Biology subjects

Alber, M.

Publications and source records attributed to Alber, M..

11 recordsLinked to original sources

bioRxiv2026

Study of Principles Governing Epithelial Cell Clustering and Collective Motion In Vitro

In epithelial wounds, physically enlarged cells emerge along injury edges where they interact with regular-size cells during collective migration to repair tissue continuity. Although such large cells are often interpreted as migration leaders, recent observations suggest that regular-size cells can reciprocally influence them and that mixed-size cell clusters engage in distinct rotational motion before merging into confluent sheets. How cell size, polarity and adhesive coupling jointly control distinct collective migration modes remains unclear. Because many features of collective epithelial migration, including large and regular-size cell phenotypes, are conserved between in vivo and in vitro systems, here we developed a multi-scale computational model of interacting epithelial cells in two-dimensional culture with dynamic cell-substrate adhesion, cell-cell interactions, protrusion-based polarity, and contact-induced myosin redistribution as polarity regulator. We also explicitly modeled two functionally distinct cell states, featuring regular and large sizes respectively. Simulations showed that symmetric and asymmetric myosin redistribution at cell-cell junctions can produce stable cell contacts and persistent rotational motions by cell doublets. Intriguingly, in mixed-size cell clusters, straight translation can arise both from leader-like large cell and regular-size cell-mediated motion, whereas rotation emerges when large-cell-generated torque overcomes translation while cell-cell adhesion is maintained. Thus, collective migration mode depends on the balance among myosin-driven torque, regular-size cell-mediated translation, substrate coupling, and cell-cell adhesion. These modeling results suggest that collective epithelial migration can emerge in vitro from reciprocal biomechanical interactions between distinct cell states, rather than from leader-like cell behavior alone, and that such interactions can produce a predator-prey-like pursuit-escape mode of collective migration. Our model also provides a framework for investigating the biochemical and biomechanical regulation of collective cellular migration. It can be readily extended from in vitro to in vivo context and can incorporate the effects of substrate topology and soluble signaling factor-driven chemotaxis. Author summaryWhen epithelial cells repair a wound, they move as coordinated groups rather than as isolated individuals. Cells of different sizes may contribute in distinct but connected ways. We developed a computational model to examine how a large cell and neighboring regular-size cells move together. In the model, cells attach to the underlying surface and one another, form protrusions that set their direction, and redistribute the force-generating protein myosin after contact. We found that group motion depends on a balance among surface attachment, cell-cell adhesion, movement of regular-size cells toward the large cell, and myosin-driven turning of the large cell. Depending on this balance, a mixed-size cluster can travel along a nearly straight path or rotate persistently, exhibiting pursuit-and-escape-like interactions between the large cell and surrounding regular-size cells. Rotation occurs when the large cells turning effect outweighs the translational motion driven by regular-size cells, while cell-cell adhesion keeps the cluster together. Our results show that collective migration can emerge from reciprocal mechanical interactions between cells in different states, not only from a "leader" cell acting alone. The model also provides experimentally testable predictions for how cell size, adhesion, and internal myosin distribution shape cell cluster movement.

cell biology↗

bioRxiv2024

Capturing spatiotemporal variation in salt marsh belowground biomass, a key resilience metric, through geoinformatics

