Seminars
January 3, 2023: (Special Time: 10AM via Zoom Only, Physics Fellow Candidate) – Xiaowen Chen, Ecole Normale Superieure
Inferring Collective Dynamics In Groups Of Social Mice.
Host: Bertrand Ottino-Loffler
Social interactions are a crucial aspect of behavior in human society and many animal species. Nonetheless, it is often difficult to distinguish the effect of interactions from independent animal behavior (e.g. non-Markovian dynamics, response to environmental cues, etc.). I will address this question in social mice, where we infer statistical physics models for the collective dynamics for groups of mice, housed and location-tracked over multiple days in a controlled yet ecologically-relevant environment. We reproduce the distribution for the co-localization patterns using pairwise maximum entropy models. The inferred interaction strength is biologically meaningful and can be used to characterize sociability for different mice strains. Moreover, these models can distinguish the effect of change of prefrontal cortex plasticity due to social-impairment drugs, and useful to study autism in the mice model. The equilibrium dynamics on the resulting model can successfully predict the transition rates, but not the waiting time distribution. Inspired by the observed long-tailed waiting time distributions in the mice, we have developed a novel inference method that can tune the dynamics while keeping the steady state distribution fixed. Constructed through a non-Markovian fluctuation-dissipation theorem, this new inference method, termed the “generalized Glauber dynamics”, addresses an important question in statistical inference, for which I will derive the expression, demonstrate its power, and show how to infer the model using examples of Ising and Potts spins. Finally, we will apply the generalized Glauber dynamics to the social mice data and show how memory is important in collective animal behavior.
January 5, 2023: (Special Time: 2PM via Zoom Only, Physics Fellow Candidate) – Merav Stern, University of Oregon and The Hebrew University of Jerusalem
Modeling Neural Networks Reveals How Neural Circuitry Transforms Space Into Time.
Host: Liat Shenhav
The connectivity structure of many biological systems, including neural circuits, is highly non-uniform. Recent developments in optogenetic tools allow mapping in detail these irregularities in neural connectivity. But our understanding of these maps, including the contribution of each connectivity component to the overall circuitry dynamics, is still lacking. I will present analytical tools from complex system studies which enable us to isolate the impact of each connectivity component by astute reduction of the network description. I will bring a few specific examples of non-uniform connectivity, including cell-type dependent connectivity and clustering. I will show how they enrich the network dynamics and transform spatial properties into timing mechanisms.
January 12, 2023: (Special Time: 10AM, Physics Fellow Candidate) – Avaneesh Narla, University of California, San Diego
Dynamic Coexistence Due To Growth Succession In Cyclic Microbial Ecosystems.
Host: Eric Siggia
Microbial ecosystems are commonly modeled by fixed interactions between microbes in steady physiological states, typically the exponential growth state. However, ecological dynamics often feature large self-generated environmental changes which drive microbes through distinct physiological states manifested by very different growth rates. Examples of such dynamics include succession dynamics in nature and simple growth-dilution cycles in the laboratory. Here, we introduce a phenomenological model to gain insight into the dynamic coexistence of microbes due to changes in physiological states in cyclic environments. Our model allows us to bypass specific interactions leading to different physiological states (e.g., nutrient starvation, stress, aggregation, contact-dependent killing, etc.), by considering the growth of each species according to a global ecological coordinate, taken here to be the total community biomass. Analysis of this model provides rigorous, quantitative criteria for the dynamic coexistence of many species in terms of differential species’ dominance (“growth niche”) along the ecological coordinates. Our model shifts the focus of ecosystem dynamics from bottom-up studies based on inter-species interaction to top-down studies based on accessible macroscopic observables such as growth rates and total biomass, thereby allowing quantitative examination of community-wide characteristics.
January 19, 2023: (Special Time: 10AM, Physics Fellow Candidate) – Caroline Holmes, Princeton University
Sensing And Encoding Problems, From Circadian Clocks To Photoreceptors.
Host: Ben Weiner
I will discuss two problems that I have worked on in my PhD, both of which have involved considering how biological systems encode information about their environments. In the first of these, I considered circadian clocks as an encoding problem. We found that the constraint of decodability significantly restricts the parameter space of circadian clocks, and that it may explain the long-standing puzzle of non-24 hour internal periods of circadian clocks. In the second section, I will discuss ongoing work on photoreceptor arrangement. This is an interesting problem in itself, as many organisms have qualitatively different photoreceptor arrangements, but it also has been a lens into thinking more deeply and generally about the relationship between optimality and variability.
February 21, 2023: (4PM) – Lisa Stein, University of Alberta
Applying Systems Biology to Resolve Microbial Metabolism of Greenhouse Gases.
