Publications

The translation and shape deformations of a passive viscous Newtonian droplet immersed in an active nematic liquid crystal under circular confinement are analyzed using a linear stability analysis. We focus on the case of a sharply aligned active nematic in the limit of strong elastic relaxation in two dimensions. Using an active liquid crystal model, we employ the Lorentz reciprocal theorem for Stokes flow to study the growth of interfacial perturbations as a result of both active and elastic stresses. Instabilities are uncovered in both extensile and contractile systems, for which growth rates are calculated and presented in terms of the dimensionless ratios of active, elastic, and capillary stresses, as well as the viscosity ratio between the two fluids. We also extend our theory to analyze the inverse scenario, namely, the stability of an active nematic droplet surrounded by a passive viscous layer. Our results highlight the subtle interplay of capillary, active, elastic, and viscous stresses in governing droplet stability. The instabilities uncovered here may be relevant to a plethora of biological active systems, from the dynamics of passive droplets in bacterial suspensions to the organization of subcellular compartments inside the cell and the cell nucleus.

Cystic fibrosis (CF) is due to loss-of-function variants of the CF transmembrane conductance regulator (CFTR) channel. The most effective treatment for people with CF carrying the F508del mutation is the triple combination of elexacaftor–tezacaftor–ivacaftor (ETI). ETI can correct the underlying defect(s) in other CFTR mutants. The use of disease-relevant predictive models such as patient-derived human nasal epithelial cells allow to investigate the response to CFTR modulators of specific genotypes, possibly supporting patients' access to treatment.

An obstacle is immersed in an externally driven 2D Stokes or Navier-Stokes fluid. We study the self-equilibration conditions for that obstacle under steady state assumptions on the flow. We then seek to optimize the translational and/or angular velocity of the obstacle by varying its shape. To allow general variations, we must consider a very large class of obstacles for which the notion of trace is meaningless. This forces us to revisit the notion of self-equilibration for both Stokes and Navier-Stokes in a measure theoretic environment.

How thousands of microtubules and molecular motors self-organize into spindles remains poorly understood. By combining static, nanometer-resolution, large-scale electron tomography reconstructions and dynamic, optical-resolution, polarized light microscopy, we test an active liquid crystal continuum model of mitotic spindles in human tissue culture cells. The predictions of this coarse-grained theory quantitatively agree with the experimentally measured spindle morphology and fluctuation spectra. These findings argue that local interactions and polymerization produce collective alignment, diffusive-like motion, and polar transport which govern the behaviors of the spindle's microtubule network, and provide a means to measure the spindle's material properties. This work demonstrates that a coarse-grained theory featuring measurable, physically-interpretable parameters can quantitatively describe the mechanical behavior and self-organization of human mitotic spindles.

The male fruit fly produces ~1.8 mm long sperm, thousands of which can be stored until mating in a ~200 micron sac, the seminal vesicle. While the evolutionary pressures driving such extreme sperm (flagellar) lengths have long been investigated, the physical consequences of their gigantism are unstudied. Through high-resolution three-dimensional reconstructions of in vivo sperm morphologies and rapid live imaging, we discovered that stored sperm are organized into a dense and highly aligned state. The packed flagella exhibit system-wide collective 'material' flows, with persistent and slow-moving topological defects; individual sperm, despite their extraordinary lengths, propagate rapidly through the flagellar material, moving in either direction along material director lines. To understand how these collective behaviors arise from the constituents' nonequilibrium dynamics, we conceptualize the motion of individual sperm as topologically confined to a reptation-like tube formed by its neighbors. Therein, sperm propagate through observed amplitude-constrained and internally driven flagellar bending waves, pushing off counter-propagating neighbors. From this conception, we derive a continuum theory that produces an extensile material stress that can sustain an aligned flagellar material. Experimental perturbations and simulations of active elastic filaments verify our theoretical predictions. Our findings suggest that active stresses in the flagellar material maintain the sperm in an unentangled, hence functional state, in both sexes, and establish giant sperm in their native habitat as a novel and physiologically relevant active matter system

The brain encodes external stimuli through patterns of neural activity, forming internal representations of the world. Increasing experimental evidence showed that neural representations for a specific stimulus can change over time in a phenomenon called “representational drift” (RD). However, the underlying mechanisms for this widespread phenomenon remain poorly understood. Here, we study RD in the piriform cortex of the olfactory system with a realistic neural network model that incorporates two general mechanisms for synaptic weight dynamics operating at two well-separated timescales: spontaneous multiplicative fluctuations on a scale of days and spike-timing-dependent plasticity (STDP) effects on a scale of seconds. We show that the slow multiplicative fluctuations in synaptic sizes, which lead to a steady-state distribution of synaptic weights consistent with experiments, can induce RD effects that are in quantitative agreement with recent empirical evidence. Furthermore, our model reveals that the fast STDP learning dynamics during presentation of a given odor drives the system toward a low-dimensional representational manifold, which effectively reduces the dimensionality of synaptic weight fluctuations and thus suppresses RD. Specifically, our model explains why representations of already “learned” odors drift slower than unfamiliar ones, as well as the dependence of the drift rate with the frequency of stimulus presentation—both of which align with recent experimental data. The proposed model not only offers a simple explanation for the emergence of RD and its relation to learning in the piriform cortex, but also provides a general theoretical framework for studying representation dynamics in other neural systems.

