Quantitative Biology Seminars

Current Seminar

Monday, January 14, 2019: 335 West Hall, 12:00p - 1:00p

PresenterWylie Stroberg, PhD., Department of Molecular and Integrative Physiology, University of Michigan

Discussion Stress sensing in the endoplasmic reticulum

Abstract Within the endoplasmic reticulum (ER) of eukaryotic cells a complex system of chaperones and foldases work in concert to correctly fold nascent proteins and aid their progress along the secretory pathway. Should this process be upset, either through increased peptide translation or changes to the chemical environment within the ER, unfolded proteins accumulate, aggregate and misfold. This state of disrupted proteostasis, known as ER stress, triggers a multifaceted transcriptional response called the unfolded protein response (UPR) that seeks to restore proteostasis. While the UPR has been extensively studied due to the important role it plays in protein misfolding diseases, cancer and aging, a critical and still-poorly-understood aspect of the UPR is the mechanism through which ER stress is detected and quantified by the cell. This talk will discuss recent theoretical work to rationalize the observed stress sensing network in the ER. Specifically, by approaching the problem from both optimal-control and information-theoretic standpoints, we show the advantage of measuring stress by “counting” both unfolded proteins and unutilized chaperones as opposed to either individually. This work serves as a starting point for a more quantitative understanding of how cells regulate ER stress and the protein secretory pathway.

Past Seminars


Monday, December 10, 2018: 335 West Hall, 12:00p - 1:00p

PresenterJeff Dunworth, PhD., Department of Mathematics, University of Michigan

Discussion Disruption of excitation/inhibition balance in cortical neuronal networks

Abstract Cortical neuron spiking activity is broadly classified as temporally irregular and asynchronous. Model networks with a balance between large recurrent excitation and inhibition capture these two features, and are a popular framework relating circuit structure and network dynamics, though are traditionally restricted to a single attractor. We analyze paired whole cell voltage-clamp recordings from spontaneously active neurons in mouse auditory cortex slices (Graupner & Reyes, 2013) showing a network where correlated excitation and inhibition effectively cancel, except for intermittent periods when the network shows a macroscopic synchronous event. These data suggest that while the core mechanics of balanced activity are important, we require new theories capturing these brief but powerful periods when balance fails. Recent work by Mongillo et.al. (2012) showed that balanced networks with short-term synaptic plasticity can depart from strict linear dynamics. We extend this model by incorporating finite network size, introducing strong nonlinearities in the firing rate dynamics and allowing finite size induced noise to elicit large scale, yet infrequent, synchronous events. We identify core requirements for system size and network plasticity to capture the transient synchronous activity observed in our experimental data set. Our model properly mediates between the asynchrony of balanced activity and the tendency for strong recurrence to promote macroscopic population dynamics.

Monday, November 12, 2018: 335 West Hall, 12:00p - 1:00p

PresenterL. M. Sander, Physics & Complex Systems, University of Michigan

Discussion Durotaxis, Random Walkers, and the Electric Telegraph

Abstract Motile biological cells in tissue often display the phenomenon of durotaxis, i.e. they tend to move towards stiffer parts of substrate tissue. The mechanism for this behavior is not understood. We consider simplified models for durotaxis based on the classic persistent random walker scheme. Even a one- dimensional model of this type sheds interesting light on the classes of behavior cells might exhibit. Our results strongly indicate that cells must be able to sense the gradient of stiffness in order to show the effects observed in experiment. This is in contrast to the claims in recent publications that it is sufficient for cells to be more persistent in their motion on stiff substrates to show durotaxis: i.e., if would be enough to sense the value of the stiffness.

Monday, October 22, 2018: 335 West Hall, 12:00p - 1:00p

PresenterPadmini Rangamani, Mechanical and Aerospace Engineering, UC San Diego

Discussion Geometric Principles Of Spatio-Temporal Dynamics Of Second Messengers In Dendritic Spines

Abstract The ability of the brain to encode and store information depends on the plastic nature of the individual synapses. The increase and decrease in synaptic strength, mediated through the structural plasticity of the spine, are important for learning, memory, and cognitive function. Dendritic spines are small structures that contain the synapse. They come in a variety of shapes (stubby, thin, or mushroom-shaped) and a wide range of sizes that protrude from the dendrite. These spines are the regions where the postsynaptic biochemical machinery responds to the neurotransmitters. Spines are dynamic structures, changing in size, shape, and number during development and aging. While spines and synapses have inspired neuromorphic engineering, the biophysical events underlying synaptic and structural plasticity remain poorly understood.

