Seminars Spring 2016
Seminars are on Tuesdays at 4 pm, preceded by tea at 3:45, unless otherwise noted.
For the months of March, April and May, our seminars will take place in either, the Carson Family Auditorium, or Weiss Research Building, Room 301. Locations will be indicated. This location change is due to construction.
January 12, 2016: Alexei Koulakov, Cold Spring Harbor LabNeural relativity principleHost: P. Sulc
January 19, 2016:Sean Eddy, Harvard UniversitySequence homology searches: the future of deciphering the pastHost: P. SulcComputational recognition of distant sequence homology is a key to studying ancient events in molecular evolution. The better our sequence analysis methods are, the deeper in evolutionary time we can see. A major aim in the field is to improve the resolution of homology recognition methods by building increasingly realistic, complex, parameter-rich models. I will describe current and future research in protein, DNA, and RNA homology search algorithms based on probabilistic inference methods, using hidden Markov models (HMMs) and stochastic context-free grammars (SCFGs). We make these methods available in the HMMER and Infernal software from my laboratory, in collaboration with sequence family databases including Pfam and Rfam.
January 26, 2016: Leonid L. Moroz, University of FloridaOrigins and Convergent Evolution of Neural Systems: From Single-neuron Genomics to NeuroSystematicsHost: C. KirstNeurons are different not only because they have different functions but also because they might have different genealogies. However, the enormous diversity of neurons both within the same nervous system and across species presents tremendous challenges for their unbiased classification. Here, I will discuss novel approaches and algorithms toward establishing the natural classification of neurons. Our research strategy is based upon (1) high-throughput single-cell RNA-seq and single-cell epigenomic analyses of entire neuronal circuits as they learn and remember, and (2) implementation of stochastic approaches from phylogenomics. Our results suggest that different classes of neurons and synapses (as well as complex brains) might have evolved more than once (convergent evolution) and allow us to start reconstruction the genealogy of neurons, trace ancestral cell lineages, and establish the natural classification of neurons within neural circuits across the majority of animal phyla: from ctenophores and cnidarians to bilaterians including cephalopods. The field of Neurosystematics is emerging. This might be an analog of the periodic table for neurons, with the predictive power to delineate novel neuronal phenotypes and fundamental constraints on the origins and parallel evolution of neural systems. In summary, there is more than one way to develop neuronal complexity, and animals frequently use different molecular toolkits to achieve similar functional outcomes.
January 28, 2016: Andrea Liu, University of PennsylvaniaTuning Mechanical Response in Disordered NetworksHost: P. SulcThe properties of amorphous solids are essentially and qualitatively different from those of simple crystals. Unless a crystal's unit cell is very complicated, all particles or inter-particle bonds contribute nearly equally to any global quantity, so that each bond plays a similar role in determining the physical properties of the solid. For example, removing a single bond in a perfectly ordered array or network decreases the overall elastic strength of the system, but in such a way that the resistance to shear and the resistance to compression drop in tandem so that their ratio is nearly unaffected. Disordered materials are not similarly constrained. We introduce a principle unique to disordered solids wherein the contribution of any bond to one global perturbation is uncorrelated with its contribution to another. Coupled with sufficient variability in the contributions of different bonds, this ``independent bond-level response" paves the way for the design of real materials with unusual and exquisitely tuned properties. For example, we can tune a disordered network’s Poisson ratio anywhere between the auxetic and incompressible limits. We can also produce a targeted response at a local scale; by perturbing the positions of pair of particles at one point we can tune in a desired response a large distance away. This response is reminiscent of allosteric regulation in proteins where a reaction at one site activates another site of the protein molecule. Experimentally, we have successfully demonstrated such mechanical networks in 2D (by laser cutting) or in 3D (3D printing).
