that when the frequency of replication $f=1/T$ is tuned to the natural oscillatory frequency of the predator-prey model, the system exhibits oscillations that are much stronger than in the model with Poissonian (non-synchronous) replication and death. The effect can be explained by resonant amplification of coloured noise generated by quasi-synchronous replication events. To show this, we consider a single-species model with quasi-synchronous replication. We calculate the spectrum and the amplitude of demographic noise in this model, and use these results to obtain these quantities for the two-species model.

cond-mat.stat-mech↗

arXiv2020

Current-density relation in the exclusion process with dynamic obstacles

We investigate the totally asymmetric simple exclusion process (TASEP) in the presence of obstacles that dynamically bind and unbind from the lattice. The model is motivated by biological processes such as transcription in the presence of DNA-binding proteins. Similar models have been studied before using the mean-field approximation, but the exact relation between the particle current and density remains elusive. Here, we first show using extensive Monte Carlo simulations that the current-density relation in this model assumes a quasi-parabolic form similar to that of the ordinary TASEP without obstacles. We then attempt to explain this relation using exact calculations in the limit of low and high density of particles. Our results suggest that the symmetric, quasi-parabolic current-density relation arises through a non-trivial cancellation of higher-order terms, similarly as in the standard TASEP.

cond-mat.stat-mech↗

arXiv2018

Bacterial growth: a statistical physicist's guide

Bacterial growth presents many beautiful phenomena that pose new theoretical challenges to statistical physicists, and are also amenable to laboratory experimentation. This review provides some of the essential biological background, discusses recent applications of statistical physics in this field, and highlights the potential for future research.

q-bio.CB↗

arXiv2018

Totally asymmetric exclusion process with site-wise dynamic disorder

We propose an extension of the totally asymmetric simple exclusion process (TASEP) in which particles hopping along a lattice can be blocked by obstacles that dynamically attach/detach from lattice sites. The model can be thought as TASEP with site-wise dynamic disorder. We consider two versions of defect dynamics: (i) defects can bind to any site, irrespective of particle occupation, (ii) defects only bind to sites which are not occupied by particles (particle-obstacle exclusion). In case (i) there is a symmetric, parabolic-like relationship between the current and particle density, as in the standard TASEP. Case (ii) leads to a skewed relationship for slow defect dynamics. We also show that the presence of defects induces particle clustering, despite the translation invariance of the system. For open boundaries the same three phases as for the standard TASEP are observed, albeit the position of phase boundaries is affected by the presence of obstacles. We develop a simple mean-field theory that captures the model's quantitative behaviour for periodic and open boundary conditions and yields good estimates for the current-density relationship, mean cluster sizes and phase boundaries. Lastly, we discuss an application of the model to the biological process of gene transcription.

cond-mat.stat-mech↗

arXiv2018

Reduced adhesion between cells and substrate confers selective advantage in bacterial colonies

Microbial colonies cultured on agar Petri dishes have become a model system to study biological evolution in populations expanding in space. Processes such as clonal segregation and gene surfing have been shown to be affected by interactions between microbial cells and their environment. In this work we investigate the role of mechanical interactions such as cell-surface adhesion. We compare two strains of the bacterium E. coli: a wild-type strain and a "shaved" strain that adheres less to agar. We show that the shaved strain has a selective advantage over the wild type: although both strains grow with the same rate in liquid media, the shaved strain produces colonies that expand faster on agar. This allows the shaved strain outgrow the wild type when both strains compete for space. We hypothesise that, in contrast to a more common scenario in which selective advantage results from increased growth rate, the higher fitness of the shaved strain is caused by reduced adhesion and friction with the agar surface.

q-bio.PE↗

arXiv2017

A physics-explicit model of bacterial conjugation shows the stabilizing role of the conjugative junction

Conjugation is a process in which bacteria exchange DNA through a physical connection (conjugative junction) between mating cells. Despite its significance for processes such as the spread of antibiotic resistance, the role of physical forces in conjugation is poorly understood. Here we use computer models to show that the conjugative junction not only serves as a link to transfer the DNA but it also mechanically stabilises the mating pair which significantly increases the conjugation rate. We discuss the importance of our findings for biological evolution and suggest experiments to validate them.

q-bio.PE↗

arXiv2017

Mechanical interactions in bacterial colonies and the surfing probability of beneficial mutations

Bacterial conglomerates such as biofilms and microcolonies are ubiquitous in nature and play an important role in industry and medicine. In contrast to well-mixed, diluted cultures routinely used in microbial research, bacteria in a microcolony interact mechanically with one another and with the substrate to which they are attached. Despite their ubiquity, little is known about the role of such mechanical interactions on growth and biological evolution of microbial populations. Here we use a computer model of a microbial colony of rod-shaped cells to investigate how physical interactions between cells determine their motion in the colony, this affects biological evolution. We show that the probability that a faster-growing mutant "surfs" at the colony's frontier and creates a macroscopic sector depends on physical properties of cells (shape, elasticity, friction). Although all these factors contribute to the surfing probability in seemingly different ways, they all ultimately exhibit their effects by altering the roughness of the expanding frontier of the colony and the orientation of cells. Our predictions are confirmed by experiments in which we measure the surfing probability for colonies of different front roughness. Our results show that physical interactions between bacterial cells play an important role in biological evolution of new traits, and suggest that these interaction may be relevant to processes such as de novo evolution of antibiotic resistance.

physics.bio-ph↗

arXiv2016

Antibiotic resistance: a physicist's view

The problem of antibiotic resistance poses challenges across many disciplines. One such challenge is to understand the fundamental science of how antibiotics work, and how resistance to them can emerge. This is an area where physicists can make important contributions. Here, we highlight cases where this is already happening, and suggest directions for further physics involvement in antimicrobial research.

