R-3 Repository :: Browsing by Author "Igoshin, Oleg A."

Browsing by Author "Igoshin, Oleg A."

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Accuracy of Substrate Selection by Enzymes Is Controlled by Kinetic Discrimination
(American Chemical Society, 2017) Banerjee, Kinshuk; Kolomeisky, Anatoly B.; Igoshin, Oleg A.; Bioengineering; Chemistry; Center for Theoretical Biological Physics
Enzymes have the remarkable ability to select the correct substrate from the pool of chemically similar molecules. The accuracy of such a selection is determined by differences in the free-energy profiles for the right and wrong reaction pathways. Here, we investigate which features of the free-energy landscape govern the variation and minimization of selectivity error. It is generally believed that minimal error is affected by both kinetic (activation barrier heights) and thermodynamic (binding stability) factors. In contrast, using first-passage theoretical analysis, we show that the steady-state selectivity error is determined only by the differences in transition-state energies between the pathways and is independent of the energies of the stable complexes. The results are illustrated for two common catalytic mechanisms: (i) the Michaelis–Menten scheme and (ii) an error-correcting kinetic proofreading scheme with tRNA selection and DNA replication as guiding biological examples. Our theoretical analysis therefore suggests that the selectivity mechanisms are always kinetically controlled.
An all-optical biological function generator and oscilloscope framework for characterizing gene circuit dynamics
(2014-04-21) Olson, Evan James; Tabor, Jeffrey J.; Igoshin, Oleg A.; Bennett, Matthew R.
Gene circuits are dynamical systems that regulate cellular behaviors, often using protein signals as inputs and outputs. Here we have developed an optogenetic ‘function generator’ for programming tailor-made gene expression signals in live E. coli. We designed light sequences with experimentally calibrated models of light-switchable two-component systems and used them to drive intracellular protein levels to match user-defined reference time-courses. This approach enabled generation of accelerated and linearized dynamics, sinusoidal oscillations with desired amplitudes and periods, and a complex waveform, all with unprecedented accuracy and precision. We also combined the function generator with a dual fluorescent protein reporter system, analogous to a dual-channel oscilloscope, to reveal that a synthetic repressible promoter linearly transforms repressor signals with an approximate 7-min delay. Our approach will enable a new generation of dynamic analyses of synthetic and natural gene circuits, providing an essential step toward the predictive design and rigorous understanding of biological systems.
Beyond microtubules: The cellular environment at the endoplasmic reticulum attracts proteins to the nucleus, enabling nuclear transport
(Elsevier, 2024) Chae, Seok Joo; Kim, Dae Wook; Igoshin, Oleg A.; Lee, Seunggyu; Kim, Jae Kyoung; Bioengineering; Biosciences; Chemistry; Center for Theoretical Biological Physics
All proteins are translated in the cytoplasm, yet many, including transcription factors, play vital roles in the nucleus. While previous research has concentrated on molecular motors for the transport of these proteins to the nucleus, recent observations reveal perinuclear accumulation even in the absence of an energy source, hinting at alternative mechanisms. Here, we propose that structural properties of the cellular environment, specifically the endoplasmic reticulum (ER), can promote molecular transport to the perinucleus without requiring additional energy expenditure. Specifically, physical interaction between proteins and the ER impedes their diffusion and leads to their accumulation near the nucleus. This result explains why larger proteins, more frequently interacting with the ER membrane, tend to accumulate at the perinucleus. Interestingly, such diffusion in a heterogeneous environment follows Chapman’s law rather than the popular Fick’s law. Our findings suggest a novel protein transport mechanism arising solely from characteristics of the intracellular environment.
