Wednesday, June 16 at 07:45pm (PDT)
Thursday, June 17 at 03:45am (BST)
Thursday, June 17 11:45am (KST)


Mechanisms Underlying Cell Polarization and Its Role in Cell Development

Organized by: Weitao Chen (University of California, Riverside, United States), Michael Trogdon (Salk Institute for Biological Studies, United States), Roya Zandi (University of California, Riverside, United States)

  • Cole Zmurchok (Vanderbilt University, United States)
    "Mechanosensing can enhance adaptation to maintain polarity of migrating cells"
  • Migratory cells are known to adapt to environments that contain wide-ranging levels of chemoattractant. While biochemical models of adaptation have been previously proposed, here we discuss a different mechanism based on mechanosensing, where the interaction between biochemical signaling and cell tension facilitates adaptation. In this talk, we develop and analyze a model of mechanochemical-based adaptation consisting of a mechanics-based physical model coupled with the wave-pinning reaction-diffusion model for Rac GTPase activity. We use Local Perturbation Analysis to predict how cells adapt signaling parameters via feedback from mechanics to maintain polarity in response to chemoattractant levels. To confirm this prediction, we simulate the mechanochemical model in moving cells, demonstrating how mechanosensing results in persistent cell polarity when cells are stimulated with wide-ranging levels of chemoattractant in silico. These results demonstrate how mechanosensing may help cells adapt to maintain polarity in variable environments.
  • Nan Hao (University of California, San Diego, United States)
    "Modeling the landscape of divergent aging in yeast"
  • Cellular aging is a complex process that involves many interwoven molecular processes. Studies in model organisms have identified many individual genes and factors that have profound effects on lifespan. However, how these genes and factors interact and function collectively to drive the aging process remains unclear. We investigated single-cell aging dynamics throughout the replicative lifespans of S. cerevisiae, and found that isogenic cells diverge towards two aging paths, with distinct phenotypic changes and death forms. We further identified specific molecular pathways driving each aging fate and revealed that these pathways interact and operate dynamically to enable an early-life switch that governs the aging fate decision and the progression towards death. Based on the identified molecular circuit, we developed a computational model that can simulate the landscape of divergent aging trajectories under various conditions. Guided by the model, we genetically engineered a new mode of aging with a dramatically extended lifespan. Our work uncovers the interconnected molecular pathways that drives the aging process and opens up the possibility of designing interventions that simultaneously target multiple network nodes, instead of single genes, to more effectively extend the healthspan.
  • Kevin Tsai (University of California, Riverside, United States)
    "Yeast budding: linking shape generation with biochemical-mechanical feedback"
  • How cells regulate behaviors such as expansion, division, and dynamical shape change is a fundamental question in biological science. The budding of Saccharomyces cerevisiae (yeast) is a prime example of asymmetrical cell growth where reproduction takes the form of a local surface protrusion. During this reproduction event, biochemically the budding process requires the recruitment of cell surface materials and the polarization of growth-associated proteins such as Cdc42. On the other hand, the mechanical properties of the cell wall potentially play a crucial role in bud formation. In this work we developed a novel 3D coarse-grained cell model incorporating probabilistic remeshing and cell growth via surface expansion. We computationally investigated different cell surface weakening and growth patterns and observed both proper and improper bud generation arising from different prescribed conditions. Furthermore, we coupled our mechanical model with a biochemical signaling model to probe the influence of the interplay between the mechanical properties and the biochemical properties on bud development.
  • Wing Cheong Lo (City University of Hong Kong, P. R. China)
    "Deterministic and stochastic analysis for the spontaneous emergence of cell polarity in budding yeast"
  • Spontaneous emergence of cell polarity intrinsically lies at the localization of signaling molecules on a particular region of cell membrane. Such a process necessarily contains a positive feedback loop to amplify the localized cluster. To describe the polarizing process and explore different feedback functions involved, deterministic and stochastic models with various regulations will be discussed in this talk.

