Session B41: Systems Biology

Whole-brain calcium imaging with cellular resolution in freely behaving Caenorhabditis elegans

The ability to acquire large-scale recordings of neuronal activity in awake and unrestrained animals is needed to provide new insights into how populations of neurons generate animal behavior. Acquiring this data, however, is challenging because it is difficult to track and image individual neurons as an animal deforms its posture and moves many body lengths. Here, we present an instrument capable of recording intracellular calcium transients from the majority of neurons in the head of a freely behaving \textit{Caenorhabditis elegans} with cellular resolution while simultaneously recording the animal’s position, posture, and locomotion. 3D volumetric fluorescent images of neurons expressing the calcium indicator GCaMP6s are recorded at 6 head-volumes/s using spinning disk confocal microscopy. At the same time, we record low magnification images of the animal to measure the animals behavior and track its head as it moves. We develop a time independent neuronal matching algorithm that uses non-rigid point set registration and machine learning to correctly match neurons across time. Using this method, we are able to observe calcium transients from up to 90 neurons for over 4 min and correlate the neural activity with the animal’s behavior.   

Dynamics of adaptive immunity against phage in bacterial populations

The CRISPR (clustered regularly interspaced short palindromic repeats) mechanism allows bacteria to adaptively defend against phages by acquiring short genomic sequences (spacers) that target specific sequences in the viral genome. We propose a population dynamical model where immunity can be both acquired and lost. The model predicts regimes where bacterial and phage populations can co-exist, others where the populations oscillate, and still others where one population is driven to extinction. Our model considers two key parameters: (1) ease of acquisition and (2) spacer effectiveness in conferring immunity. Analytical calculations and numerical simulations show that if spacers differ mainly in ease of acquisition, or if the probability of acquiring them is sufficiently high, bacteria develop a diverse population of spacers. On the other hand, if spacers differ mainly in their effectiveness, their final distribution will be highly peaked, akin to a ``winner-take-all'' scenario, leading to a specialized spacer distribution. Bacteria can interpolate between these limiting behaviors by actively tuning their overall acquisition rate.   

Distinguishing Feedback Mechanisms in Clock Models

Biological oscillators are very diverse but can be classified based on dynamical motifs such as type of feedback. The S. Elongatus circadian oscillator is a novel circadian oscillator that can operate at constant protein number by modifying covalent states. It can be reproduced in vitro with only 3 different purified proteins: KaiA, KaiB, and KaiC. We use computational and analytic techniques to compare models of the S. Elongatus post-translational oscillator that rely on positive feedback with models that rely on negative feedback. We show that introducing a protein that binds competitively with KaiA to the KaiB-KaiC complex can distinguish between positive and negative feedback as the primary driver of the rhythm, which has so far been difficult to address experimentally.   

Starvation-induced dormancy in E. coli

Isogenic bacterial populations can exhibit phenotypic heterogeneity. Phenotypic heterogeneity is often viewed as a bet-hedging strategy to cope with environmental fluctuations, and believed to be under genetic control. The experimental evidence of this view, however, is limited. Here, we report experimental evidence that prompts reconsideration of this view. Observing how starved E. coli cells resume growth upon nutrient upshift at the single-cell level in real time, we revealed that physiological and metabolic state of starved cells, as well as growth resumption kinetics, vary from cell to cell. Upon nutrient upshift, a majority of cells resume growth instantly, but a small fraction maintain a non-growth state for several hours or days (i.e., long lag time). Hence they are dormant cells. The fraction strongly depends on the duration of starvation. The dormancy does not confer resistance to starvation. Oxidative damage accumulated during starvation leads to the appearance of dormant cells. Taken together, our data suggests that a dormant subpopulation appears as an inevitable consequence of starvation, rather than cellular decision to cope with starvation. Hence, the existence of a genetic program and adaptive value as a bet-hedging strategy to cope with starvation stress may not be needed to explain the emergence of bacterial dormancy.   