Biophysics at the coffee shop: lessons learned working with George Oster
(American Society for Cell Biology, 2019) Igoshin, Oleg A.; Chen, Jing Han; Xing, Jianhua; Liu, Jian; Elston, Timothy C.; Grabe, Michael; Kim, Kenneth S.; Nirody, Jasmine A.; Rangamani, Padmini; Sun, Sean X.; Wang, Hongyun; Wolgemuth, Charles; Bioengineering; Biosciences; Chemistry
Over the past 50 years, the use of mathematical models, derived from physical reasoning, to describe molecular and cellular systems has evolved from an art of the few to a cornerstone of biological inquiry. George Oster stood out as a pioneer of this paradigm shift from descriptive to quantitative biology not only through his numerous research accomplishments, but also through the many students and postdocs he mentored over his long career. Those of us fortunate enough to have worked with George agree that his sharp intellect, physical intuition, and passion for scientific inquiry not only inspired us as scientists but also greatly influenced the way we conduct research. We would like to share a few important lessons we learned from George in honor of his memory and with the hope that they may inspire future generations of scientists.
Breakdown of Boltzmann-type models for the alignment of self-propelled rods
(Elsevier, 2024) Murphy, Patrick; Perepelitsa, Misha; Timofeyev, Ilya; Lieber-Kotz, Matan; Islas, Brandon; Igoshin, Oleg A.; Bioengineering; Biosciences; Chemistry; Center for Theoretical Biological Physics
Studies in the collective motility of organisms use a range of analytical approaches to formulate continuous kinetic models of collective dynamics from rules or equations describing agent interactions. However, the derivation of these kinetic models often relies on Boltzmann’s “molecular chaos” hypothesis, which assumes that correlations between individuals are short-lived. While this assumption is often the simplest way to derive tractable models, it is often not valid in practice due to the high levels of cooperation and self-organization present in biological systems. In this work, we illustrated this point by considering a general Boltzmann-type kinetic model for the alignment of self-propelled rods where rod reorientation occurs upon binary collisions. We examine the accuracy of the kinetic model by comparing numerical solutions of the continuous equations to an agent-based model that implements the underlying rules governing microscopic alignment. Even for the simplest case considered, our comparison demonstrates that the kinetic model fails to replicate the discrete dynamics due to the formation of rod clusters that violate statistical independence. Additionally, we show that introducing noise to limit cluster formation helps improve the agreement between the analytical model and agent simulations but does not restore the agreement completely. These results highlight the need to both develop and disseminate improved moment-closure methods for modeling biological and active matter systems.
Cell behaviors underlying Myxococcus xanthus aggregate dispersal
(American Society for Microbiology, 2023) Murphy, Patrick; Comstock, Jessica; Khan, Trosporsha; Zhang, Jiangguo; Welch, Roy; Igoshin, Oleg A.; Bioengineering; Biosciences; Chemistry; Center for Theoretical Biological Physics
The soil bacterium Myxococcus xanthus is a model organism with a set of diverse behaviors. These behaviors include the starvation-induced multicellular development program, in which cells move collectively to assemble multicellular aggregates. After initial aggregates have formed, some will disperse, with smaller aggregates having a higher chance of dispersal. Initial aggregation is driven by two changes in cell behavior: cells slow down inside of aggregates and bias their motion by reversing direction less frequently when moving toward aggregates. However, the cell behaviors that drive dispersal are unknown. Here, we use fluorescent microscopy to quantify changes in cell behavior after initial aggregates have formed. We observe that after initial aggregate formation, cells adjust the bias in reversal timings by initiating reversals more rapidly when approaching unstable aggregates. Using agent-based modeling, we then show dispersal is predominantly generated by this change in bias, which is strong enough to overcome slowdown inside aggregates. Notably, the change in reversal bias is correlated with the nearest aggregate size, connecting cellular activity to previously observed correlations between aggregate size and fate. To determine if this connection is consistent across strains, we analyze a second M. xanthus strain with reduced levels of dispersal. We find that far fewer cells near smaller aggregates modified their bias. This implies that aggregate dispersal is under genetic control, providing a foundation for further investigations into the role it plays in the life cycle of M. xanthus.