Image Analysis and Machine Learning for Bio-Medical Applications

Organized by: Amit Roy-Chowdhury (University of California, Riverside), G. Venugopala Reddy (University of California, Riverside)
Note: this minisymposia has multiple sessions. The second session is MS16-DDMB.

  • B. S. Manjunath (University of California, Santa Barbara)
    "3D cell/nuclei segmentation and tracking using deep networks"
  • Accurate cell/nuclei segmentation and tracking play an important role in time-lapse 3D microscopy image analysis. Features of interest often depend on precise localization of 3D points on the boundary. Towards this, we present a deep network coupled with a conditional random field model for cell segmentation of 3D confocal membrane tagged image stacks, and a supervoxel based segmentation of 3D nuclei tagged images with few annotations. To track these segmented cells/nuclei, a computationally efficient algorithm is proposed that utilizes the relative cell/nuclei location while maintaining tracking accuracy. Detailed experimental results demonstrate the feasibility of the proposed methods on large 3d time-lapse imagery.
  • Michelle Digman (University of California, Irvine)
    "Quantifying Spatio-temporal dynamics and Metabolic Alterations of protein upon DNA Damage"
  • DNA damage signaling is critical for the maintenance of genome integrity and cell fate decision. Our genome is constantly under assault by various endogenous and environmental agents, exposure of UV rays and even routine DNA replication can cause obstruction of replication or transcription. The DNA damage response is a highly integrated signaling network has a set of mechanism that can detect the type of severity of DNA damage to initiate repair or apoptosis. This talk will describe methodologies used to investigate p53 protein activity and alteration of the metabolic pathway upon DNA damage. Here we present 2-Photon excitation laser microirradiation to induce different types of DNA damage, the Number and Molecular Brightness (N&B) method to map aggregation, and the phasor approach to FLIM to map metabolic changes upon DNA damage. Overall, our findings demonstrate that by multiplexing these techniques we have the ability to spatially and temporally quantify p53 activation and map p53‚Äôs influence in the metabolic pathway.
  • Cory Braker Scott (University of California, Irvine)
    "Morphological Analysis of Biological Images Using Spectral Graph Theory and Graph Neural Networks"
  • We present a method for learning ``spectrally descriptive'' edge weights for graphs. We generalize a previously known distance measure between graphs (Graph Diffusion Distance), thereby allowing it to be tuned to minimize an arbitrary loss function. Because all steps involved in calculating this modified GDD are differentiable, we demonstrate that it is possible for a small neural network model to learn edge weights to minimize loss. We demonstrate this by applying this metric to two groups of graphs derived from samples from two genotypes of Arabidopsis. GDD by itself cannot distinguish between these two categories of graphs. However, training edge weights and kernel parameters with contrastive loss produces a learned distance metric with large margins between graph categories. We demonstrate this by showing improved performance of a simple k-nearest-neighbors classifier on the learned distance matrix. We also demonstrate further applications of this technique.
  • Kevin Rodriguez (University of California, Riverside)
    "Interplay between layer specific chemical signals and mechanical properties maintain the structure and shape of the shoot apical meristem in Arabidopsis"
  • The shoot apical meristem (SAM) is continually derived from a population of stem cells located at the growing tip of the plants. These stem cells shed off populations of daughter cells both radially and basally. As the daughter cells are displaced, they undergo increased cell division rates and changes in gene expression critical to determine the SAM structure and shape. The cell division rates and changes in gene expression occur at a certain distance along the transcription factor-WUSCHEL and plant hormone cytokinin signaling domains. In addition, the cell division and gene expression are compromised in wuschel and cytokinin signaling mutants, suggesting these chemical signals regulate cell division rates. The changes in cell division rates and displacement of daughter cells affects the structure and shape of local cells and ultimately the SAM as a whole. Through a combination of transient gene expression, quantitative image analysis and biologically-calibrated computational model simulations we test the possible mechanisms regulating cell division to determine the SAM structure. Our analysis suggests that WUSCHEL, cytokinin, and mechanical stress regulate patterns of cell expansion and cell division plane orientation in a layer specific fashion to maintain the layered structure and shape of SAMs which are critical for stem cell homeostasis.