Our current focus is on understanding the biophysical events underlying structural plasticity. I will discuss two recent efforts from my group — first, a systems biology approach to construct a mathematical model of biochemical signaling and actin-mediated transient spine expansion in response to calcium influx caused by NMDA receptor activation and second, a series of spatial models to study the role of spine geometry and organelle location within the spine for calcium and cyclic AMP signaling. I will conclude with some new efforts in using reconstructions from electron microscopy to inform computational domains. I will conclude with how geometry and mechanics plays an important role in our understanding of fundamental biological phenomena and some general ideas on bio-inspired engineering.

Monday, September 10, 2018: 335 West Hall, 12:00p - 1:00p

PresenterFarzan Beroz, Department of Physics and Michigan Life Science Fellows Program, University of Michigan

Discussion Verticalization of Bacterial Biofilms

Abstract Biofilms are communities of bacteria adhered to surfaces. Recently, biofilms of rod-shaped bacteria were observed at single-cell resolution and shown to develop from a disordered, two-dimensional layer of founder cells into a three-dimensional structure with a vertically-aligned core. Here, we elucidate the physical mechanism underpinning this transition using a combination of agent-based and continuum modeling. We find that verticalization proceeds through a series of localized mechanical instabilities on the cellular scale. For short cells, these instabilities are primarily triggered by cell division, whereas long cells are more likely to be peeled off the surface by nearby vertical cells, creating an "inverse domino effect". The interplay between cell growth and cell verticalization gives rise to an exotic mechanical state in which the effective surface pressure becomes constant throughout the growing core of the biofilm surface layer. This dynamical isobaricity determines the expansion speed of a biofilm cluster and thereby governs how cells access the third dimension. In particular, theory predicts that a longer average cell length yields more rapidly expanding, flatter biofilms. We experimentally show that such changes in biofilm development occur by exploiting chemicals that modulate cell length.

Wednesday, May 30, 2018: 335 West Hall, 12:00p - 1:00p

PresenterYonaton Savir, Dept of Physiology, Biophysics and Systems Biology, Technion, Israel

Discussion Single cell response to multiple carbon sources: a case study of combinatorial signal integration

Abstract A major determinant of the fitness of biological systems is their ability to integrate multiple cues from the environment and coordinate their response accordingly. Yet, our understanding of combinatorial integration of multiple inputs and its age dependence is still limited. One of the well-studied examples of such regulation is catabolite repression - a phenomenon where preferred carbon source (e.g., glucose) represses the pathway required for the consumption of alternative carbon sources (e.g., galactose). As a model system, we study how yeast response to hundreds of environments with different carbon sources as a function of time and age. We found that, in contrast to the textbook view, instead of merely inhibiting galactose utilization when glucose is above a threshold concentration, individual cells respond to the ratio of glucose and galactose, and based on this ratio determine whether to induce genes involved in galactose metabolism. We investigate the genetic architectures that can result in a ratio sensing and derive the conditions in which the optimal switching strategy involves preparation and when it is changed from threshold-sensing to ratio-sensing. We characterize the ability of cells to respond to changes in carbon source as a function of age and show that there is a non-trivial relation between mortality rate and failure rate.

Monday, April 9, 2018: 335 West Hall, 12:00p - 1:00p

PresenterCarmen Canavier, Professor and Vice Chair for Research, Department of Cell Biology and Anatomy, Louisiana State University School of Medicine in New Orleans

Discussion Multiple gamma mechanisms co-exist in an excitatory/inhibitory network

Abstract Gamma oscillations have been implicated in many cognitive functions. Fast spiking interneurons are thought to play an important role in gamma synchrony. Recently, fast spiking interneurons in the entorhinal cortex have been shown to exhibit type 2 excitability and postinhibitory rebound (PIR). Theoretical work has shown that these properties make interneuronal network gamma (ING) more robust than in networks of type 1 interneurons. Here we show that this robust ING persists in a sparsely connected excitatory network. We also show that phase response curve (PRC) theory can predict under what circumstances the interneurons will sparsely synchronize in two clusters, and how increasing the delay and/or the conductance destabilizes two clusters in favor of a single cluster.