The Belowground Ecosystem Resiliency Model (BERM) is a geoinformatics tool that was developed to predict belowground biomass (BGB) of Spartina alterniflora in salt marshes based on remote sensing of aboveground characteristics and other readily available hydrologic, climatic, and physical data. We sought to characterize variation in S. alterniflora BGB over both temporal and spatial gradients through extensive marsh field observations in coastal Georgia, USA, to quantify their relationship with a suite of predictor variables, and to use these results to improve performance and expand the parameter space of BERM. We conducted pairwise comparisons of S. alterniflora growth metrics measured at nine sites over three to eight years and found that BGB grouped by site differed in 69% of comparisons, while only in 21% when grouped by year. This suggests that BGB varies more spatially than temporally. We used the BERM machine learning algorithms to evaluate how variables relating to biological, climatic, hydrologic, and physical attributes covaried with these BGB observations. Flooding frequency and intensity were most influential in predicting BGB, with predictor variables related to hydrology composing 61% of the total feature importance in the BERM framework. When we used this expanded calibration dataset and associated predictors to advance BERM, model error was reduced from a normalized root mean square error of 13.0% to 9.4% in comparison to the original BERM formulation. This reflects both an improvement in predictive performance and an expansion in conditions for potential model application. Finally, we used regression commonality analysis to show that model estimates reflected the spatiotemporal structure of BGB variation observed in field measurements. These results can help guide future data collection efforts to describe landscape-scale BGB trends. The advanced BERM is a robust tool that can characterize S. alterniflora productivity and resilience over broad spatial and temporal scales.

ecology↗

bioRxiv2024

Electrophysiological signatures of a developmental delay in a stem cell model of KCNQ2 developmental and epileptic encephalopathy

BackgroundKCNQ2, encoding KV7.2 ion channels, has emerged as one of the prominent genes causing early onset seizures with developmental delay (KCNQ2 developmental and epileptic encephalopathy; KCNQ2-DEE). KCNQ2 de novo loss-of-function (LOF) and associated neuronal hyperexcitability have been accepted as mechanisms contributing to seizures. To investigate the developmental impact of KCNQ2 LOF, we generated patient iPSC-derived models for two previously reported de novo variants, p.(Arg325Gly) and p.(Gly315Arg), linked to severe congenital DEE. MethodsFunctional investigation of the two variants was initially performed in Xenopus laevis oocyte system. Patient-derived iPSC lines were differentiated using NGN2- and embryoid body-based protocols yielding neurons roughly corresponding to mid- and mid-late gestational stages, respectively. KV7- mediated M-current, passive neuronal properties, action potential generation and spontaneous oscillatory network activities were analysed with whole-cell patch clamping. FindingsStudied KCNQ2 variants showed LOF with a dominant-negative effect in the heterologous system. Reduced M-currents in patient iPSC-derived neurons corroborated a LOF as the main pathomechanism. Interestingly, this led to the reduced neuronal firing of the early neurons and to a disruption of complex oscillatory activity, with significantly reduced duration and amplitude of these events in patient iPSC-derived neurons. InterpretationWe provide experimental evidence for changing roles of the M-current throughout development and place disease variant-mediated M-current reduction in the context of the neuronal maturation in the prenatal brain. Based on the reduced neuronal firing and disrupted oscillatory activity seen in patient iPSC-derived neurons, we propose that a delayed/impaired maturation of neuronal and network properties underlies KCNQ-DEE caused by LOF variants.

neuroscience↗

bioRxiv2024

Study of Impacts of Two Types of Cellular Aging on the Yeast Bud Morphogenesis

Understanding the mechanisms of cellular aging processes is crucial for attempting to extend organismal lifespan and for studying age-related degenerative diseases. Yeast cells divide through budding, providing a classical biological model for studying cellular aging. With their powerful genetics, relatively short lifespan and well-established signaling pathways also found in animals, yeast cells offer valuable insights into the aging process. Recent experiments suggested the existence of two aging modes in yeast characterized by nucleolar and mitochondrial declines, respectively. In this study, by analyzing experimental data it was shown that cells evolving into those two aging modes behave differently when they are young. While buds grow linearly in both modes, cells that consistently generate spherical buds throughout their lifespan demonstrate greater efficacy in controlling bud size and growth rate at young ages. A three-dimensional chemical-mechanical model was developed and used to suggest and test hypothesized mechanisms of bud morphogenesis during aging. Experimentally calibrated simulations showed that tubular bud shape in one aging mode could be generated by locally inserting new materials at the bud tip guided by the polarized Cdc42 signal during the early stage of budding. Furthermore, the aspect ratio of the tubular bud could be stabilized during the late stage, as observed in experiments, through a reduction on the new cell surface material insertion or an expansion of the polarization site. Thus model simulations suggest the maintenance of new cell surface material insertion or chemical signal polarization could be weakened due to cellular aging in yeast and other cell types. Significance StatementAging yeast exhibits two modes with different bud shapes. Experimental data analysis reveals that control of growth rate and bud size is more robust in cells aging in a spherical budding mode than in cells aging in a tubular budding mode. A computational model was developed and used in combination with experiments to test the hypothesized mechanisms underlying different types of budding in aging cells. Model simulations suggest that localized growth is sufficient to generate tubular budding and its aspect ratio can be stabilized through the regulation of chemical signals with an expanding polarization site or a decline on the new cell surface material insertion. Proposed mechanisms of morphological changes in aging yeast can be present in other cell types.