Chaperone-Mediated Stress Sensing in Mycobacterium tuberculosis Enables Fast Activation and Sustained Response
(American Society for Microbiology, 2021) Rao, Satyajit D.; Datta, Pratik; Gennaro, Maria Laura; Igoshin, Oleg A.; Bioengineering; Center for Theoretical Biological Physics
Dynamical properties of gene regulatory networks are tuned to ensure bacterial survival. In mycobacteria, the MprAB-σE network responds to the presence of stressors, such as surfactants that cause surface stress. Positive feedback loops in this network were previously predicted to cause hysteresis, i.e., different responses to identical stressor levels for prestressed and unstressed cells. Here, we show that hysteresis does not occur in nonpathogenic Mycobacterium smegmatis but does occur in Mycobacterium tuberculosis. However, the observed rapid temporal response in M. tuberculosis is inconsistent with the model predictions. To reconcile these observations, we implement a recently proposed mechanism for stress sensing, namely, the release of MprB from the inhibitory complex with the chaperone DnaK upon the stress exposure. Using modeling and parameter fitting, we demonstrate that this mechanism can accurately describe the experimental observations. Furthermore, we predict perturbations in DnaK expression that can strongly affect dynamical properties. Experiments with these perturbations agree with model predictions, confirming the role of DnaK in fast and sustained response. IMPORTANCE Gene regulatory networks controlling stress response in mycobacterial species have been linked to persistence switches that enable bacterial dormancy within a host. However, the mechanistic basis of switching and stress sensing is not fully understood. In this paper, combining quantitative experiments and mathematical modeling, we uncover how interactions between two master regulators of stress response—the MprAB two-component system (TCS) and the alternative sigma factor σE—shape the dynamical properties of the surface stress network. The result show hysteresis (history dependence) in the response of the pathogenic bacterium M. tuberculosis to surface stress and lack of hysteresis in nonpathogenic M. smegmatis. Furthermore, to resolve the apparent contradiction between the existence of hysteresis and fast activation of the response, we utilize a recently proposed role of chaperone DnaK in stress sensing. These result leads to a novel system-level understanding of bacterial stress response dynamics.
Chromosomal Arrangement of Phosphorelay Genes Couples Sporulation and DNA Replication
(Elsevier, 2015) Narula, Jatin; Kuchina, Anna; Lee, Dong-yeon; Fujita, Masaya; Süel, Gürol M.; Igoshin, Oleg A.; Bioengineering
Genes encoding proteins in a common regulatory network are frequently located close to one another on the chromosome to facilitate co-regulation or couple gene expression to growth rate. Contrasting with these observations, here, we demonstrate a functional role for the arrangement of Bacillus subtilis sporulation network genes on opposite sides of the chromosome. We show that the arrangement of two sporulation network genes, one located close to the origin and the other close to the terminus, leads to a transient gene dosage imbalance during chromosome replication. This imbalance is detected by the sporulation network to produce cell-cycle coordinated pulses of the sporulation master regulator Spo0A∼P. This pulsed response allows cells to decide between sporulation and continued vegetative growth during each cell cycle spent in starvation. The simplicity of this coordination mechanism suggests that it may be widely applicable in a variety of gene regulatory and stress-response settings.