q-bio.PE↗

arXiv2016

Phenotypic switching can speed up biological evolution of microbes

Stochastic phenotype switching has been suggested to play a beneficial role in microbial populations by leading to the division of labour among cells, or ensuring that at least some of the population survives an unexpected change in environmental conditions. Here we use a computational model to investigate an alternative possible function of stochastic phenotype switching - as a way to adapt more quickly even in a static environment. We show that when a genetic mutation causes a population to become less fit, switching to an alternative phenotype with higher fitness (growth rate) may give the population enough time to develop compensatory mutations that increase the fitness again. The possibility of switching phenotypes can reduce the time to adaptation by orders of magnitude if the "fitness valley" caused by the deleterious mutation is deep enough. Our work has important implications for the emergence of antibiotic-resistant bacteria. In line with recent experimental findings we hypothesise that switching to a slower growing but less sensitive phenotype helps bacteria to develop resistance by exploring a larger set of beneficial mutations while avoiding deleterious ones.

q-bio.PE↗

arXiv2015

A simple non-equilibrium, statistical-physics toy model of thin-film growth

We present a simple non-equilibrium model of mass condensation with Lennard-Jones interactions between particles and the substrate. We show that when some number of particles is deposited onto the surface and the system is left to equilibrate, particles condense into an island if the density of particles becomes higher than some critical density. We illustrate this with numerically obtained phase diagrams for three-dimensional systems. We also solve a two-dimensional counterpart of this model analytically and show that not only the phase diagram but also the shape of the cross-sections of three-dimensional condensates qualitatively matches the two-dimensional predictions. Lastly, we show that when particles are being deposited with a constant rate, the system has two phases: a single condensate for low deposition rates, and multiple condensates for fast deposition. The behaviour of our model is thus similar to that of thin film growth processes, and in particular to Stranski-Krastanov growth.

cond-mat.stat-mech↗

arXiv2015

Spatial model predicts dispersal and cell turnover cause reduced intra-tumor heterogeneity

Most cancers in humans are large, measuring centimeters in diameter, composed of many billions of cells. An equivalent mass of normal cells would be highly heterogeneous as a result of the mutations that occur during each cell division. What is remarkable about cancers is their homogeneity - virtually every neoplastic cell within a large cancer contains the same core set of genetic alterations, with heterogeneity confined to mutations that have emerged after the last clonal expansions. How such clones expand within the spatially-constrained three dimensional architecture of a tumor, and come to dominate a large, pre-existing lesion, has never been explained. We here describe a model for tumor evolution that shows how short-range migration and cell turnover can account for rapid cell mixing inside the tumor. With it, we show that even a small selective advantage of a single cell within a large tumor allows the descendants of that cell to replace the precursor mass in a clinically relevant time frame. We also demonstrate that the same mechanisms can be responsible for the rapid onset of resistance to chemotherapy. Our model not only provides novel insights into spatial and temporal aspects of tumor growth but also suggests that targeting short range cellular migratory activity could have dramatic effects on tumor growth rates.

q-bio.PE↗

arXiv2014

Lower glycolysis carries a higher flux than any biochemically possible alternative

The universality of many pathways of core metabolism suggests a strong role for evolutionary selection, but it remains unclear whether existing pathways have been selected from a large or small set of biochemical possibilities. To address this question, we construct "in silico" all possible biochemically feasible alternatives to the trunk pathway of glycolysis and gluconeogenesis, one of the most highly conserved pathways in metabolism. We show that, even though a large number of alternative pathways exist, the alternatives carry lower flux than the real pathway under typical physiological conditions. Alternative pathways that could potentially carry higher flux often lead to infeasible intermediate metabolite concentrations. We also find that if physiological conditions were different, different pathways could outperform those found in nature. Our results demonstrate how the rules of biochemistry restrict the alternatives that are open to evolution, and suggest that the existing trunk pathway of glycolysis and gluconeogenesis represents a maximal flux solution.

q-bio.MN↗

arXiv2013

An exclusion process on a tree with constant aggregate hopping rate

We introduce a model of a totally asymmetric simple exclusion process (TASEP) on a tree network where the aggregate hopping rate is constant from level to level. With this choice for hopping rates the model shows the same phase diagram as the one-dimensional case. The potential applications of our model are in the area of distribution networks; where a single large source supplies material to a large number of small sinks via a hierarchical network. We show that mean field theory (MFT) for our model is identical to that of the one-dimensional TASEP and that this mean field theory is exact for the TASEP on a tree in the limit of large branching ratio, $b$(or equivalently large coordination number). We then present an exact solution for the two level tree (or star network) that allows the computation of any correlation function and confirm how mean field results are recovered as $b\rightarrow\infty$. As an example we compute the steady-state current as a function of branching ratio. We present simulation results that confirm these results and indicate that the convergence to MFT with large branching ratio is quite rapid.

cond-mat.stat-mech↗

arXiv2012

Mutational pathway determines whether drug gradients accelerate evolution of drug-resistant cells

Drug gradients are believed to play an important role in the evolution of bacteria resistant to antibiotics and tumors resistant to anti-cancer drugs. We use a statistical physics model to study the evolution of a population of malignant cells exposed to drug gradients, where drug resistance emerges via a mutational pathway involving multiple mutations. We show that a non-uniform drug distribution has the potential to accelerate the emergence of resistance when the mutational pathway involves a long sequence of mutants with increasing resistance, but if the pathway is short or crosses a fitness valley, the evolution of resistance may actually be slowed down by drug gradients. These predictions can be verified experimentally, and may help to improve strategies for combatting the emergence of resistance.

q-bio.PE↗