biophysics↗

bioRxiv2022

Balancing competing effects of tissue growth and cytoskeletal regulation during Drosophila wing disc development

Cytoskeletal structure and force generation within cells must be carefully regulated as the developing organ grows to reach a final size and shape. However, how the complex regulation of multiple features of tissue architecture is simultaneously coordinated remains poorly understood. Through iterations between experiments and novel computational multi-scale model simulations, we investigate the combined regulation of cytoskeletal regulation and proliferation in the growing wing imaginal disc. First, we found through experiments and calibrated model simulations that the local curvature and nuclear positioning of cells in the growing wing disc are defined by patterning of nested spatial domains of peaks in apical and basal contractility. Additionally, predictions from model simulations that incorporate a mechanistic description of interkinetic nuclear migration demonstrate that cell proliferation increases the local basal curvature of the wing disc. This is confirmed experimentally as basal curvature increases when growth and proliferation are increased through insulin signaling. In surprising contrast, we experimentally found that Decapentaplegic (Dpp), the key morphogen involved in both growth control and patterning of the anterior-posterior axis, counteracts increases in tissue bending due to cell proliferation via a combined mechanism that balances the competing impacts of both proliferation and patterning of cell contractility. Overall, the high conservation of these regulatory interactions suggests an important balancing mechanism through dual regulation of proliferation and cytoskeleton to meet the multiple criteria defining tissue morphogenesis.

developmental biology↗

bioRxiv2022

A Chemical-mechanical Coupled Model Predicts Roles of Spatial Distribution of Morphogen in Maintaining Tissue Growth

The exact mechanism controlling cell growth remains a grand challenge in developmental biology and regenerative medicine. The Drosophila wing disc tissue serves as an ideal biological model to study growth regulation due to similar features observed in other developmental systems. The mechanism of growth regulation in the wing disc remains a subject of intense debate. Most existing models to study tissue growth focus on either chemical signals or mechanical forces only. Here we developed a multiscale chemical-mechanical coupled model to test a growth regulation mechanism depending on the spatial range of the morphogen gradient. By comparing the spatial distribution of cell division and the overall shape of tissue obtained in the coupled model with experimental data, our results show that the distribution of the Dpp morphogen can be critical in resulting tissue size and shape. A larger tissue size with a faster growth rate and more symmetric shape can be achieved if the Dpp gradient spreads in a larger domain. Together with the absorbing boundary conditions, the feedback regulation that downregulates Dpp receptors on the cell membrane allows the further spread of the morphogen away from its source region, resulting in prolonged tissue growth at a more spatially homogeneous growth rate. Summary StatementA multiscale chemical-mechanical model was developed by coupling submodels representing dynamics of a morphogen gradient at the tissue level, intracellular chemical signals, and mechanical properties at the subcellular level. By applying this model to study the Drosophila wing disc, it was found that the spatial range of the morphogen gradient affected tissue growth in terms of the growth rate and the overall shape.

developmental biology↗

bioRxiv2020

Role of combined cell membrane and wall mechanicalproperties regulated by polarity signals in cell budding