February 4, 2016 (Thursday, 2 PM): Sonya Hanson, Memorial Sloan Kettering Cancer CenterUnderstanding the physical basis for biological temperature sensingHost: E. SiggiaEngineered sensors allow us to accurately measure external stimuli, such as temperature, pressure, light, and sound. However, how biological organisms detect some of these same stimuli remains poorly understood. One of the most fundamental of these is the detection of temperature: avoiding cell damage while seeking optimal temperatures for cell physiology is key to the survival of both complex and simple organisms. While temperature affects many rates within the cell, certain components have evolved specifically to function as temperature sensors. While we know these temperature sensors exist in various forms, such as the changing of membrane fluidity, folding of RNA thermometers, or opening of ion channel pores, our understanding of how these distinct mechanisms are invoked by identical changes in temperature is incomplete. Did evolution harness the same statistical mechanical principles for all of these? For some models of temperature sensing, parallels can be drawn to problems in protein folding. This talk will walk through recent developments relevant to understanding temperature sensing in biology. First will be an overview of the exciting advances of the last decade in understanding the TRP channel family: a temperature sensing family of ion channel proteins (present only in eukaryotes), in which hot and cold sensitive channels are also sensitive to the small molecules capsaicin (of chili peppers) and menthol (of mint), respectively. Then we will examine the variety of tools initially developed to perform and analyze long timescale molecular simulations for protein folding applied to model protein systems chosen to refine the statistical mechanical understanding of small molecule binding to proteins. The talk will conclude with a look forward to how we can combine these tools to define model temperature sensing systems and develop a general framework for understanding temperature sensing mechanisms across biological organisms.
February 9, 2016 (2 PM): Tyler Shendruk, University of OxfordFrom Single Swimmers to Spontaneous Spin-StatesHost: E. SiggiaFor the most part microbial life does not swim through simplebulk Newtonian fluids but rather moves through complex environments. Surfaces, interfaces and confinement are ubiquitous in microbial environments . Motile microbes can be either aided or deterred from reaching surfaces by external flows, and the flowing medium may exhibit a dual fluidic and elastic nature. In this seminar, we will discuss the dynamics and hydrodynamics of self-propelled microorganisms in these biologically relevant environments. In particular, swimmer trajectories within flowing films will be considered in order to determine how swimming strategy results in differing swimmer distributions. It will be shown that the rheology of flowing biological medium plays an important role in setting the ability of microbes to swim upstream in microchannels. We will then turn our attention to suspensions of many swimmers confined within an array of responsive obstacles to explore the ability of collective motion to restructure micro-environments. We model the dense suspensions of motile cells as a complex fluid: an active nematic liquid crystal. Our simulations show that a lattice of rotors immersed a bacterial suspension in self-organizes into a spin-state wherein neighboring disc-like obstacles continuously rotate in permanent alternating directions due to combined hydrodynamic and elastic effects. This antiferromagnetic spin-state is permanent and only exists for sufficiently small inter-disc spacing. The existence of such active matter-mediated forces between passive bodies suggests the ability of living suspensions to facilitate collective motion by altering their surroundings.
March 1, 2016: Ned Wingreen, Princeton University [Weiss Research Building, Room 301]Getting together: What can enzyme clustering do for metabolism?Host: P. SulcMetabolism is the set of enzymatic reactions that cells use to generate energy and biomass. Interestingly, recent studies suggest that many metabolic enzymes assemble into large clusters, often in response to environmental conditions. Theoretically, we find that large-scale enzyme clusters, with no internal spatial ordering of enzymes, offer many of the same advantages as direct substrate channeling: accelerating intermediate processing, protecting intermediates from degradation/cross-reactions, and protecting the cell from toxic intermediates. The model predicts the separation and size of coclusters that maximize metabolic efficiency. For direct validation, we study a metabolic branch point in Escherichia coli and experimentally confirm the model predictions. Our studies establish a quantitative framework to understand coclustering-mediated metabolic channeling and its application to both efficiency improvement and metabolic regulation.
March 8, 2016: Michael Laub, MIT [Carson Family Auditorium]Specificity and evolution of protein-protein interfacesHost: P. SulcProtein-protein interactions are critical to the operation and functions of all cells. The specificity of these interactions is often dictated at the level of molecular recognition, meaning proteins have an intrinsic ability to discriminate cognate from non-cognate partners. Understanding precisely how this discrimination is accomplished remains a major problem, particularly for paralogous protein families in which the individual members share high sequence and structural similarity. Our work tackles this problem primarily in the context of two-component signal transduction systems, the predominant form of signaling in bacteria, and more recently with toxin-antitoxin systems, also found throughout the bacterial kingdom. I will describe our work using analyses of amino acid coevolution to pinpoint the molecular basis of specificity in these proteins. This work has enabled the rational rewiring of protein-protein interactions and signal transduction pathways. Additionally, these studies have driven efforts to systematically map sequence spaces and probe the selective pressures and constraints that govern the evolution of protein-protein interactions.