Monday, February 12, 2018: 335 West Hall, 12:00p - 1:00p

PresenterJianping Fu, Mechanical and Biomedical Engineering, University of Michigan

Discussion Synthetic human embryology in a dish

Abstract Most of our current knowledge of mammalian embryology is derived from studies of the mouse embryo. However, mammalian development involves substantial divergence in the mechanism and order of cell-fate allocations among species, and there has been a critical lack of information regarding human development due to the scarcity of human embryo specimens. Recent studies from my laboratory and others have shown that under suitable culture conditions human pluripotent stem cells (hPSCs) can undergo intricate morphogenetic events and self-organize to form patterned human embryo-like structures in vitro. These synthetic human embryo-like structures have sparked great interests in using such human development models for advancing human embryology, embryo toxicology, and reproductive medicine. In this talk, I will first discuss our effort in developing a micropatterned hPSC-based neuroectoderm developmental model, wherein pre-patterned geometrical confinement induces emergent patterning of neuroepithelial (NE) and neural plate border (NPB) cells, mimicking neuroectoderm regionalization during early neurulation. In the second part of my talk, I will discuss our work in developing a hPSC-based, synthetic embryological model of human post-implantation development that recapitulates multiple embryogenic events including amniotic cavity formation, amnion-epiblast patterning, and primitive streak formation. Together, our studies provide novel insight into previously inaccessible but critical embryogenic events in human development. Continuous development of these human development models will provide synthetic embryological platforms that open up previously inaccessible phases of the human life cycle to experimental study.

Monday, January 8, 2018: 335 West Hall, 12:00p - 1:00p

PresenterJustin Eilertsen, UM Physiology

Discussion Geometric singular perturbation theory and the mathematical description of enzyme kinetics

Abstract Due to the prevelance of fast and slow timescales in enzyme-catalyzed reactions, geometric singular perturbation theory (GSPT) plays a pivotal role in the mathematical illustration of enzyme kinetics. I’ll begin the talk by reviewing some of the earlier work that characterizes single-enzyme/single-substrate (SE/SS) reactions. At the same time, I’ll introduce some of the principal theorems of GSPT and demonstrate their applicability to SE/SS reactions. Finally, I’ll conclude with a description of my current work on coupled reactions. Coupled reactions generally consist of multiple fast timescales and multiple slow timescales; thus, they serve as a novel platform from which to study the applicability of GSPT in higher dimensional dynamical systems.


Monday, April 10, 2017: 335 West Hall, 12:00p - 1:00p

PresenterThomas Gregor, Department of Physics and Lewis-Sigler Institute for Integrative Genomics Princeton University

Discussion How the physics of enhancers shapes development

Abstract Enhancers are small regulatory pieces of DNA that control the activity of genes, which eventually determine cellular fates during the development of multicellular organisms. They need to measure the concentrations of various input effector molecules, called transcription factors, and then act over often very long distances along the DNA in order to activate a distantly located gene. In this talk I will present my laboratory’s progress on two fundamental physical properties of these enhancers: 1. How do enhancers operate at long distances to instruct gene activity? 2. How do enhancers decode the information of the input transcription factors and then transduce it into a precise output? We use a combination of genome editing, live imaging and statistical mechanics techniques to address these questions in the developing fly embryo.


Monday, November 7, 2016: 335 West Hall, 12:00p - 1:00p

PresenterDaniel Wójcik, PhD, Nencki Institute for Experimental Biology, Warsaw

Discussion Source reconstruction from extracellular potentials: from single cells to the whole brains

Abstract Extracellular recordings of electric potential remain a popular tool for investigations of brain activity on all scales in animals and humans, from single cells (spikes) to systems studied with depth electrodes (LFP, SEEG), subdural recordings (ECoG), and on the scalp (EEG). They are relatively easy to record but difficult to interpret: since electric field is long range one can observe neural activity several millimeters from its source. As a consequence, every recording reflects activity of many cells, populations and regions, depending on which level we focus. One way to overcome this problem is to reconstruct the distribution of current sources (CSD) underlying the measurement.

