Biology subjects

Mugler, A.

Publications and source records attributed to Mugler, A..

15 recordsLinked to original sources

bioRxiv2026

Colony morphogenesis regulates sporulation dynamics in bacterial biofilms

In multicellular systems, organized phenotypic heterogeneity emerges from the interplay of processes spanning scales from molecular to population-level. Using Bacillus subtilis, we investigated feedback between the collective process of colony expansion and the distribution of spore development among individual cells, a process triggered by starvation. Biofilms are commonly studied using a strain with inhibited sporulation. Intact regulation yielded high-frequency sporulation early in biofilm growth. Biofilm composition was organized by a wave of sporulation driving biofilms toward dormancy from within. However, expansion was also maintained by non-sporulating cells in a narrow front at the external edge. Along with mathematical modeling, we also used mutants with altered biofilm morphogenesis to probe the relationship between colony expansion and sporulation. Sporulation dynamics were patterned by radial expansion, but the faster biofilms spread, the greater the separation of growth and sporulation distributions. We demonstrate essential interplay between cell behavior and the physics of collective expansion that organizes differentiation among cells.

microbiology↗

bioRxiv2025

Decay in transcriptional information flow is a hallmark of cellular aging

Aging is marked by the progressive loss of cellular function, yet the organizing principles underlying this decline remain unclear. Although molecular fingerprints of aging are diverse, many converge on disruption of the interrelated and overlapping communication networks that coordinate molecular activity. Here, we apply information theory to quantify age-related corruption in gene regulation by modeling regulatory interactions between transcription factors (TFs) and their target genes (TGs) as a multi-input multi-output communication channel. Using an analytically tractable probabilistic model and single-cell RNA-sequencing data from multiple tissues, we find that the mutual information (a measure of information transfer) between TFs and TGs declines with age across all ten tissues analyzed, establishing loss of regulatory information transmission as a hallmark of aging. Structural analysis of the regulatory network reveals that aging degrades communication primarily through input distribution mismatch, reflecting a loss of coordinated TF activity, rather than channel corruption, or the inability of TFs to reliably activate or inhibit their targets. This mismatch is caused by increased network centralization and loss of stabilizing feedback motifs, leading to reduced robustness to random perturbations. Notably, in silico upregulation of a small set of TFs restores youthful information transfer and gene expression levels, suggesting that targeted reinforcement of key regulatory nodes may rejuvenate aged networks.

systems biology↗

bioRxiv2025

Bacterial population dynamics during colonization of solid tumors

Bacterial colonization of tumors is widespread, yet the dynamics during colonization remain underexplored. Here we discover strong variability in the sizes of intratumor bacterial clones and use this variability to infer the mechanisms of colonization. We monitored bacterial population dynamics in murine tumors after introducing millions of genetically barcoded Escherichia coli cells. Results from intravenous injection revealed that roughly a hundred bacteria seeded a tumor and that colonizers underwent rapid, yet highly nonuniform growth. Within a day, bacteria reached a steady-state and then sustained load and clone diversity. Intratumor injections, circumventing infection bottlenecks, revealed that the nonuniformity persists and that the sizes of bacterial progenies followed a scale-free distribution. Theory suggested that our observations are compatible with a growth model constrained by a local niche load, global resource competition, and noise. Our work provides the first dynamical model of tumor colonization and may allow distinguishing genuine tumor microbiomes from contamination.

systems biology↗

bioRxiv2024

Hyperballistic intercellular signaling through growth assisted positive feedback

Intercellular signaling in bacteria is often mediated by small molecules secreted by cells. These small molecules disperse via diffusion which limits the speed and spatial extent of information transfer in spatially extended systems. Theory shows that a secondary signal and feedback circuits can speed up the flow of information and allow it to travel further. Here, we construct and test several synthetic circuits in Escherichia coli to determine to what extent a secondary signal and feedback can improve signal propagation in bacterial systems. We find that positive feedback-regulated secondary signals propagate further and faster than diffusion-limited signals. Additionally, the speed at which the signal propagates can accelerate in time, provided the density of the cells within the system increases. These findings provide the foundation for creating fast, long-range signal propagation circuits in spatially extended bacterial systems.

synthetic biology↗

bioRxiv2023

Optimal antimicrobial response to a changing microbial background at a mucus interface