Colony Expansion of Socially MotileﾠMyxococcus xanthusﾠCells Is Driven by Growth, Motility, and Exopolysaccharide Production
(Public Library of Science, 2016) Patra, Pintu; Kissoon, Kimberley; Cornejo, Isabel; Kaplan, Heidi B.; Igoshin, Oleg A.; Bioengineering
Myxococcus xanthus, a model organism for studies of multicellular behavior in bacteria, moves exclusively on solid surfaces using two distinct but coordinated motility mechanisms. One of these, social (S) motility is powered by the extension and retraction of type IV pili and requires the presence of exopolysaccharides (EPS) produced by neighboring cells. As a result, S motility requires close cell-to-cell proximity and isolated cells do not translocate. Previous studies measuring S motility by observing the colony expansion of cells deposited on agar have shown that the expansion rate increases with initial cell density, but the biophysical mechanisms involved remain largely unknown. To understand the dynamics of S motility-driven colony expansion, we developed a reaction-diffusion model describing the effects of cell density, EPS deposition and nutrient exposure on the expansion rate. Our results show that at steady state the population expands as a traveling wave with a speed determined by the interplay of cell motility and growth, a well-known characteristic of Fisher’s equation. The model explains the density-dependence of the colony expansion by demonstrating the presence of a lag phase–a transient period of very slow expansion with a duration dependent on the initial cell density. We propose that at a low initial density, more time is required for the cells to accumulate enough EPS to activate S-motility resulting in a longer lag period. Furthermore, our model makes the novel prediction that following the lag phase the population expands at a constant rate independent of the cell density. These predictions were confirmed by S motility experiments capturing long-term expansion dynamics.
Coupling between feedback loops in autoregulatory networks affects bistability range, open-loop gain and switching times
(IOP Publishing, 2012) Tiwari, Abhinav; Igoshin, Oleg A.; Bioengineering
Biochemical regulatory networks governing diverse cellular processes such as stress-response, differentiation and cell cycle often contain coupled feedback loops. We aim at understanding how features of feedback architecture, such as the number of loops, the sign of the loops and the type of their coupling, affect network dynamical performance. Specifically, we investigate how bistability range, maximum open-loop gain and switching times of a network with transcriptional positive feedback are affected by additive or multiplicative coupling with another positive- or negative-feedback loop. We show that a network's bistability range is positively correlated with its maximum open-loop gain and that both quantities depend on the sign of the feedback loops and the type of feedback coupling. Moreover, we find that the addition of positive feedback could decrease the bistability range if we control the basal level in the signal-response curves of the two systems. Furthermore, the addition of negative feedback has the capacity to increase the bistability range if its dissociation constant is much lower than that of the positive feedback. We also find that the addition of a positive feedback to a bistable network increases the robustness of its bistability range, whereas the addition of a negative feedback decreases it. Finally, we show that the switching time for a transition from a high to a low steady state increases with the effective fold change in gene regulation. In summary, we show that the effect of coupled feedback loops on the bistability range and switching times depends on the underlying mechanistic details.
The energy cost and optimal design of networks for biological discrimination
(The Royal Society, 2022) Yu, Qiwei; Kolomeisky, Anatoly B.; Igoshin, Oleg A.; Bioengineering; Biosciences; Chemical and Biomolecular Engineering; Chemistry; Physics and Astronomy; Center for Theoretical Biological Physics
Many biological processes discriminate between correct and incorrect substrates through the kinetic proofreading mechanism that enables lower error at the cost of higher energy dissipation. Elucidating physico-chemical constraints for global minimization of dissipation and error is important for understanding enzyme evolution. Here, we identify theoretically a fundamental error–cost bound that tightly constrains the performance of proofreading networks under any parameter variations preserving the rate discrimination between substrates. The bound is kinetically controlled, i.e. completely determined by the difference between the transition state energies on the underlying free energy landscape. The importance of the bound is analysed for three biological processes. DNA replication by T7 DNA polymerase is shown to be nearly optimized, i.e. its kinetic parameters place it in the immediate proximity of the error–cost bound. The isoleucyl-tRNA synthetase (IleRS) of E. coli also operates close to the bound, but further optimization is prevented by the need for reaction speed. In contrast, E. coli ribosome operates in a high-dissipation regime, potentially in order to speed up protein production. Together, these findings establish a fundamental error–dissipation relation in biological proofreading networks and provide a theoretical framework for studying error–dissipation trade-off in other systems with biological discrimination.