Queueing-Based Synchronization and Entrainment for Synthetic Gene Oscillators

Synthetic gene oscillators have been a major focus of synthetic biology research since the beginning of the field 15 years ago. They have proven to be useful both for biotechnological applications as well as a testing ground to significantly develop our understanding of the design principles behind synthetic and native gene oscillators. In particular, the principles governing synchronization and entrainment of biological oscillators have been explored using a synthetic biology approach. Our work combines experimental and theoretical approaches to specifically investigate how a bottleneck for protein degradation, which is present in most if not all existing synthetic oscillators, can be leveraged to robustly synchronize and entrain biological oscillators. We use both the terminology and mathematical tools of queueing theory to intuitively explain the role of this bottleneck in both synchronization and entrainment, which extends prior work demonstrating the usefulness of queueing theory in synthetic and native gene circuits. We conclude with an investigation of how synchronization and entrainment may be sensitive to the presence of multiple proteolytic pathways in a cell that couple weakly through crosstalk.   

Effect of correlations between minima on a complex energy landscape

We recently modeled cellular interconvertion dynamics[1] by using an epigenetic landscape model[2] inspired by neural network models[3]. Given an arbitrary set of patterns, the model can be used to construct an energy landscape in which those patterns are the global minima. We study the possible stable states and metastable states of the landscapes thus constructed. We consider three different cases: i) choosing the patterns to be random and independently distributed ii) choosing a set of patterns directly derived from the experimental cellular transcription factor expression data for a representative set of cell types in an organism and iii) choosing randomly generated trees of hierarchically correlated patterns, inspired by biology. For each of the three cases, we study the energy landscapes. In particular we study the basins of attraction of both the stable states and the metastable states, we compute the configurational entropy as a function of energy, and we demonstrate how those results depend on the correlations between the patterns. \\References\\{ } [1] Pusuluri et.al (2015) arXiv:1505.03889.\\ { } [2] Lang et.al (2014) PLoS computational biology 10, e1003734.\\ { } [3] Kanter et.al (1987) Physical Review A 35, 380–392.   

The Power Spectrum of Ionic Nanopore Currents: The Role of Ion Correlations

Measuring the ionic current passing through a nanometer-scale membrane pore has emerged over the past decades as a versatile technique to study molecular transport. These measurements suffer from high noise levels that typically exhibit a power law dependence on the frequency. A thorough theoretical understanding of the power spectrum is essential for the optimisation of experimental setups and for the use of measurement noise as a novel probe of the nanopore's microscopic properties. We calculate the power spectrum of electric-field-driven ion transport through nanopores using both linearized mean-field theory and Langevin dynamics simulations. With only one fitting parameter, the linearized mean-field theory accurately captures the dependence of the simulated power spectrum on the pore radius and the applied electric field. Remarkably, the linearized mean-field theory predicts a plateau in the power spectrum at low frequency f, which is confirmed by the simulations at low ion concentration. At high ion concentration, however, the power spectrum follows a power law that is reminiscent of the 1/f dependence found experimentally at low frequency. Based on simulations with and without ion-ion interactions, we attribute the low-frequency power law dependdence to ion-ion correlations   

Statistical Models of Adaptive Immune populations

The availability of large (10\textasciicircum 4-10\textasciicircum 6 sequences) datasets of B or T cell populations from a single individual allows reliable fitting of complex statistical models for na\"{\i}ve generation, somatic selection, and hypermutation. It is crucial to utilize a probabilistic/informational approach when modeling these populations. The inferred probability distributions allow for population characterization, calculation of probability distributions of various hidden variables (e.g. number of insertions), as well as statistical properties of the distribution itself (e.g. entropy). In particular, the differences between the T cell populations of embryonic and mature mice will be examined as a case study. Comparing these populations, as well as proposed mixed populations, provides a concrete exercise in model creation, comparison, choice, and validation.   

Networks In Real Space: Characteristics and Analysis for Biology and Mechanics

Functional networks embedded in physical space play a crucial role in countless biological and physical systems, from the efficient dissemination of oxygen, blood sugars, and hormonal signals in vascular systems to the complex relaying of informational signals in the brain to the distribution of stress and strain in architecture or static sand piles. Unlike their more-studied abstract cousins, such as the hyperlinked internet, social networks, or economic and financial connections, these networks are both constrained by and intimately connected to the physicality of their real, embedding space. We report on the results of new computational and analytic approaches tailored to these physical networks with particular implications and insights for mammalian organ vasculature.   