Complex lifeforms host microbiota, microbes that live synergistically with their host. Accordingly, hosts have mechanisms to defend against and tolerate the microbiota. The intestinal mucus, where these systems collide, plays a pivotal role in managing this relationship, yet lacks an integrative theoretical framework. We propose a minimal model to elucidate dynamics at this interface, focusing on the ileums mucus defense. The model considers the effect of delay in host antimicrobial peptide secretion and how the host can use two different signals, from the bulk microbiota and from segmented filamentous bacteria (SFB), assuming that the SFB anticipate the bulk microbiota. We propose a theory whereby the host can optimize defense by minimizing antimicrobial peptide production and controlling bacterial exposure. Integrating two recent experiments, we show host dynamics are consistent with sensing both bulk and SFB, supporting our optimal defense hypothesis. Therefore, we propose that similar mechanisms could prove advantageous to other species and applicable beyond the ileums mucus barrier.

biophysics↗

bioRxiv2023

Signaling in microbial communities with open boundaries

Microbial communities such as swarms or biofilms often form at the interfaces of solid substrates and open fluid flows. At the same time, in laboratory environments these communities are commonly studied using microfluidic devices with media flows and open boundaries. Extracellular signaling within these communities is therefore subject to different constraints than signaling within classic, closed-boundary systems such as developing embryos or tissues, yet is understudied by comparison. Here, we use mathematical modeling to show how advective-diffusive boundary flows and population geometry impact cell-cell signaling in monolayer microbial communities. We reveal conditions where the intercellular signaling lengthscale depends solely on the population geometry and not on diffusion or degradation, as commonly expected. We further demonstrate that diffusive coupling with the boundary flow can produce signal gradients within an isogenic population, even when there is no flow within the population. We use our theory to provide new insights into the signaling mechanisms of published experimental results, and we make several experimentally verifiable predictions. Our research highlights the importance of carefully evaluating boundary dynamics and environmental geometry when modeling microbial cell-cell signaling and informs the study of cell behaviors in both natural and synthetic systems. O_TEXTBOXSIGNIFICANCEMicrobial communities in natural environments and microfluidic devices are often exposed to open boundaries and flows, but models used to characterize diffusive signaling in such systems often ignore how device geometry, boundary conditions, and media flow influence signaling behavior. We demonstrate how the effective signaling capacity of these communities can be shaped by population geometry and advective-diffusive boundary flow in quasi-2D environments. Our approach provides a general framework to understand and control advection-reaction-diffusion systems--and their interactions with cellular signaling networks--in both natural and synthetic environments. C_TEXTBOX

biophysics↗

bioRxiv2022

Precise temporal control of neuroblast migration through combined regulation and feedback of a Wnt receptor

Many developmental processes depend on precise temporal control of gene expression. We have previously established a theoretical framework for regulatory strategies that can govern such high temporal precision, but experimental validation of these predictions was still lacking. Here, we use the time-dependent expression of a Wnt receptor that controls neuroblast migration in C. elegans as a tractable system to study a robust, cell-intrinsic timing mechanism in vivo. Single molecule mRNA quantification showed that the expression of the receptor increases non-linearly, a dynamic that is predicted to enhance timing precision over an unregulated, linear increase in timekeeper abundance. We show that this upregulation depends on transcriptional activation, providing in vivo evidence for a model in which the timing of receptor expression is regulated through an accumulating activator that triggers expression when a specific threshold is reached. This timing mechanism acts across a cell division that occurs in the neuroblast lineage, and is influenced by the asymmetry of the division. Finally, we show that positive feedback of receptor expression through the canonical Wnt pathway enhances temporal precision. We conclude that robust cell-intrinsic timing can be achieved by combining regulation and feedback of the timekeeper gene.

developmental biology↗

bioRxiv2022

The fidelity of genetic information transfer with aging segregates according to biological processes