March 22, 2016: Claude Desplan, NYU[Weiss Research Building, Room 301]Evolution of color and motion visionHost: P. SulcLike the human retina, the Drosophila retina contains randomly distributed color photoreceptor cells that are defined by the expression of different color sensitive Rhodopsins. In Drosophila, two types of individual unit eyes (ommatidia) are specified by stochastic expression of the transcription factor Spineless. This decision is controlled by a two-step process: First, each allele of spineless randomly makes a cell-intrinsic ON/OFF expression decision governed by global activation coupled with stochastic repression. When the expression decisions disagree (one allele ON and one allele OFF), interchromosal communication coordinates expression state between the two alleles. This effect does not depend on chromosomal pairing or endogenous spineless chromosomal position but instead requires specific DNA elements to mediate regulatory interactions. This mechanism couples stochastic repression with interallelic coordination and contrasts starkly with the noisy activation mechanisms seen in bacteria, and the mono-allelic, stochastic activation mechanisms observed in the mouse olfactory and human color vision systems. Many vertebrate and invertebrate eyes also have retinal mosaics that contain different stochastically specified types of photoreceptors. At least one group, the butterflies, make a three-way stochastic choice between three ommatidial types. However, it remains unclear how much of the regulatory network that specifies photoreceptor subtypes is retained or has evolved in other insects, and whether they use stochastic Spineless expression to diversify their sometimes more complex retinal mosaics. I will present evidence that a conserved regulatory code defines and expands photoreceptor subtypes between flies (Drosophila) and butterflies (Papilio xuthus and Vanessa cardui). We used CRISPR/Cas9 to knock out Spineless in butterflies and provide functional evidence that there is deep evolutionary conservation of stochastic patterning mechanisms. Furthermore, butterflies have two R7 photoreceptors that allow for the specification of three types of ommatidia instead of two. This in turn allowed for the evolution and deployment of additional opsins, tetrachromacy, and improved color vision, important features of butterfly life history and ecology. Our extensive knowledge of patterning in the Drosophila visual system applies to other groups, and adaptation for specific visual requirements can occur through modification of this network. Patterning of the neurons that process visual information in the optic lobes is, in contrast to the retina, highly deterministic. The medulla, where motion and color information are processed, contains 40,000 neurons of more than 70 cell types. These neurons are born from neural stem cells (Neuroblasts) that sequentially express five transcription factors. The neurons emerging from neuroblasts at each stage maintain expression of the corresponding gene and become different cell types. We will describe the mechanisms controlling the transition from one neuroblast stage to the next. The neuroepithelium that generates the medulla neuroblasts is also highly patterned, with eight regions defined by the expression of spatially restricted transcription factors. Each region contributes to generating two types of neurons: ‘Uni-columnar neurons’ that have a 1:1 stoichiometry with the photoreceptors that innervate the medulla and are generated throughout the neuroepithelium. The less numerous ‘non-columnar’ neurons, which contact multiple photoreceptors, are generated from specific sub-regions of the neuroepithelium and migrate to take on their retinotopic position in the medulla. This combination of temporal and spatial patterning allows for the generation of the 70 medulla cell types.
March 24, 2016: Jane Wang, Cornell [Carson Family Auditorium]Insect Flight: From Newton's Law to NeuronsHost: P. SulcWhy do animals move the way they do? Bacteria, insects, birds, and fish share with us the necessity to move so as to live. Although each organism follows its own evolutionary course, it also obeys a set of common laws. At the very least, the movement of animals, like that of planets, is governed by Newton’s law: All things fall. On Earth, most things fall in air or water, and their motions are thus subject to the laws of hydrodynamics. Through trial and error, animals have found ways to interact with fluid so they can float, drift, swim, sail, glide, soar, and fly. This elementary struggle to escape the fate of falling shapes the development of motors, sensors, and mind. Perhaps we can deduce parts of their neural computations by understanding what animals must do so as not to fall. In this talk I will discuss recent developments along this line of inquiry in the case of insect flight. Asking how often a fly must sense its orientation in order to balance in air has shed new light on the role of motor neurons and steering muscles responsible for flight stability.