An Engineered B. subtilis Inducible Promoter System with over 10 000-Fold Dynamic Range
(American Chemical Society, 2019) Castillo-Hair, Sebastian M.; Fujita, Masaya; Igoshin, Oleg A.; Tabor, Jeffrey J.; Bioengineering; Biosciences; Center for Theoretical Biological Physics
Bacillus subtilis is the leading model Gram-positive bacterium, and a widely used chassis for industrial protein production. However, B. subtilis research is limited by a lack of inducible promoter systems with low leakiness and high dynamic range. Here, we engineer an inducible promoter system based on the T7 RNA Polymerase (T7 RNAP), the lactose repressor LacI, and the chimeric promoter PT7lac, integrated as a single copy in the B. subtilis genome. In the absence of IPTG, LacI strongly represses T7 RNAP and PT7lac and minimizes leakiness. Addition of IPTG derepresses PT7lac and simultaneously induces expression of T7RNAP, which results in very high output expression. Using green fluorescent and β-galactosidase reporter proteins, we estimate that this LacI-T7 system can regulate expression with a dynamic range of over 10 000, by far the largest reported for an inducible B. subtilis promoter system. Furthermore, LacI-T7 responds to similar IPTG concentrations and with similar kinetics as the widely used Phy-spank IPTG-inducible system, which we show has a dynamic range of at most 300 in a similar genetic context. Due to its superior performance, our LacI-T7 system should have broad applications in fundamental B. subtilis biology studies and biotechnology.
Enhanced sampling and applications in protein folding
(2013-07-24) Zhang, Cheng; Ma, Jianpeng; McNew, James A.; Igoshin, Oleg A.
We show that a single-copy tempering method is useful in protein-folding simulations of large scale and high accuracy (explicit solvent, atomic representation, and physics-based potential). The method uses a runtime estimate of the average potential energy from an integral identity to guide a random walk in the continuous temperature space. It was used for folding three mini-proteins, trpzip2 (PDB ID: 1LE1), trp-cage (1L2Y), and villin headpiece (1VII) within atomic accuracy. Further, using a modification of the method with a dihedral bias potential added on the roof temperature, we were able to fold four larger helical proteins: α3D (2A3D), α3W (1LQ7), Fap1-NRα (2KUB) and S-836 (2JUA). We also discuss how to optimally use simulation data through an integral identity. With the help of a general mean force formula, the identity makes better use of data collected in a molecular dynamics simulation and is more accurate and precise than the common histogram approach.
FlowCal: A User-Friendly, Open Source Software Tool for Automatically Converting Flow Cytometry Data from Arbitrary to Calibrated Units
(American Chemical Society, 2016) Castillo-Hair, Sebastian M.; Sexton, John T.; Landry, Brian P.; Olson, Evan J.; Igoshin, Oleg A.; Tabor, Jeffrey J.; Bioengineering; Biosciences; Center for Theoretical Biological Physics
Flow cytometry is widely used to measure gene expression and other molecular biological processes with single cell resolution via fluorescent probes. Flow cytometers output data in arbitrary units (a.u.) that vary with the probe, instrument, and settings. Arbitrary units can be converted to the calibrated unit molecules of equivalent fluorophore (MEF) using commercially available calibration particles. However, there is no convenient, nonproprietary tool available to perform this calibration. Consequently, most researchers report data in a.u., limiting interpretation. Here, we report a software tool named FlowCal to overcome current limitations. FlowCal can be run using an intuitive Microsoft Excel interface, or customizable Python scripts. The software accepts Flow Cytometry Standard (FCS) files as inputs and is compatible with different calibration particles, fluorescent probes, and cell types. Additionally, FlowCal automatically gates data, calculates common statistics, and produces publication quality plots. We validate FlowCal by calibrating a.u. measurements of E. coli expressing superfolder GFP (sfGFP) collected at 10 different detector sensitivity (gain) settings to a single MEF value. Additionally, we reduce day-to-day variability in replicate E. coli sfGFP expression measurements due to instrument drift by 33%, and calibrate S. cerevisiae Venus expression data to MEF units. Finally, we demonstrate a simple method for using FlowCal to calibrate fluorescence units across different cytometers. FlowCal should ease the quantitative analysis of flow cytometry data within and across laboratories and facilitate the adoption of standard fluorescence units in synthetic biology and beyond.