Maintenance of organismal function requires tightly regulated biomolecular communication. However, with aging, communication deteriorates, thereby disrupting effective information flow. Using information theory applied to skeletal muscle single cell RNA-seq data from young, middle-aged, and aged animals, we quantified the loss of communication efficiency over time. We considered communication channels between transcription factors (TF; input message) and corresponding target genes (TG; output message). Mutual information (MI), defined as the information effectively transmitted between TFs and TGs, declined with age. This decline was attributed to escalating biological noise and loss of precision with which TFs regulate TGs (i.e., channel capacity). When we ranked TF:TG pairs by MI, pairs associated with fatty acid oxidation displayed the greatest loss of communication with aging, while the system preserved communication between pairs related to RNA synthesis. These data suggest ineffective communication with aging against a backdrop of resource reallocation to support essential cellular functions.

bioengineering↗

bioRxiv2022

Computational model of fractal interface formation in bacterial biofilms

Bacteria benefit from cellular heterogeneity: cells differentiate into diverse gene expression states. As colonies grow, cellular phenotypes arrange into spatial patterns. To uncover the functional role of these emergent patterns, we must understand how they arise from cellular growth and mechanical interactions. Here we present a simple, agent-based model to predict patterns of motile and extracellular matrix-producing cells in biofilms of Bacillus subtilis. By incorporating phenotypic inheritance, mechanical interactions, and peripheral motile cell dispersal, our model predicts the emergence of a pattern: matrix cells surround a fractal-like interior motile population. We find that, while some properties of the motile-matrix interface depend on initial conditions, the motile distribution at large radii depends solely on the models growth mechanism. The phenotypic interface exhibits a fractal dimension that increases as biofilms grow but reaches a maximum as the peripheral layer of matrix cells exceeds the capacity of the inner cells to push it out of the way. By varying parameters, we find correlations between the interface fractal dimension and expansion of motile cells. We validate findings using experiments on B. subtilis biofilms in microfluidics. Our model demonstrates the emergence of colony-level phenotypes from single cell-level interactions and cells modifying their own environment.

biophysics↗

bioRxiv2022

Cells function as a ternary logic gate to decide migration direction under integrated chemical and fluidic cues

Cells sense various environmental cues and process intracellular signals to decide their migration direction in many physiological and pathological processes. Although several signaling molecules have been identified in these directed migrations, it still remains elusive how cells decipher multiple cues, specifically chemical and fluidic cues. Here, we investigated the cellular signal processing machinery by reverse-engineering directed cell migration under integrated chemical and fluidic cues. We exposed controlled chemical and fluidic cues to cells using a microfluidic platform and analyzed the extracellular coupling of the cues with respect to the cellular detection limit. Then, the cells migratory behavior was reverse-engineered to build the cells intrinsic signal processing system as a logic gate. Our primary finding is that the cellular signal processing machinery functions as a ternary logic gate to decipher integrated chemical and fluidic cues. The proposed framework of the ternary logic gate suggests a systematic approach to understand how cells decode multiple cues to make decisions in migration.

biophysics↗

bioRxiv2020

Capacity to multitask limits cellular chemotaxis

Chemotaxis is ubiquitous in many biological processes, but it still remains elusive how cells sense and decipher multiple chemical cues. In this study, we postulate a hypothesis that the chemotactic performance of cells under complex cues is regulated by the signal processing capacity of the cellular sensory machinery. The underlying rationale is that cells in vivo should be able to sense and process multiple chemical cues, whose magnitude and compositions are entangled, to determine their migration direction. We experimentally show that the combination of TGF-{beta} and EGF suppresses the chemotactic performance of cancer cells using independent receptors to sense the two cues. Based on this observation, we develop a biophysical framework suggesting that the antagonism is caused by the saturation of the signal processing capacity, but not by the mutual repression. Our framework suggests the significance of the signal processing capacity in the cellular sensory machinery.