Host: Ben Weiner
Technologies to reduce GHG emissions must take microorganisms into account as this invisible majority is largely responsible for production and consumption of methane and nitrous oxide, the second and third most important GHGs in causing global warming. Methanogenesis produces most of the methane emitted to the atmosphere, whereas methanotrophic microbes account for methane consumption prior to its emission, plus ca. 1% of atmospheric methane consumption. The primary source of nitrous oxide to the atmosphere is from nitrifying and denitrifying microorganisms whose activity has accelerated over the past 60 years due to anthropogenic input of reactive-N to the biosphere. Interestingly, methanotrophic and nitrifying microbes share common enzymes and metabolic pathways, enabling both groups to produce or consume GHGs depending mainly on redox potential and nitrogen availability. Using the bacterium Methylomicrobium denitrificans FJG1 as a model system, we collected RNAseq, proteomics and metabolomics data across 6-point growth curves to examine the dynamics of methane consumption and nitrous oxide production as a function of oxygen and nitrogen availability. A gene regulatory network of the RNAseq data showed different topologies with either ammonium or nitrate as the N-source, as nitrate is required to induce methane-dependent denitrification to nitrous oxide. With a genome-scale metabolic model under construction, the omics data point to a division of labor in M. denitrificans between fermentation and denitrification at the onset of anoxia. Extrapolating to natural ecosystems, a similar division of labor has been observed in anoxic freshwater lakes wherein methanotrophs use alternative electron acceptors to consume methane while providing organic molecules from fermentation to cross-feed other microbial populations. However, when nitrate is the alternative electron acceptor, nitrous oxide is produced proportionally to methane consumption. This case-study demonstrates the need to consider interconnectedness and coevolution of microbial functionality, and to apply omics-based systems biology models when developing and implementing GHG reduction strategies at ecosystem scale.
February 28, 2022: (4PM) – Arup Chakraborty, Massachusetts Institute of Technology
The Antibody Response to Mutable Viruses.
Host: Bertrand Ottino-Loffler
Infectious disease-causing pathogens have plagued humanity since antiquity, and the COVID-19 pandemic has been a vivid reminder of this perpetual existential threat. Vaccination has saved more lives than any other medical procedure, and indeed, effective vaccines have helped control the COVID-19 pandemic. However, we do not have effective vaccines against rapidly mutating viruses, such as HIV; nor do we have a universal vaccine against seasonal variants of influenza or SARS-CoV-2 variants that continue to evolve. The ability to develop effective universal vaccines that protect us from variant strains of mutable viruses will help create a more pandemic-resilient world. In this talk, I will describe how by bringing together approaches from statistical physics, virology and immunology, progress is being made to address this challenge. In particular, I will focus on approaches that aim to design vaccines and immunization strategies that elicit antibodies that can protect against diverse mutant strains. As I hope to show, this is a problem at the intersection of statistical physics, evolutionary biology, immunology, and vaccine development. The application of fundamental concepts to HIV, influenza and SARS-CoV-2 vaccines will be discussed.
March 14, 2023: (4PM) – Jennifer A.N. Brophy, Stanford University
Reprogramming Plant Development Using Synthetic Genetic Circuits.
Host: Ben Weiner
Structural features of a plant contribute to its ability to survive in challenging environments. For example, the size and shape of a plant’s root system influences its ability to reach essential nutrients in the soil or to acquire water during drought. Yet, our understanding of relationships between form and function remain limited. We are using synthetic gene circuits to modify the size and shape of plants so that we can test the contribution of specific plant features to environmental stress tolerance. A better understanding of the plant features that are important for environmental stress tolerance would enable targeted breeding and biotechnological interventions that strengthen our agricultural systems.
March 16, 2023: (4PM) – David Zeevi, Weizmann Institute of Science
Investigating Human Effects On Natural Microbial Communities.
Host: Liat Shenhav
Microbial ecosystems are critical for supporting life on Earth, regulating global nutrient cycles, greenhouse gas exchange, and disease transmission and protection. Yet, there is increasing evidence that natural microbial communities are affected by anthropogenic stress from pollutants, fertilizers and land-use changes, among other factors. In my lab, we study human effects on microbial communities. Our ultimate goal is to discover microbe-based modalities for upcoming challenges, such as food security in an increasingly warm and polluted planet. Common approaches for studying the response of microbial communities to human intervention usually depend on comparisons between environments (e.g., natural and managed). However, microbial communities are affected by many factors, making any two such environments different and increasing the risk of spurious findings. In addition, most species and genes in many of these environments are uncharacterized, greatly limiting the discovery of microbe-based modalities. In my talk, I will discuss the approaches we undertake to advance discovery while addressing these issues, including the development of novel computational methods and the collection of unique data.
April 5, 2023: (Note: This is a Wednesday seminar – 4PM) – Jan Skotheim, Stanford University
How Cells Coordinate Growth And Division.
Host: Eric Siggia
Cell size is fundamental to function in different cell types across the human body because it sets the scale of organelle structures, surface transport, and, most importantly, biosynthesis. While some genes affecting cell size have been identified, the molecular mechanisms through which cell growth drives cell division had remained elusive. While it was expected that growth would act to increase the activities of the cyclin-dependent kinases (Cdk) known to promote cell division, this is not the case. Rather, we found that cell growth acts in the opposite manner. Cell growth triggers division by diluting proteins that inhibit cell division, Whi5 in yeast, and the retinoblastoma tumor suppressor Rb in human cells. Thus, inhibitor dilution provides one long sought mechanism coupling cell growth to cell division and it relies on the differential scaling of the biosynthesis of cell cycle activators and inhibitors molecules. How are some molecules synthesized to remain in proportion to cell size while others are synthesized in amounts that are independent of cell size? We have begun to elucidate the molecular mechanisms underlying size scaling across the proteome and have uncovered both transcriptional and post-transcriptional mechanisms that tune protein concentrations to enhance cellular function and control cell size.
April 25, 2023: (4PM) – Daniel H. Buckley, Cornell University
To Come.
Host: Ben Weiner
To Come.