Graph-based modeling and evolutionary analysis of microbial metabolism
(2013-09-16) Zhou, Wanding; Ma, Jianpeng; Nakhleh, Luay K.; Igoshin, Oleg A.; Bennett, George N.
Microbial organisms are responsible for most of the metabolic innovations on Earth. Understanding microbial metabolism helps shed the light on questions that are central to biology, biomedicine, energy and the environment. Graph-based modeling is a powerful tool that has been used extensively for elucidating the organising principles of microbial metabolism and the underlying evolutionary forces that act upon it. Nevertheless, various graph-theoretic representations and techniques have been applied to metabolic networks, rendering the modeling aspect ad hoc and highlighting the conflicting conclusions based on the different representations. The contribution of this dissertation is two-fold. In the first half, I revisit the modeling aspect of metabolic networks, and present novel techniques for their representation and analysis. In particular, I explore the limitations of standard graphs representations, and the utility of the more appropriate model---hypergraphs---for capturing metabolic network properties. Further, I address the task of metabolic pathway inference and the necessity to account for chemical symmetries and alternative tracings in this crucial task. In the second part of the dissertation, I focus on two evolutionary questions. First, I investigate the evolutionary underpinnings of the formation of communities in metabolic networks---a phenomenon that has been reported in the literature and implicated in an organism's adaptation to its environment. I find that the metabolome size better explains the observed community structures. Second, I correlate evolution at the genome level with emergent properties at the metabolic network level. In particular, I quantify the various evolutionary events (e.g., gene duplication, loss, transfer, fusion, and fission) in a group of proteobacteria, and analyze their role in shaping the metabolic networks and determining the organismal fitness. As metabolism gains an increasingly prominent role in biomedical, energy, and environmental research, understanding how to model this process and how it came about during evolution become more crucial. My dissertation provides important insights in both directions.
How to train your microbe: methods for dynamically characterizing gene networks
(Elsevier, 2015) Castillo-Hair, Sebastian M.; Igoshin, Oleg A.; Tabor, Jeffrey J.; Bioengineering; Biosciences; Center for Theoretical Biological Physics
Gene networks regulate biological processes dynamically. However, researchers have largely relied upon static perturbations, such as growth media variations and gene knockouts, to elucidate gene network structure and function. Thus, much of the regulation on the path from DNA to phenotype remains poorly understood. Recent studies have utilized improved genetic tools, hardware, and computational control strategies to generate precise temporal perturbations outside and inside of live cells. These experiments have, in turn, provided new insights into the organizing principles of biology. Here, we introduce the major classes of dynamical perturbations that can be used to study gene networks, and discuss technologies available for creating them in a wide range of microbial pathways.
Independent control of mean and noise by convolution of gene expression distributions
(Springer Nature, 2021) Gerhardt, Karl P.; Rao, Satyajit D.; Olson, Evan J.; Igoshin, Oleg A.; Tabor, Jeffrey J.; Bioengineering; Biosciences; Chemistry; Center for Theoretical Biological Physics
Gene expression noise can reduce cellular fitness or facilitate processes such as alternative metabolism, antibiotic resistance, and differentiation. Unfortunately, efforts to study the impacts of noise have been hampered by a scaling relationship between noise and expression level from individual promoters. Here, we use theory to demonstrate that mean and noise can be controlled independently by expressing two copies of a gene from separate inducible promoters in the same cell. We engineer low and high noise inducible promoters to validate this result in Escherichia coli, and develop a model that predicts the experimental distributions. Finally, we use our method to reveal that the response of a promoter to a repressor is less sensitive with higher repressor noise and explain this result using a law from probability theory. Our approach can be applied to investigate the effects of noise on diverse biological pathways or program cellular heterogeneity for synthetic biology applications.