April 5, 2016: Michael Hagan, Brandeis University [Carson Family Auditorium]Cargo encapsulation by self-assembling icosahedral containersHost: P. SulcThe self-assembly of a protein shell around a cargo is a common mechanism of encapsulation in biology, and is inspiring development of drug delivery vehicles that form by self-assembly. However, the physics underlying such multicomponent assembly processes is incompletely understood. In this talk I will describe how minimal computational models can elucidate two biological examples in which icosahedral protein shells assemble around cargos. In each case we find that the material properties of the cargo play a key role in directing its encapsulation. The first example concerns viruses with single-stranded RNA (ssRNA) genomes. For many ssRNA viruses, formation of an infectious virus requires the spontaneous assembly of an icosahedral protein shell (called a capsid) around the genome. I will describe simulations that investigate how this co-assembly process depends on the physical properties of RNA: its length, electrostatic charge, and 3D structure. When applied to specific virus capsids, the calculated optimal RNA lengths closely correspond to the natural viral genome lengths. This suggests that evolution of viral RNA is driven not only by the fitness of the proteins that it encodes for, but also by how its material properties favor encapsulation. We then show that assembly can proceed through two qualitatively different classes of pathways, which can be tuned by solution conditions or changing the capsid protein properties. The second example concerns carboxysomes, which are large, roughly icosahedral protein shells that facilitate carbon fixation in cyanobacteria. Carboxysomes assemble around a cargo which is topologically different from ssRNA, a noncovalently linked, amorphous complex of the enzyme RuBisCO. Motivated by this problem, we study assembly of icosahedral shells around a fluid cargo. We find different assembly pathways and different critical control parameters as compared to assembly around RNA, and that the predominant assembly pathway depends strongly on the cargo fluidity. We discuss relationships between simulated assembly pathways and recent experiments observing assembly of individual carboxysomes in bacteria.
April 12, 2016: Jonathon Howard, Yale University[Weiss Research Building, Room 301]Beat Generation: Ciliary and Flagellar Motion Driven by Cooperative Molecular MotorsHost: P. SulcThe beating patterns of sperm flagella and the breast-stroke like swimming of ciliates are driven by the molecular motor dynein. This motor generates sliding forces between adjacent microtubule doublets within the axoneme, the motile cytoskeletal structure. To create regular, oscillatory beating patterns, the activities of the dyneins must be coordinated both spatially and temporally. It is thought that coordination is mediated by stresses or strains that build up within the moving axoneme, but it is not known which components of stress or strain are involved, nor how they feed back on the dyneins. To answer this question, we measured the beating patterns of isolated, reactivate axonemes of the unicellular alga Chlamydomonas. We compared the measurements in wildtype and mutant cells with models derived from different feedback mechanisms. We found that regulation by changes in axonemal curvature was the only mechanism that accords with the measurements.
April 21, 2016: Luca Cardelli, Microsoft Research[Carson Family Auditorium]Noise Reduction in Complex Biological SwitchesHost: P. SulcCells operate in noisy molecular environments via complex regulatory networks. It is possible to understand how molecular counts are related to noise in specific networks, but it is not generally clear how noise relates to network complexity, because different levels of complexity also imply different overall number of molecules. For a fixed function, does increased network complexity reduce noise, beyond the mere increase of overall molecular counts? If so, complexity could provide an advantage counteracting the costs involved in maintaining larger networks. For that purpose, we investigate how noise affects multistable systems, where a small amount of noise could lead to very different outcomes; thus we turn to biochemical switches like the G2/M cell cycle transition switch. Our method for comparing networks of different structure and complexity is to place them in conditions where they produce exactly the same deterministic function. We are then in a good position to compare their noise characteristics relatively to their identical deterministic traces. We show that more complex networks are better at coping with both intrinsic and extrinsic noise. Intrinsic noise tends to decrease with complexity, and extrinsic noise tends to have less impact. Our findings suggest a new role for increased complexity in biological networks, at parity of function.
April 26, 2016: Arup Chakraborty, MIT [Carson Family Auditorium]How to hit HIV where it hurtsHost: P. SulcHIV continues to wreak havoc around the world, especially in poor countries. A vaccine is urgently needed to overcome this major global health challenge. I will describe key challenges that must be confronted to achieve this goal. I will then focus on some work that aims to address a part of these challenges by bringing together theory and computation (rooted in statistical physics), consideration of structures of multi-protein assemblies, basic immunology, and human clinical data. The results of these studies suggest the design of immunogens and immunization strategies for vaccines that might elicit immune responses which might be able to hit HIV where it hurts upon natural infection.