Studies in Drosophila have contributed a great deal to our understanding of developmental mechanisms. Indeed, familiar names of critical signaling components, such as Hedgehog and Notch, have their origins in the readily identifiable morphological phenotypes of Drosophila. Most studies that led to the identification of these and many other highly conserved genes were based on the end-point phenotypes, such as the larval cuticle or the adult wing. Additional information can be extracted from longitudinal studies, which can reveal how the phenotypes emerge over time. Here we present the Fruit Fly Auxodrome, an experimental setup that enables monitoring and quantitative analysis of the entirety of development of 96 individually housed Drosophila from hatching to eclosion. The Auxodrome combines an inexpensive live imaging setup and a computer vision pipeline that provides access to a wide range of quantitative information, such as the times of hatching and pupation, as well as dynamic patterns of larval activity. We demonstrate the Auxodrome in action by recapitulating several previously reported features of wild-type development as well as developmental delay in a Drosophila model of a human disease. The scalability of the presented design makes it readily suitable for large-scale longitudinal studies in multiple developmental contexts.

Although canonical protein design has benefited from machine learning methods trained on databases of protein sequences and structures, synthetic heteropolymer design still relies heavily on physics-based methods. The Rosetta software, which provides diverse physics-based methods for designing sequences, exploring conformations, docking molecules, and performing analysis, has proven invaluable to this field. Nevertheless, Rosetta’s aging architecture, monolithic structure, non-open source code, and steep development learning curve are beginning to hinder new methods development. Here, we introduce the Masala software suite, a free, open-source set of C++ libraries intended to extend Rosetta and other software, and ultimately to be a successor to Rosetta. Masala is structured for modern computing hardware, and its build system automates the creation of application programming interface (API) layers, permitting Masala’s use as an extension library for existing software, including Rosetta. Masala features modular architecture in which it is easy for novice developers to add new plugin modules, which can be independently compiled and loaded at runtime, extending functionality of software linking Masala without source code alteration. Here, we describe implementation of Masala modules that accelerate protein and synthetic peptide design. We describe the implementation of Masala real-valued local optimizers and cost function network optimizers that can be used as drop-in replacements for Rosetta’s minimizer and packer when designing heteropolymers. We explore design-centric guidance terms for promoting desirable features, such as hydrogen bond networks, or discouraging undesirable features, such as unsatisfied buried hydrogen bond donors and acceptors, which we have re-implemented far more efficiently in Masala, providing up to two orders of magnitude of speedup in benchmarks. Finally, we discuss development goals for future versions of Masala.

Viruses exploit host cell reliance on compartmentalization to facilitate their replication. Herpes simplex virus type 1 (HSV-1) modulates the subcellular localization of host proteins to suppress immune activation, license viral gene expression, and achieve translational shutoff. To spatially resolve dynamic protein-protein interaction (PPI) networks during infection with an immunostimulatory HSV-1 strain, we integrated nuclear/cytoplasmic fractionation with thermal proximity coaggregation analysis (N/C-TPCA). The resulting expanded depth and spatial resolution of PPIs charted compartment-specific assemblies of protein complexes throughout infection. We find that a broader suite of host chaperones than previously anticipated exhibits nuclear recruitment to form condensates known as virus-induced chaperone-enriched (VICE) domains. Monitoring protein and RNA constituents and ribosome activity, we establish that VICE domains sequester ribosome biogenesis factors from ribosomal RNA, accompanying a cell-wide defect in ribosome supply. These findings highlight infection-driven VICE domains as nodes of translational remodeling and demonstrate the utility of N/C-TPCA to study dynamic biological contexts.

A lack of tools for detecting receptor activity in vivo has limited our ability to fully explore receptor-level control of developmental patterning. Here, we extend phospho-tyrosine tag (pYtag) biosensors to visualize endogenous receptor tyrosine kinase (RTK) activity in Drosophila. We build biosensors for three RTKs that function across developmental stages and tissues. By characterizing Torso::pYtag during embryonic terminal patterning, we find that Torso activity differs from downstream extracellular signal-regulated kinase (ERK) activity in two surprising ways: Torso activity is narrowly restricted to the poles but produces a broader gradient of ERK and decreases over developmental time, while ERK activity is sustained, an effect mediated by ERK pathway-dependent negative feedback. Our results suggest that a narrow domain of Torso activity, tuned in amplitude by negative feedback, locally activates signaling effectors, which diffuse through the syncytial embryo to form the ERK gradient. Altogether, the results of this work highlight the usefulness of pYtags for investigating receptor-level regulation of developmental patterning.