Collective Behavior and Social Evolution

Organized by: Daniel Cooney (University of Pennsylvania, USA) & Olivia Chu (Princeton University, USA)
Note: this minisymposia has multiple sessions. The second session is MS18-EVOP.

  • Heather Zinn Brooks (Harvey Mudd College)
    "Rounding out the corners: Smooth approximations for bounded-confidence models of opinion dynamics"
  • Vandana Venkateswaran (University of Illinois)
    "Modeling the interplay between life-history, sexual, and social traits"
  • Males and females have distinct life-history strategies that have co-evolved with diverse sex-specific traits. Previous studies have addressed how resource allocation towards single sex-specific traits impacts lifetime reproductive success (LRS). However, the tradeoffs between diverse sex-specific characteristics and their impact on LRS remain largely unassessed impeding our understanding of life-history evolution. We present a theoretical framework (informed by experimental data and evolutionary genetics) that explores the effects of multiple sex-specific traits and assessed how they influence LRS. From the individual sex-specific traits, we show the consequences at the population level (by evaluating adult sex ratios or ASR). We present how sex-specific resource allocation towards the assessed traits (parental investment, ornamentation and immunocompetence) resulted in a biased ASR. In general, this framework can be employed to understand the combined impact of diverse sex-specific traits on the LRS and the eventual population dynamics of particular model systems.
  • Taylor Kessinger (University of Pennsylvania)
    "Models of institution formation and breakdown under indirect reciprocity"
  • We live in a society. Societies require a high level of cooperation, and they cannot flourish unless defectors are punished. How do we ensure this? Indirect reciprocity models offer a potential solution: individuals may track the reputations of others, cooperating with those they consider good and punishing those they consider bad. But if individuals rely solely on their own private, personal assessments of others, disagreement about reputations makes it prohibitively difficult for cooperation to proliferate. We provide a mechanism for fomenting consensus about reputations: adherence to centralized institutions that track and broadcast reputational assessments. We show that, by tweaking the size of the institution and its tolerance to occasional antisocial behavior, cooperation can spread even under social norms that ordinarily are inhospitable to cooperation. We also show that adherence to institutional evaluation can spread in a population of private assessors and is robust against invasion. Finally, we consider mechanisms that may lead to the breakdown of institutional evaluation: ingroup/outgroup dynamics, corruption, competing institutions, and systemic bias. Our models underscore the importance of ensuring that institutions are fair and inclusive.
  • Sara Loo (University of New South Wales)
    "The evolution of learned behaviour and strategy: with applications to reproduction and disease emergence"
  • The question of why males invest more into competition than offspring care is an age old problem in evolutionary biology. On the one hand, paternal care could increase the fraction of offspring surviving to maturity. On the other hand, competition could increase the likelihood of more paternities and thus the relative number of offspring produced. We present a simple dynamic model to investigate the benefits of these two alternative fitness-enhancing pathways. Using this framework, we evaluate the sensitivity of equilibrium dynamics to changes in payoffs for male allocation to mating versus parenting. We then consider an application of the model that includes men’s competition for hunting reputations where big game supplies a benefit to all and find a frequency-dependent parameter region within which either strategy may outperform the other. Results demonstrate that allocation to competition gives males greater fitness than offspring care for a range of circumstances that are dependent on life-history parameters and, for the large-game hunting application, frequency dependent. We then consider an extension to the model that explores the effect of female life-history on male reproductive strategies and compare three different life histories to study conditions where paternal care may arise. This is driven by observations of paternal care in callitrichids.

Models of COVID-19 Vaccination, Non-Pharmaceutical Interventions, and Relaxation

Organized by: Jane Heffernan (York University, Canada), Miranda Teboh Ewungkem (Lehigh University, USA), Zhilan Feng (Purdue University, USA), John Glasser (Centres for Disease Control, USA)
Note: this minisymposia has multiple sessions. The second session is MS11-MEPI. The third session is MS20-MEPI.