The budding yeast, Saccharomyces cerevisiae, is a prime biological model to study mechanisms underlying asymmetric growth. Previous studies have shown that, prior to yeast bud emergence, polarization of a conserved small GTPase, Cdc42, must be established. Additionally, hydrolase changes the mechanical properties of the cell wall and plasma membrane with the periplasm between them (cell surface). However, how the surface mechanical properties in the emerging bud are different from the properties of the mother cell and their role in bud formation are not well understood. We hypothesize that the polarized chemical signal alters the local dimensionless ratio of stretching to bending stiffness of the cell surface of the emerging yeast bud. To test this hypothesis, a novel three-dimensional coarse-grained particle-based model has been developed which describes inhomogeneous mechanical properties of the cell surface. Model simulations suggest that regulation of the dimensionless ratio of stretching to bending stiffness of the cell surface is necessary to initiate bud formation. Furthermore, model simulations predict that bud shape depends strongly on the experimentally observed molecular distribution of the polarized signaling molecule Cdc42, while the neck shape of the emerging bud is strongly impacted by the properties of the chitin and septin ring. This 3D model of asymmetric cell growth can also be used for studying viral budding and other vegetative reproduction processes performed via budding.

biophysics↗

bioRxiv2020

Microbial community composition is affected by press, but not pulse, seawater intrusion

Tidal freshwater marshes (TFMs) are threatened by seawater intrusion, which can affect microbial communities and alter biogeochemical processes. Here, we report on Seawater Addition Long Term Experiment (SALTEx), a manipulative field experiment that investigated continuous (press) and episodic (pulse, 2 months/yr) inputs of brackish water on microbial communities in a TFM. After 2.5 years, microbial diversity was lower in press treatments than in control (untreated) plots. Sulfate reducers increased in response to both press and pulse treatments whereas methanogens did not differ among treatments. Our results suggest that microbial communities in TFMs are resilient to episodic events, but that continuous seawater intrusion may alter bacterial diversity in ways that affect ecosystem functioning. Scientific Significance StatementSea level rise and seawater intrusion threaten tidal freshwater marshes (TFMs) and the important ecosystem services they provide. Intrusion of seawater in TFMs can occur across a range of timescales, such as episodic events, like storm surges or drought, or continuous intrusion as a result of rising sea level. The effects of these stressors on TFM microbial communities are not well understood. Our multi-year field manipulation of brackish water inputs revealed that microbial communities were resilient to short-term pulses of salinity whereas continuous seawater intrusion led to reduced microbial diversity along with changes in relative abundance of key functional groups. Such alterations may diminish the ability of TFMs to sequester carbon and cycle nutrients.

ecology↗

bioRxiv2020

Machine Learning and Optimal Control of Enzyme Activities to Preserve Solvent Capacity in the Cell

Experimental measurements or computational model predictions of the post-translational regulation of enzymes needed in a metabolic pathway is a difficult problem. Consequently, regulation is mostly known only for well-studied reactions of central metabolism in various model organisms. In this study, we utilize two approaches to predict enzyme regulation policies and investigate the hypothesis that regulation is driven by the need to maintain the solvent capacity in the cell. The first predictive method uses a statistical thermodynamics and metabolic control theory framework while the second method is performed using a hybrid optimization-reinforcement learning approach. Efficient regulation schemes were learned from experimental data that either agree with theoretical calculations or result in a higher cell fitness using maximum useful work as a metric. Model predictions provide the following novel general principles: (1) the regulation itself causes the reactions to be much further from equilibrium instead of the common assumption that highly non-equilibrium reactions are the targets for regulation; (2) regulation is used to maintain the concentrations of both immediate and downstream product concentrations rather than to maintain a specific energy charge; and (3) the minimal regulation needed to maintain metabolite levels at physiological concentrations also results in the maximal energy production rate that can be obtained at physiological conditions. The resulting energy production rate is an emergent property of regulation which may be represented by a high value of the adenylate energy charge. In addition, the predictions demonstrate that the amount of regulation needed can be minimized if it is applied at the beginning or branch point of a pathway, in agreement with common notions. The approach is demonstrated for three pathways in the central metabolism of E. coli (gluconeogenesis, glycolysis-TCA and Pentose Phosphate-TCA) that each require different regulation schemes. It is shown quantitatively that hexokinase, glucose 6-phosphate dehydrogenase and glyceraldehyde phosphate dehydrogenase, all branch points of pathways, play the largest roles in regulating central metabolism.