Interplay of Gene Expression Noise and Ultrasensitive Dynamics Affects Bacterial Operon Organization
(Public Library of Science, 2012) Ray, J. Christian J.; Igoshin, Oleg A.; Bioengineering
Bacterial chromosomes are organized into polycistronic cotranscribed operons, but the evolutionary pressures maintaining them are unclear. We hypothesized that operons alter gene expression noise characteristics, resulting in selection for or against maintaining operons depending on network architecture. Mathematical models for 6 functional classes of network modules showed that three classes exhibited decreased noise and 3 exhibited increased noise with same-operon cotranscription of interacting proteins. Noise reduction was often associated with a decreased chance of reaching an ultrasensitive threshold. Stochastic simulations of the lac operon demonstrated that the predicted effects of transcriptional coupling hold for a complex network module. We employed bioinformatic analysis to find overrepresentation of noiseminimizing operon organization compared with randomized controls. Among constitutively expressed physically interacting protein pairs, higher coupling frequencies appeared at lower expression levels, where noise effects are expected to be dominant. Our results thereby suggest an important role for gene expression noise, in many cases interacting with an ultrasensitive switch, in maintaining or selecting for operons in bacterial chromosomes.
Mean-field model for nematic alignment of self-propelled rods
(American Physical Society, 2022) Perepelitsa, Misha; Timofeyev, Ilya; Murphy, Patrick; Igoshin, Oleg A.; Bioengineering; Biosciences; Chemistry; Center for Theoretical Biological Physics
Self-propelled rods are a facet of the field of active matter relevant to many physical systems ranging in scale from shaken granular media and bacterial alignment to the flocking dynamics of animals. In this paper we develop a model for nematic alignment of self-propelled rods interacting through binary collisions. We avoid phenomenological descriptions of rod interaction in favor of rigorously using a set of microscopic-level rules. Under the assumption that each collision results in a small change to a rod's orientation, we derive the Fokker-Planck equation for the evolution of the kinetic density function. Using analytical and numerical methods, we study the emergence of the nematic order from a homogeneous, uniform steady state of the mean-field equation. We compare the level of orientational noise needed to destabilize this nematic order and compare our results to an existing phenomenological model that does not explicitly account for the physical collisions of rods. We show the presence of an additional geometric factor in our equations reflecting a reduced collision rate between nearly aligned rods that reduces the level of noise at which nematic order is destroyed, suggesting that alignment that depends on purely physical collisions is less robust.
Mechanism for Collective Cell Alignment inﾠ Myxococcus xanthus Bacteria
(Public Library of Science, 2015) Balagam, Rajesh; Igoshin, Oleg A.; Bioengineering; Center for Theoretical Biological Physics
Myxococcus xanthusﾠcells self-organize into aligned groups, clusters, at various stages of their lifecycle. Formation of these clusters is crucial for the complex dynamic multi-cellular behavior of these bacteria. However, the mechanism underlying the cell alignment and clustering is not fully understood. Motivated by studies of clustering in self-propelled rods, we hypothesized thatﾠM.ﾠxanthusﾠcells can align and form clusters through pure mechanical interactions among cells and between cells and substrate. We test this hypothesis using an agent-based simulation framework in which each agent is based on the biophysical model of an individualﾠM.ﾠxanthusﾠcell. We show that model agents, under realistic cell flexibility values, can align and form cell clusters but only when periodic reversals of cell directions are suppressed. However, by extending our model to introduce the observed ability of cells to deposit and follow slime trails, we show that effective trail-following leads to clusters in reversing cells. Furthermore, we conclude that mechanical cell alignment combined with slime-trail-following is sufficient to explain the distinct clustering behaviors observed for wild-type and non-reversingﾠM.ﾠxanthusﾠmutants in recent experiments. Our results are robust to variation in model parameters, match the experimentally observed trends and can be applied to understand surface motility patterns of other bacterial species.

Browsing by Author "Igoshin, Oleg A."

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