  • Jeff Shaman (Columbia University, USA)
    "Overall Burden and Characteristics of COVID-19 in the US"
  • The COVID-19 pandemic disrupted health systems and economies throughout the world during 2020 and was particularly devastating for the United States, which experienced the highest numbers of reported cases and deaths during 2020. Many of epidemiological features responsible for observed rates of morbidity and mortality have not been comprehensively quantified. Here we use a data-driven model-inference approach to simulate the pandemic at county-scale in the United States during 2020 and estimate critical, time-varying epidemiological properties underpinning the dynamics of the virus, in particular the ascertainment rate, population susceptibility, community infection rates and the infection fatality rate. The results provide a county-resolved depiction of conditions until the end of 2020 when COVID-19 vaccine administration began. The implications for ongoing control of the virus are also investigated.
  • David Dick (York University, Canada)
    "A Model of COVID-19 Vaccination and Waning Immunity in Canada"
  • We have developed an age- and immunity-structured model of COVID-19 infection and vaccination. The model assumes rates of waning immunity from infection and vaccination. It also includes different non-pharmaceutical interventions, including work-from-home, school closure, social distancing and mask wearing. In this talk I will discuss different outcomes of a Canadian-informed COVID-19 vaccination program given different types of vaccines and rollout strategies. I will also discuss scenarios for relaxation and mitigation strategies needed to inhibit a Fall 2021 resurgence.
  • Toby Brett (University of Georgia, USA)
    "How mathematical modeling reveals the impracticality of COVID-19 herd immunity strategies"
  • Confronted with escalating COVID-19 outbreaks, countries at the leading edge of the pandemic have resorted to imposing drastic social distancing measures, with serious societal and economic repercussions. Establishing herd immunity in a population by allowing the epidemic to spread, while mitigating the negative health impacts of COVID-19, has presented a tantalizing resolution to the crisis. Using an ODE-based transmission model, parameterized to simulate SARS-CoV-2 transmission in the United Kingdom, we assessed the long-term prospects of achieving herd immunity without mass vaccination. We studied a range of different nonpharmaceutical intervention scenarios incorporating social distancing applied to differing age groups using a combination of numerical simulations and analytical techniques. Our modeling confirmed that suppression of SARS-CoV-2 transmission is possible with plausible levels of social distancing over a period of months, consistent with observed trends. Our findings show that achieving herd immunity without overwhelming hospital capacity leaves little room for error. Intervention levels must be carefully manipulated in an adaptive manner for an extended period, despite acute sensitivity to poorly quantified epidemiological factors. Specifically, we found that 1) social distancing must initially reduce the transmission rate to within a narrow range, 2) to compensate for susceptible depletion, the extent of social distancing must be adaptive over time in a precise yet unfeasible way, and 3) social distancing must be maintained for an extended period to ensure the healthcare system is not overwhelmed. Such fine-tuning of social distancing renders this strategy impractical.
  • Daniel Larremore (University of Colorado, USA)
    "Vaccine prioritization strategies with age, serostatus, and immunosenescence"
  • Limited initial supply of SARS-CoV-2 vaccine raised the question of how to prioritize available doses. One might reason, intuitively, that doses should be prioritized to directly protect those who are most vulnerable. Yet one might also intuitively argue that we should use vaccination as a means to break chains of transmission by prioritizing early doses to those most responsible for transmission, thereby indirectly protecting the vulnerable by reducing prevalence. Unfortunately, these two intuitive solutions make orthogonal recommendations. Here, we introduce a family of mixed discrete and differential equation models to resolve the tension between these recommendations, and compare five age-stratified vaccine prioritization strategies. By considering the demographics and contact patterns in the country of interest, transmission rates, vaccine properties, and the accumulated immunity in the population due to prior infection with SARS-CoV-2, we show how one can use differential equation models to quantify the tradeoffs between vaccine rollout strategies in a context-specific ways. We also highlight ways in which these models can help ameliorate existing pandemic-related inequities in access to healthcare and protection. In this talk, we will cover both the high-level results and recommendations, as well as vaccine-related modeling choices that complicate the more typical and standard 'SIR' type disease model.