We recently proposed a kernel-based method of CSD estimation from multiple extracellular recordings from arbitrarily placed probes (i.e. not necessarily on a grid) which we called kernel Current Source Density method (kCSD). In my presentation, I will present the recent advances of this method, latest software implementations, and explain why it works. I will also show two recent developments, skCSD (single cell kCSD) and kESI (kernel Electrophysiological Source Imaging). skCSD assumes that we know which part of the recorded signal comes from a given cell and we have access to the morphology of the cell. This could be achieved by patching a cell, driving it externally while recording the potential on a multielectrode array, injecting a dye, and reconstructing the morphology. In this case we know that the sources must be located on the cell and this information can be successfully used in source estimation. In kESI we consider simultaneous recordings with subdural ECoG (strip and grid electrodes) and with depth electrodes (SEEG). Such recordings are taken on some epileptic patients prepared for surgical removal of epileptogenic zone. When MR scan of the patient head is taken and the positions of the electrodes are known as well as the brain’s shape, the idea of kCSD can be applied to constrain the possible distribution of sources facilitating localization of the foci.

Monday, October 10, 2016: 335 West Hall, 12:00p - 1:00p

PresenterSofia Piltz, PhD, Department of Mathematics, University of Michigan

Discussion A piecewise-smooth, two smooth, and a fast-slow system for plankton population dynamics

Abstract Phytoplankton, and the zooplankton that graze upon them, play a crucial role in the dynamics observed at higher levels of the aquatic ecosystem. There is a vast literature on differential equation models of plankton dynamics, and a recent trend in ecological models has considered plasticity in parameters and adaptation. In this talk, we interpret plasticity as prey switching, that is, predator’s adaptive change of diet in response to the abundance of prey. We first analyse a model constructed for one predator feeding on two different types of prey and inspired by plankton observations. This model has a discontinuity between two vector fields. We then discuss two different smooth formulations of the model and compare model predictions with data on freshwater plankton collected from Lake Constance on the German-Swiss-Austrian border. Finally, we discuss a 1 fast-3 slow system for one predator feeding adaptively on two different prey types and inspired by the first model.

Monday, September 12, 2016: 335 West Hall, 12:00p - 1:00p

PresenterIndika Rajapakse, Departments of Computational Medicine and Bioinformatics, and of Mathematics, University of Michigan

Discussion Mathematics of Cellular Reprogramming

Abstract In 2007, a remarkable discovery was made that with just 4 external inputs (transcription factors), it was possible to change differentiated cells into embryonic-like cells. This type of cellular reprogramming changes the fundamental nature of a cell. It invites the possibility of building a universal template for transcription factor guided reprogramming. I will discuss our initial work on this, using advanced genomics technologies + mathematics.

Monday, April 11, 2016: 335 West Hall, 12:00p - 1:00p

PresenterXueying Wang, Department of Mathematics, Washington State University

Discussion Mathematical Modeling of Cholera Epidemics

Abstract Cholera is a severe water-borne disease caused by the bacterium Vibrio cholerae. In this talk, I will present some recent investigations of cholera epidemics through mathematical modeling and analysis. The talk consists of two parts. In the first part, I will give a introduction to infectious disease modeling. In the second part, we will discuss disease threshold dynamics and cholera traveling waves by using ODE and PDE models.


Monday, April 27th, 2015: 335 West Hall, 12:00p - 1:00p

PresenterPaul Francois
Department of Physics McGill University

Discussion Immunology ‡ la physicienne

Abstract T Cells have to make quick, sensitive and specific decisions to recognize not self from self. I will describe a coarse-grained modelling approach aimed at uncovering the basic principles of such immune recognition, that led us to a new "adaptive sorting" model. Adaptive sorting relies on a combination of kinetic proofreading and biochemical adaptation. A more refined model of immune recognition explains many puzzling features of early immune detection, such as antagonism and "digital" response when varying phosphatase concentrations, and was validated experimentally. Finally, I will recast this problem using decision theory and show how this mechanism is especially useful for detection in a fluctuating background of biochemically similar ligands. Adaptive sorting thus constitutes a generic model for "qualitative" sensing of biological signals.
Additional seminar
under Mathematical Biology

Monday, April 20th, 2015

PresenterBard Ermentrout, PhD
Department of Mathematics, University of Pittsburgh

Discussion Keeping the beat: Homeostatic frequency control in coupled oscillators