April 28, 2016: Rémi Monasson, Simona Cocco, ENS, Paris[Weiss Research Building, Room 301]Benchmarking inverse statistical approaches for protein structure and design with exactly solvable modelsHost: P. SulcInverse statistical approaches, modeling pairwise correlations between amino acids in the sequences of homologous proteins across many different organisms, can successfully extract protein structure (contact) information. Here, we benchmark those statistical approaches on exactly solvable models of proteins, folding on a 3D lattice, to assess the reasons underlying their success and their limitations. We show that the inferred parameters (effective pairwise interactions) of the statistical models have clear and quantitative interpretations in terms of positive (favoring the native fold) and negative (disfavoring competing folds) protein sequence design. New sequences randomly drawn from the statistical models are likely to fold into the native structures when effective pairwise interactions are accurately inferred, a performance which cannot be achieved with independent-site models.
May 3, 2016: Hiro Matsunami, Duke University[Weiss Research Building, Room 301]Mammalian odorant receptors: deorphanization, trafficking and gene choiceHost: M. MagnascoImpressive progress in membrane biology has revealed important relationships in G-protein coupled receptor (GPCR) structure and function. Despite this, understanding of the largest family of GPCRs, the mammalian odorant receptors (ORs), lags behind. To date, there is no crystal structure of any ORs and many remain orphans without known ligands. These challenges must be overcome in order to understand the molecular mechanisms of olfaction. We have developed a new strategy that enables comprehensive screening of ORs in freely behaving animals by odor stimulation. We combine phosphorylated ribosomal protein S6 immunoprecipitation with next generation sequencing to profile OR expression in active olfactory sensory neurons. This method is capable of not only identifying a repertoire of odorant-OR pairs, but also reveals the most robust and sensitive ORs. This deorphanization is key to understanding structure-function relationships of odorant-OR interactions. Poor cell surface expression of ORs in heterologous cells represents a major challenge in functional studies of ORs. We previously identified the RTP family of accessory proteins that facilitate OR cell surface expression, and used them for functional analysis in heterologous cells. A transcriptomic and in situ hybridization analysis of olfactory mucosa of RTP1 and RTP2 knockout mice has revealed that the majority of ORs are downregulated, whereas a small subset of ORs are upregulated. This subset of ORs demonstrate expression at the cell surface in heterologous systems, suggesting an unexpected connection between OR protein trafficking and gene choice.
May 10, 2016: Alexandre Pouget, Université de Genève [Weiss Research Building, Room 301]Learning and demixing in the olfactory systemHost: C. Kirst
May 17, 2016: Nicolas Brunel, University of Chicago [Carson Family Auditorium]Inferring learning rules in cortical circuitsHost: C. KirstUnderstanding the mechanisms of learning and memory is one of the major challenges in neuroscience. The dominant theory holds that information about sensory inputs is stored in cortical circuits thanks to synaptic plasticity. In spite of decades of research, the exact rules governing how synapses change as a function of the activity of pre and post-synaptic neurons remain the subject of debate. In this talk, I will present two novel approaches for investigating the mechanisms of learning and memory. The first consists in inferring a learning rule from in vivo data, using experiments comparing the statistics of responses of neurons to large sets of novel and familiar stimuli. The second consists in exploring the consequences of an information optimization principle on the statistics of synaptic connectivity. I will show how methods from statistical physics can be used to characterize the statistics of connectivity in networks that optimize information storage, and compare the theoretical results with available data.
May 24, 2016: Christopher Jarzynski, University of Maryland[Weiss Research Building, Room 301]Irreversibility, information and the second law of thermodynamics at the nanoscaleHost: P. SulcWhat do the laws of thermodynamics look like, when applied to microscopic systems such as optically trapped colloidal particles, single molecules manipulated with laser tweezers, and biomolecular machines? In recent years it has become apparent that the fluctuations of small systems far from thermal equilibrium satisfy strong and unexpected laws, which allow us to rewrite familiar inequalities of macroscopic thermodynamics as equalities. These results in turn have spurred a renewed interest in the feedback control of small systems and the closely related Maxwell’s demon paradox. I will describe some of this progress, and will argue that it has refined our understanding of irreversibility, the second law, and the thermodynamic arrow of time.