biophysics↗

bioRxiv2020

Sensitivity to perturbations of a cell migration under temporal regulation

Few studies have measured the robustness to perturbations of the final position of a long-range migrating cell. In the nematode Caenorhabditis elegans, the QR neuroblast migrates anteriorly in the young larva, while undergoing three rounds of division. The daughters of QR.pa stop their migration at an anterior body position and acquire a neuronal fate. Previous studies showed that the migration stops upon expression of the Wnt receptor MIG-1, which surprisingly is not induced by positional cues but by a timing mechanism (Mentink et al. 2014). Given this temporal regulation, we wondered 1) how precise QR.pax positioning is when confronted with various challenges, such as stochastic noise, environment or body size variation and 2) whether QR.pax position varies among C. elegans wild isolates. We find that the variance of QR.pax final position is similar to that of other long-range migrating neurons. Its mean position undergoes a slight posterior shift at higher temperature, while its variance is greatly increased following sustained starvation at hatching. We manipulated body size using mutants and tetraploid animals. As expected from the temporal mechanism, smaller mutants display anteriorly shifted QR.pax cells, while longer mutants and tetraploids display posteriorly shifted QR.pax cells. Using a mathematical model, we show however that body size variation is partially compensated. We find that cell speed is indeed altered in body size mutants. Finally, we could detect highly significant variation among C. elegans wild isolates. Overall, this study reveals that the final cell position of QR.pax shows some degree of sensitivity to external perturbations and natural genetic variation.

developmental biology↗

bioRxiv2020

Intermediate adhesion maximizes fluidity and migration velocity of multicellular clusters

Collections of cells exhibit coherent migration during morphogenesis, cancer metastasis, and wound healing. In many cases, bigger clusters split, smaller sub-clusters collide and reassemble, and gaps continually emerge. The connections between cell-level adhesion and cluster-level dynamics, as well as the resulting consequences for cluster properties such as migration velocity, remain poorly understood. Here we investigate collective migration of one- and two-dimensional cell clusters that collectively track chemical gradients using a mechanism based on contact inhibition of locomotion. We develop both a minimal description based on the lattice gas model of statistical physics, and a more realistic framework based on the cellular Potts model which captures cell shape changes and cluster rearrangement. In both cases, we find that cells have an optimal adhesion strength that maximizes cluster migration speed. The optimum negotiates a tradeoff between maintaining cell-cell contact and maintaining cluster fluidity, and we identify maximal variability in the cluster aspect ratio as a revealing signature. Our results suggest a collective benefit for intermediate cell-cell adhesion. SIGNIFICANCECells have been observed to migrate faster and more efficiently in clusters than as individuals. We conjecture that adhesion among cells and with the extracellular environment plays an important role in achieving higher-speed for the entire cluster. We carry out our analyses analytically and computationally, by employing a simplistic one-dimensional model and a realistic two-dimensional model which capture the essential features of multicellular migration. Our study demonstrates that an optimal cell-cell adhesion, which corresponds to maximal cellular rearrangement and loose packing, leads to a higher migration velocity for a multicellular cluster, acting as a crucial factor in effective movement of a collection of cells in a coordinated and directed fashion.

biophysics↗

bioRxiv2020

Diffusion vs. direct transport in the precision of morphogen readout

Morphogen profiles allow cells to determine their position within a developing organism, but not all morphogen profiles form by the same mechanism. Here we derive fundamental limits to the precision of morphogen concentration sensing for two canonical mechanisms: the diffusion of morphogen through extracellular space and the direct transport of morphogen from source cell to target cell, e.g., via cytonemes. We find that direct transport establishes a morphogen profile without adding noise in the process. Despite this advantage, we find that for suffciently large values of profile length, the diffusion mechanism is many times more precise due to a higher refresh rate of morphogen molecules. We predict a profile lengthscale below which direct transport is more precise, and above which diffusion is more precise. This prediction is supported by data from a wide variety of morphogens in developing organisms.

biophysics↗

bioRxiv2017

Modeling of cytometry data in logarithmic space: when is a bimodal distribution not bimodal?

Recent efforts in systems immunology lead researchers to build quantitative models of cell activation and differentiation. One goal is to account for the distributions of proteins from single-cell measurements by flow cytometry or mass cytometry as a readout of biological regulation. In that context, large cell-to-cell variability is often observed in biological quantities. We show here that these readouts, viewed in logarithmic scale may result in two easily-distinguishable modes, while the underlying distribution (in linear scale) is unimodal. We introduce a simple mathematical test to highlight this mismatch. We then dissect the flow of influence of cell-to-cell variability proposing a graphical model which motivates higher-dimensional analysis of the data. Finally we show how acquiring additional biological information can be used to reduce uncertainty introduced by cell-to-cell variability, helping to clarify whether the data is uni- or bimodal. This communication has cautionary implications for manual and automatic gating strategies, as well as clustering and modeling of single-cell measurements.

immunology↗