Models and Computations for Studying Biofluid Applications

Organized by: Zhiliang Xu (Univeristy of Notre Dame, USA), Giordano Tierra (University of North Texas, USA), Shixin Xu (Duke Kunshan University)
Note: this minisymposia has multiple sessions. The second session is MS10-MMPB.

  • Rolf Ryham (Fordham University, USA)
    "Collective hydrodynamics of amphiphilic particles assembled as small unilamellar vesicles"
  • In this talk we study the collective hydrodynamic behavior of amphiphilic Janus particles assembled as small unilamellar vesicles (sUVs). The simulations use a hybrid approach that is shown to capture the formation of bilayers in a solvent (SIAM J Multiscale Model. Simul., vol 18, pp. 79-103). In this hybrid formulation, the non-local interactions between the coarse-grained lipid molecules are described by a hydrophobicity functional, giving rise to forces and torques (between lipid particles) that dictate the motion of both particles and the fluid flow in the viscous solvent. Both the hydrophobic and hydrodynamic interactions between the coarse-grained amphiphilic particles are formulated into integral equations, which allow for accurate and efficient numerical simulations in both two- and three-dimensions. We validate our hybrid coarse-grained model by reproducing various physical properties of a lipid bilayer membrane, and use this simulation tool to examine how a small unilamellar vesicle behaves under a planar shear flow, and investigate the collective dynamics of sUVs under a shear flow. Finally we also examine the possibility of membrane rupture by extreme flowing conditions.
  • Wenrui Hao (Penn State University, USA)
    "Computational models of cardiovascular disease"
  • In this talk, I will introduce several computational models of cardiovascular disease including both atherosclerosis and aortic aneurysm growth to quantitatively predict the long-term cardiovascular risk. These models integrate both the multi-layered structure of the arterial wall and the aneurysm pathophysiology together. The heterogeneous multiscale method is employed to tackle different time scales while the finite element method is adopted to the deformation of the hyperelastic arterial wall all the time. A three-dimensional realistic cardiovascular FSI problem with an aortic aneurysm growth based upon the patients' CT scan data is simulated to validate a medically reasonable long-term prediction.
  • Yiwei Wang (Illinois Institute of Technology, USA)
    "An energetic variational approach for wormlike micelle solutions: Coarse graining and dynamic stability"
  • Wormlike micelles are self-assemblies of polymer chains that can break and recombine reversibly. In this talk, we present a thermodynamically consistent two-species micro-macro model of wormlike micellar solutions by employing an energetic variational approach. The model incorporates a break- age and combination process of polymer chains into the classical micro-macro dumbbell model of polymeric fluids in a unified variational framework. The modeling approach can be applied to other reactive or active complex fluids. Different maximum entropy closure approximations to the new model will be discussed. By imposing a proper dissipation in the coarse-grained level, the closure model, obtained by “closure-then-variation”, preserves the thermo- dynamical structure of both mechanical and chemical parts of the original system. The same modeling approach can be applied to many active or reactive systems found in biology.
  • Giordano Tierra (University of North Texas, USA)
    "Energy-stable numerical schemes for fluid vesicles with internal nematic order"
  • Models of flows containing vesicles membranes with liquid crystalline phases have been widely studied in recent times due to its connection with biological applications. During the presentation I will present the main ideas to derive a new model to represent the interaction between flows and vesicle membranes with internal nematic order and preferential orientation of their molecules in the membrane. In fact, the dynamics of this system is determined by the dissipation of an energy that regulates the competition between different effects, through the kinetic, bending, elastic and anchoring energies. Moreover, I will introduce a new unconditionally energy-stable numerical scheme to approximate the model, and I will present several numerical results in order to show the well behavior of the proposed scheme and the dynamics of this type of vesicle membranes.