May 26, 2016: Jean-Pierre Eckmann, University of Geneva[Carson Family Auditorium]The geometry of the genotype-to-phenotype map of proteins: dimension, correlation and spectrumHost: P. SulcI will report on work with Tsvi Tlusty on how one can envisage a concrete map between the genetic information contained in the DNA sequence and mechanical function of the protein. The simplicity of our model allows for an extensive survey of the "protein universe", spanning a huge number of generations and samples, far beyond what can be done in real living matter. This helps in understanding how mechanical constraints on the function of the protein force the system into a very small subset of possible states. Evolution can be described in terms of a low-dimensional random walk on this subset of an almost infinite-dimensional space. This is also the origin of tight correspondence between the spectrum of functional DNA sequences and the mechanical modes of the protein.
September 20, 2016: Alex Mogilner, NYUSpontaneous and induced cell polarization and collective migrationHost: P. SulcFish keratocyte cells served as the model system to understand biophysics of cell motility for decades. Recently, we combined experiment and modeling to understand the mechanism of polarization of these cells. We found that two essential feedbacks - positive one between myosin density and actin flow, and negative one between stick-slip adhesions and actin flow - underlie the motility initiation. Interestingly, keratocytes polarize in electric fields much faster but not stably, through different mechanism. I will also describe preliminary results on collective keratocyte migration in electric fields.
September 27, 2016: David Pine, NYUDNA-directed self-assembly of colloidal crystals: diamond and pyrochloreHost: P. SulcCoating colloidal particles with DNA is emerging as a new way to direct self assembly. In principle, it allows one to program the assembly of different materials in almost any way imaginable. Here we describe recent progress, which includes the introduction of valence and novel superlattices to create new colloidal structures for photonic applications.
October 4, 2016: Philip Kim, University of TorontoIntegrating computational and experimental methods in proteomics and drug discovery"Host: P. SulcI will present our advances in combining computational and experimental techniques to develop novel inhibitors. We have developed an integrated pipeline that first computationally designs large libraries of potential inhibitors and can then screen these for either cellular phenotype or high affinity binding. I will showcase this pipeline on two example applications, first for developing inhibitors to protein-protein interactions and second for developing novel high-affinity biologics.
October 11, 2016: Mehran Kardar, MITForce from non-equilibrium fluctuations in QED and Active MatterHost: P. SulcEquilibrium fluctuation-induced forces are abundant in nature, ranging from quantum electrodynamic (QED) Casimir and van der Waals forces, to their thermal analogs in fluctuating soft matter. Manifestations of QED fluctuations out of thermal equilibrium are also well-known, as in the Stefan-Boltzmann laws of radiation pressure and heat transfer. These laws, however, acquire non-trivial twists in the near-field regime of sub-micron separations, and in the proximity of moving surfaces. I will discuss dissipation in moving steady states, and the non-Gaussian fluctuations of a particle in a quantum bath. Non-equilibrium fluctuation forces for particulate matter also hold surprises which I present in the contexts of diffusive transport, and active matter: For the simple case of a current of diffusive particles between parallel slabs, we find a force that falls off with slab separation d as kT/d (at temperature T, and in all spatial dimensions), but that can be attractive or repulsive. There is also a universal transient force when a system of particles undergoes temperature quench or sudden agitation. For a wide wide class of active systems, we find that the pressure exerted on a container depends on details of interactions with the confining walls, as well as wall curvature and asymmetry.
October 18, 2016: Yuhai Tu, IBM ResearchPhysics of information processing in living systems: on sensory adaptation and biological oscillationsHost: P. SulcLiving organisms need to obtain and process information that are crucial for their survival. Information processing in living systems, ranging from signal transduction in a single cell to image processing in the human brain, are performed by biological circuits (networks of interacting bio-molecules or neurons), which are inherently noisy. However, certain accuracy is required to carry out proper biological functions. How do biological networks process information with noisy components? What is the free energy cost of accurate biological computing? Are there fundamental physics principles underlying the performance of these biological circuits? In this talk, we will describe our recent work in trying to address these general questions in the context of two basic cellular computing tasks: sensory adaptation for memory encoding; biochemical oscillation for accurate timekeeping.