Abstract When nonlinear oscillators are forced or coupled they will generally lock if the frequency is in a narrow enough range. However, humans and other animals such as fireflies and Snowball the dancing cockatoo are able to adjust the intrinsic frequency of their oscillators to widen the range of locking and even zeroing the phase-lag. In this talk, I will start with some simple abstract circle maps and show that when the frequency is modulated by the coupling there are many possible final states and fractal basin boundaries between them. I will then turn to continuous time oscillators. Using averaging I will derive a new class of phase models and analyze their properties. I apply this to some neural models and show how the homeostatic control of the frequency greatly expands the ability to lock. Finally, I show that traveling periodic wave trains can be destabilized when there is frequency adjustment in rings of coupled oscillators

Monday, April 6th, 2015

PresenterUnCheol Lee, PhD
Department of Anesthesiology, University of Michigan

Discussion Identification of a general relationship between network topology and directed connectivity provides an explanation for how a brain network topology shapes information flow pattern in conscious and unconscious states

Abstract Background: Recent simulation and empirical studies suggest that network topology shapes directed connectivity (sometimes referred to as information flow) in brain networks. However, no general relationship has been systematically studied or identified.

Methods: In simple network models, neural mass models and empirical brain networks, hub nodes of higher degree were consistently targets for directed connectivity. After computational perturbation of networks or administration of anesthetics in humans, monkey and mouse, major hub nodes lost degree and directed connectivity was altered accordingly. Furthermore, the theoretical predictions for the information flow patterns before and after reorganizations of network topology in the conscious and unconscious states were confirmed by the experimental data.

Results: A general relationship can describe directed connectivity in brain networks and perturbations of topology predictably alter the direction of information flow. This relationship may have implications for the neurobiology of consciousness across species as well as state transitions in humans.

Monday, March 9th, 2015

PresenterLawrence Cohen, PhD
Department of Cellular and Molecular Physiology
Yale University

Discussion Determining the function of the mammalian olfactory bulb

Abstract We measured the input from the nose to the olfactory bulb in the mouse using calcium sensitive dye in the olfactory receptor cell nerve terminals in the glomeruli. We are now trying to measure the output of the bulb, carried by the mitral/tufted neurons, with the same glomerular level spatial resolution. The comparison of input and output would define the function(s) carried out by the bulb. Understanding the roles of different neuron types requires fluorescent protein activity indicators that can be expressed in specific cell types. The genetically encoded voltage indicator (GEVI) ArcLight consists of the voltage sensing domain of the Ciona voltage-sensitive phosphatase and the fluorescent protein super ecliptic pHluorin (A227D). The fluorescence of ArcLight changes by ~40% in response to a 100mV depolarization; about five times larger than previously reported signals. ArcLight can be specifically expressed in mitral/tufted neurons and reports odor-evoked electrical activity. The experiments comparing the input and output of the bulb are just beginning.

Monday, January 26th, 2015

PresenterMark Reimers, PhD
Neuroscience Program, Michigan State University

Discussion Two Vignettes in Computational Neuroscience: from data to models

Abstract This talk will describe two models for brain dynamics and their relation to data.

The first is a model for slow (delta-band) activity over the surface of mouse cortex. We develop a linear model for both intrinsic regional dynamics and communication between cortical regions, and use this model to estimate some of the effective connectivity between different cortical regions. Our estimates from dynamical data correspond well to known anatomical connections. Short-term predictions from this model are correlated 65% with observed data. The model is being extended to non-linear dynamics.

The second model reproduces the gamma rhythm found in active regions of cortex. There have been several models that generate plausible rhythms in the gamma range (30-50 Hz); but the parameters of these models are not realistic. Furthermore recent genomic data from healthy human subjects indicates very high variability in key parameters of these models, and current models are not robust to this variability. We propose a more realistic model drawing on data; the distinctive feature is high diversity among connection strengths. This model gives much more realistic gamma rhythms, on all measures, and is also more robust to inter-individual variation.


Monday, December 8th, 2014

PresenterTibin John, PhD
Kalamazoo College, Center for Complex Systems Studies

Discussion Cell and Network Level Changes Related to Overproduction of Alzheimers Amyloid Cause Altered Synchronized Activity in Model of Hippocampal Theta Rhythm Generation

Monday, November 24th, 2014

PresenterAngela Violi, PhD
Associate Professor of Mechanical Engineering, Chemical Engineering, Biomedical Engineering, Macromolecular Science and Engineering, and Applied Physics, at the University of Michigan

Discussion Simulating biological membranes