systems biology↗

bioRxiv2020

Epithelial organ shape is generated by patterned actomyosin contractility and maintained by the extracellular matrix

Epithelial sheets play important roles in defining organ architecture during development. Here, we employed an iterative experimental and multi-scale computational modeling approach to decouple direct and indirect effects of actomyosin-generated forces, nuclear positioning, extracellular matrix (ECM), and cell-cell adhesion in shaping Drosophila wing imaginal discs, a powerful system for elucidating general principles of epithelial morphogenesis. Basally generated actomyosin forces are found to regulate apically biased nuclear positioning and are required for generating epithelial bending and cell elongation of the wing disc pouch. Surprisingly, however, short-term pharmacological inhibition of ROCK-driven actomyosin contractility does not impact the maintenance of tissue height or curved shape. In comparison, the relative tautness of the extracellular basement membrane is also patterned between regions of the wing disc. However, computational simulations show that patterning of ECM tautness provides only a minor contribution to modulating tissue shape. Instead, the buildup of a passive ECM pre-strain serves a principle role in shape maintenance. Surprisingly, this is independent from the maintenance of actomyosin contractility. Furthermore, localized apical adhesion between the two cell layers within the wing disc requires ROCK-driven actomyosin activity in the absence of the basal extracellular matrix. This apical adhesion between the two cell layers provides additional mechanical support to help maintain tissue integrity. The combined experimental and computational approach provides general insight into how the subcellular forces are generated and maintained within individual cells to induce tissue curvature and suggests an important design principle of epithelial organogenesis whereby forces generated by actomyosin followed by maintenance as pre-strain within the ECM are interconnected, but functionally separable. Significance statementA major outstanding question in developmental biology is the elucidation of general principles of organ shape formation and maintenance. Here, an iterative experimental and multi-scale computational modeling approach reveals that actomyosin contractility generates the bent profile along the anterior-posterior axis while tension within the ECM is sufficient and necessary for preserving the bent shape even in the absence of continued actomyosin contractility once the shape is generated. The mechanisms tested in this study define the necessary factors for establishing the shape of the wing disc, which later everts to form the adult wing during pupal development. The method can be extended to test novel mechanisms of other epithelial systems that consist of several cellular and ECM layers.

biophysics↗

bioRxiv2019

Stutter: a Transient Dynamic Instability Phase that is Strongly Associated with Catastrophe

Microtubules (MTs) are cytoskeletal fibers that undergo dynamic instability (DI), a remarkable process involving phases of growth and shortening separated by stochastic transitions called catastrophe and rescue. Dissecting dynamic instability mechanism(s) requires first characterizing and quantifying these dynamics, a subjective process that often ignores complexity in MT behavior. We present a Statistical Tool for Automated Dynamic Instability Analysis (STADIA), which identifies and quantifies not only growth and shortening, but also a category of intermediate behaviors that we term stutters. During stutters, the rate of MT length change tends to be smaller in magnitude than during typical growth or shortening phases. Quantifying stutters and other behaviors with STADIA demonstrates that stutters precede most catastrophes in our dimer-scale MT simulations and in vitro experiments, suggesting that stutters are mechanistically involved in catastrophes. Related to this idea, we show that the anti-catastrophe factor CLASP2{gamma} works by promoting the return of stuttering MTs to growth. STADIA enables more comprehensive and data-driven analysis of MT dynamics compared to previous methods. The treatment of stutters as distinct and quantifiable DI behaviors provides new opportunities for analyzing mechanisms of MT dynamics and their regulation by binding proteins.

cell biology↗