A kinetic model for chemical neurotransmission

Recent experimental observations in presynaptic terminals at the neuromuscular junction indicate that there are stereotyped patterns of cooperativeness in the fusion of adjacent vesicles. That is, a vesicle in hemifusion process appears on the side of a fused vesicle and which is followed by another vesicle in a priming state while the next one is in a docking state. In this talk we present a kinetic model for this morphological pattern in which each vesicle state previous to the exocytosis is represented by a kinetic state. This chain states kinetic model can be analyzed by means of a Master equation whose solution is simulated with the stochastic Gillespie algorithm. With this approach we have reproduced the responses to the basal release in the absence of stimulation evoked by the electrical activity and the phenomena of facilitation and depression of neuromuscular synapses. This model offers new perspectives to understand the underlying phenomena in chemical neurotransmission based on molecular interactions that result in the cooperativity between vesicles during neurotransmitter release.   

Oxidant Signaling in Cells Revealed by Single Rare-Earth Based Nanoparticle Imaging

The spatio-temporal organization of signaling pathways controls the cell response. Reactive oxygen species (ROS) are second messengers involved in the control of numerous normal and pathological processes and their local concentration is thus tightly regulated. However, the dynamics of ROS production and organization is mostly unknown, due to the lack of efficient probes. We developed single ROS sensitive Eu$^{\mathrm{3+}}$-doped nanoparticle imaging to quantitatively probed the intracellular ROS response. We revealed specific temporal patterns of ROS production under different types of stimulation (PDGF and ET-1) and quantitatively identified mechanisms of transactivation, which notably control the dynamics of the cell response. By using a microfluidic system, we apply spatially controlled stimulations and displayed the maintenance of asymmetric ROS concentration in the cell under a PDGF gradient. We then developed a ratiometric method using a nanoparticle mix, to quantitatively detect ROS with a 500 ms temporal resolution. We thus elucidate molecular mechanisms responsible for the control of the oxidant production kinetics. Altogether, our results reveal regulation mechanisms controlling ROS spatio-temporal organization, which can be crucial for the buildup of the cell response.   

Regulatory inhibition of biological tissue mineralization through post-nucleation shielding

In vertebrates, insufficient availability of calcium and phosphate ions in extracellular fluids leads to loss of bone density and neuronal hyper-excitability. To counteract this problem, calcium ions are present at high concentrations throughout body fluids – at concentrations exceeding the saturation point. This condition leads to the opposite situation where unwanted mineral sedimentation may occur. Remarkably, ectopic or out-of-place sedimentation into soft tissues is rare, in spite of the thermodynamic driving factors. This fortunate fact is due to the presence of auto-regulatory proteins that are found in abundance in bodily fluids. Yet, many important inflammatory disorders such as atherosclerosis and osteoarthritis are associated with this undesired calcification. Hence, it is important to gain an understanding of the regulatory process and the conditions under which it can go awry. We adapted mean-field classical nucleation theory to the case of surface-shielding in order to study the regulation of sedimentation of calcium phosphate salts in biological tissues.   

E.coli in weak magnetic field in different media

We study the growth of E-coli in a weak magnetic field, both in a liquid and a solid medium. We use LB broth for that purpose at the room temperature and study the growth in different types of magnetic field. We grow it over the bar magnets and within the magnetic field generated by the Helmholtz coils. It has been clearly noticed that the growth of bacteria is clearly affected with the magnetic field and the different types of magnetic field affect differently.   

Comparative Study of Bacterial Growth in Magnet Fields

It has been shown that magnetic fields affect bacterial growth. A comparative study of growth rates for gram-positive and gram-negative bacteria with different types of magnetic fields is done. Special focus is placed upon growth within liquid media, and the effect of magnetic fields relative to the chosen growth medium is considered.