October 25, 2016: Alexander Grosberg, NYUActivity induced phase separation in particles and (bio)polymersHost: P. SulcParticles may phase separate because they are of different sizes, of different shapes, or interact differently. But there is also the possibility that they separate based on the different level of activity. I will present a simple model which illustrates this idea. I will also discuss how situation changes if particles are connected to form a polymer chain, and speculate about possible implications of these results.
November 1, 2016: Jeff Hammerbacher, Icahn Institute at Mount SinaiTumor neoepitope selection for biomarker discovery and therapeutic vaccinationHost: P. SulcWe'll review some open source software our lab has developed to facilitate a Phase I clinical trial of a personalized therapeutic vaccine targeting tumor neoepitopes. We'll also present some results from our analysis of clinical trials of checkpoint blockade in 3 different cancer types and some open source software we've created to facilitate similar analyses.
November 8, 2016: Eric Vanden-Eijnden, NYUNon-equilibrium transitions between metastable patterns in populations of motile bacteriaHost: P. SulcActive materials can self-organize in many more ways than their equilibrium counterparts. For example, self-propelled particles whose velocity decreases with their density can display motility-induced phase separation (MIPS), a phenomenon building on a positive feedback loop in which patterns emerge in locations where the particles slow down. Here, we investigate the effects of intrinsic fluctuations in the system's dynamics on MIPS, using a field theoretic description building on results by Cates and collaborators. We show that these fluctuations can lead to transitions between metastable patterns. The pathway and rate of these transitions is analyzed within the realm of large deviation theory, and they are shown to proceed in a very different way than one would predict from arguments based on detailed-balance and microscopic reversibility. Specifically, we show that these transitions involve fluctuations in diffiusivity of the bacteria followed by fluctuations in their population, in a specific sequence. The method of analysis proposed here, including its numerical component, can be used to study noise-induced non-equilibrium transitions in a variety of other non-equilibrium set-ups, and leads to predictions that are verifiable experimentally.
November 15, 2016: Elodie Ghedin (NYU)Dynamics of influenza virus transmissionHost: P. SulcAbstract: The characterization of virus populations by deep sequencing is transforming our understanding of viral evolutionary dynamics. This enables us to address questions about the extent of within-host virus diversity and what proportion of this diversity is transmitted between infected hosts. Using the same tools we can also query the host environment in which the virus evolves—such as host microbial ecology and local response to infection—to determine its effect on virus evolution. I will discuss how we quantify virus diversity and characterize virus variants that achieve sustainable transmission, and illustrate how immune status, the respiratory microbiome, and mixed infections can shape influenza virus transmission.
November 22, 2016: Armita Nourmohammad (Princeton University)Effective theory for immune-pathogen coevolutionHost: P. SulcWe normally think of evolution occurring in a population of organisms, in response to their external environment. Rapid evolution of cellular populations also occurs within our bodies, as the adaptive immune system works to eliminate infection. Some pathogens, such as HIV, are able to persist in a host for extended periods of time, during which they evolve to evade the immune response. In this talk I will introduce an analytical framework for the rapid coevolution of B-cell and viral populations. I will quantify the amount of out-of-equilibrium adaptation in each of the two populations by analysis of their co-evolutionary history. I will discuss the consequences of competition between lineages of antibodies, and characterize the fate of a given lineage dependent on the state of the antibody and viral populations. In particular, I will discuss the conditions for emergence of highly potent broadly neutralizing antibodies, which are now recognized as critical for designing an effective vaccine against HIV.
November 29, 2016: Alessandra Carbone, University of Paris VIConservation, co-evolution and dynamics: from sequences to functionsHost: P. SulcBiology entered a new era, with computational biology producing biological data that are impossible nowadays to obtain with wet experiments. Tackling biological questions with advanced engineering, new computer algorithms and novel computational approaches is a challenge that will lead to revolutionize biology and medicine through deeper, ubiquitous use of DNA information. A fundamental question is the extraction of evolutionary information from DNA sequences. Here, we consider protein sequences and structures, and describe how important biological information on protein-protein binding sites and on mechanical and allosteric properties of proteins can be extracted. Among different examples, we shall present a computational approach to protein-protein interactions that we developed within a project on protein network reconstruction on neuromuscular diseases. The project demands a high computational power to test billions of interactions, it ran on the machines of the World Community Grid for more than 3 years, and provided a huge amount of information on the interaction of human proteins. High Performance Computing helped to obtain an unprecedented amount of information on protein-protein interactions between real partners but also, and most importantly, between non-partners.
December 6, 2016: Eugene Shakhnovich, Harvard UniversityUnderstanding evolution on multiple scales: from protein physics to population genetics and back.Host: P. SulcBiological phenomena unfold in a broad range of scales ranging from molecules to cells to populations and ecosystems. Variation of molecular properties of biomolecules profoundly impact the ability of cells to survive and propagate (fitness). Finally, the fate of a mutation is decided by Darwinian selection on the level of the population, where three outcomes are possible: fixation in the population, elimination by purifying selection or separation in the population in a subdominant clone (polymorphism). In this lecture I will outline my lab’s and others efforts in an emerging new field which merges molecular mechanism with evolution. I will discuss new models of evolutionary dynamics on biophysical fitness landscapes. Traditional population genetics models are agnostic to the physical-chemical nature of mutational effects. Rather they operate with an a’priori assumed distributions of fitness effects (DFE) of mutations from which evolutionary dynamics are derived. In departure with this tradition the novel multiscale models integrate the molecular effects of mutations on physical properties of proteins into physically intuitive yet detailed genotype-phenotype relationship (GPR) assumptions. I will present a range of models from simple analytical diffusion-based model on biophysical fitness landscapes to more sophisticated computational models of populations of model cells where genetic changes are mapped into molecular effects using biophysical modeling of proteins and ensuing fitness changes determine the fate of mutations in realistic population dynamics. Examples of insights derived from biophysics-based multiscale models include the fundamental limit on mutation rates in living organisms, physics of thermal adaptation, co-evolution of protein interactions and abundances in cytoplasm and related results, some of which I will briefly present and discuss. Next, I will present major results from novel “bottom-up” experimental approach to study evolutionary dynamics on biophysical fitness landscapes. The approach spans all scales of biological organization involving concurrent use of genome editing, biophysical characterization of molecular effects of mutations, high throughput proteomic analysis at the systems level and phenotypic analysis. It validates and further develops the concept of biophysical fitness landscapes by showing that certain combinations of molecular traits can serve as a universal predictor of fitness effects of mutations. Thus linking fitness effects to intermediate phenotype – molecular and cellular effects of mutations – provides a comprehensive low-dimensional mapping of genotype to phenotype – a biophysical fitness landscape - on which evolutionary dynamics unfolds.
December 20, 2016 Ned Seeman, NYUDNA: Not Merely the Secret of LifeHost: P. SulcThe essence of Structural DNA Nanotechnology is the combination of branched DNA molecules combined with interactions that can be prescribed by Watson-Crick base pairing. The key goals of the area include the production of objects, lattices and nanomechanical devices made from DNA, as well as controlling the positions of other materials. By the middle 1990s, geometrical control was achieved, leading well-defined objects, often objects acting as tiles for 2D lattices. . Nanorobotics is a key area of application. We have made robust 2-state and 3-state sequence-dependent devices and bipedal walkers. We have constructed a molecular assembly line using a DNA origami layer and three 2-state devices, so that there are eight different states represented by their arrangements. All eight products can be built from this system. Organization of other materials by DNA is another key goal. We have placed differently-sized gold nanoparticles in a checkerboard array in 2D, and in specific positions in 3D. We have also placed carbon nanotubes on DNA origami in specific positions. There is an empirical rule stating that the best arrays in multidimensional DNA systems result when helix axes span each dimension. We have self-assembled a 2D crystalline origami array by applying this rule. We used the same rule to self-assemble a 3D crystalline array. We initially reported its crystal structure to 4 Å resolution, but rational design of intermolecular contacts has enabled us to improve the crystal resolution to better than 3 Å. We can use crystals with two molecules in the crystallographic repeat to control the color of the crystals. We can change the color of crystals by doing strand displacement of duplex DNA; we can also color the crystals using triplex formation. When tailed in DNA, we can add semiconductors to the crystals, and follow their transitions by crystal color. The use of the crystals to host guests promises an approach to the organization of macromolecules in 3D. Diffraction of the crystals offers a means to ascertain the successful construction of their targets and the characterization of their guests. This Research was supported by MURI W911NF-11-1-0024 from ARO, N000141110729 from ONR, grants EFRI-1332411 and CCF-1526650 from the NSF, DE-SC0007991 from DOE for DNA synthesis and partial salary support, and grant GBMF3849 from the Gordon and Betty Moore Foundation.
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