Below is an overview of my previous research spanning undergraduate, graduate school and postdoctoral work, grouped by topic and sorted in reverse chronological order.
For an introduction to nucleic acid phase separation, please see our recent review published in Reports on Progress in Physics, written with Omar Saleh, Gabrielle Abraham, Aria Chaderjian, and Anna Nguyen.
Cells operate in part by compartmentalizing chemical reactions. For example, recent work has shown that chromatin, the material that contains the cell's genome, can auto-regulate its structure by utilizing reaction products (proteins, RNA) to compartmentalize biomolecules via liquid-liquid phase separation (LLPS). Here, we develop a model biomolecular system that permits quantitative investigation of such dynamics, particularly by coupling a phase-separating system of DNA nanostars to an in vitro transcription reaction. The DNA nanostars' sequence is designed such that they self-assemble into liquid droplets only in the presence of a transcribed single-stranded RNA linker. We find that nanostar droplets form with a substantial delay and non-linear response to the kinetics of RNA synthesis. In addition, we utilize the compartments generated by the phase-separation process to engineer an activator/repressor network, where the transcription reaction activates the formation of droplets, and then droplets suppress the transcription reaction by segregating transcription components inside them. Our work on transcription-driven liquid-liquid phase separation constitutes a robust and programmable platform to explore non-equilibrium reaction-phase transition dynamics and could also provide a foundation to understand the dynamics of transcriptional condensate assembly in cells.
Liquid–liquid phase separation in biology has recently been shown to play a major role in the spatial control of biomolecular components within the cell. However, as they are phase transitions, these processes also display nontrivial dynamics. By measuring the delay time for phase-separated droplets to appear, we demonstrate that the dynamics of DNA nanostar phase separation reflect that of a metastable binary mixture of patchy particles. For sufficiently deep temperature quenches, droplets undergo spinodal decomposition and grow spontaneously, driven by Brownian motion and coalescence of phase-separated droplets, as confirmed by comparing experimental measurements to particle-based simulations. Near the coexistence boundary, droplet growth slows substantially, indicative of a nucleation process. These dynamical principles are relevant to behaviors associated with liquid–liquid phase separating systems, such as their spatial patterning, reaction coupling, and biological function.
Recently, an extraordinary amount of research has investigated various aspects of biomolecular liquid-liquid phase separation—the spontaneous separation of biomolecules into liquid droplets. Here, we report a quite clear and surprising experimental result: The droplet-droplet structure is “hyperuniform.” The emerging science of hyperuniformity describes systems that appear at first glance to be randomly distributed, yet upon analysis display a hidden order involving, over long length scales, an unexpected regularity in the location of particles. In our experiments, we investigate DNA nanostars, star-shaped synthetic DNA particles that interact to form liquid droplets. We find that, upon phase separation, the nanostar droplets spontaneously form hyperuniform structures. The underlying mechanisms driving hyperuniformity are pervasive in physics, chemistry, astronomy, and biology. Our work opens potential applications by using hyperuniform droplets as probes of complex materials or as seed materials with structures that give rise to unique photonic or mechanical properties.
In periodically sheared suspensions there is a dynamical phase transition, characterized by a critical strain amplitude, between an absorbing state, where particle trajectories are reversible and an active state, where trajectories are chaotic and diffusive. A simple model called random organization qualitatively reproduces the dynamical features of this transition. Random organization and other absorbing state models exhibit hyperuniformity, a strong suppression of density fluctuations on long length scales at criticality. Here we show experimentally that the particles in periodically sheared suspensions organize into structures with anisotropic short-range order but isotropic, long-range hyperuniform order when oscillatory shear amplitudes approach critical.
Sphere packing is an ancient problem. The densest packing is known to be a face-centered cubic (FCC) crystal, with space-filling fraction 𝜋/√18≈0.74. The densest “random packing,” random close packing (RCP), is yet ill defined, although many experiments and simulations agree on a value ≈0.64. We introduce a simple model, biased random organization (BRO), which exhibits a Manna class dynamical phase transition between absorbing and active states that has RCP as its densest critical point and, like other Manna models, is hyperuniform at criticality. The configurations we obtain from BRO appear to be structurally identical to RCP configurations from other protocols. This leads us to conjecture that the highest-density absorbing state for an isotropic BRO model produces an ensemble of configurations that characterizes the state conventionally known as RCP.
A simple dynamical model, biased random organization (BRO), appears to produce configurations known as random close packing (RCP) as BRO’s densest critical point in dimension 𝑑=3. We conjecture that BRO likewise produces RCP in any dimension; if so, then RCP does not exist in 𝑑=1–2 (where BRO dynamics lead to crystalline order). In 𝑑=3–5, BRO produces isostatic configurations and previously estimated RCP volume fractions. We find that BRO belongs to the Manna universality class of dynamical phase transitions by measuring critical exponents associated with the steady-state activity and the long-range density fluctuations. Additionally, BRO’s distribution of near contacts (gaps) displays behavior consistent with the infinite-dimensional theoretical treatment of RCP when 𝑑≥4. The association of BRO’s densest critical configurations with random close packing implies that RCP’s upper-critical dimension is consistent with the Manna class 𝑑=4.
Liquid droplets of biomolecules serve as organizers of the cellular interior and are of interest in biosensing and biomaterials applications. Here, we investigate means to tune the interfacial properties of a model biomolecular liquid consisting of multi-armed DNA 'nanostar' particles. We find that long DNA molecules that have binding affinity for the nanostars are preferentially enriched on the interface of nanostar droplets, thus acting as surfactants. Fluorescent measurements indicate that, in certain conditions, the interfacial density of the surfactant is around 20 per square micron, indicative of a sparse brush-like structure of the long, polymeric DNA. Increasing surfactant concentration leads to decreased droplet size, down to the sub-micron scale, consistent with droplet coalesence being impeded by the disjoining pressure created by the brush-like surfactant layer. Added DNA surfactant also keeps droplets from adhering to both hydrophobic and hydrophilic solid surfaces, apparently due to this same disjoining effect of the surfactant layer. We thus demonstrate control of the size and adhesive properties of droplets of a biomolecular liquid, with implications for basic biophysical understanding of such droplets, as well as for their applied use.
Liquid droplets of biomolecules play key roles in organizing cellular behavior, and are also technologically relevant, yet physical studies of dynamic processes of such droplets have generally been lacking. Here, we investigate and quantify the dynamics of formation of dilute internal inclusions, i.e., vacuoles, within a model system consisting of liquid droplets of DNA ‘nanostar’ particles. When acted upon by DNA-cleaving restriction enzymes, these DNA droplets exhibit cycles of appearance, growth, and bursting of internal vacuoles. Analysis of vacuole growth shows their radius increases linearly in time. Further, vacuoles pop upon reaching the droplet interface, leading to droplet motion driven by the osmotic pressure of restriction fragments captured in the vacuole. We develop a model that accounts for the linear nature of vacuole growth, and the pressures associated with motility, by describing the dynamics of diffusing restriction fragments. The results illustrate the complex non-equilibrium dynamics possible in biomolecular condensates.
We study the driven collective dynamics of a colloidal monolayer sedimenting down an inclined plane. The action of the gravity force parallel to the bottom wall creates a flow around each colloid, and the hydrodynamic interactions among the colloids accelerate the sedimentation as the local density increases. This leads to the creation of a universal “triangular” inhomogeneous density profile, with a traveling density shock at the leading front moving in the downhill direction. Unlike density shocks in a colloidal monolayer driven by applied torques rather than forces [Phys. Rev. Fluids 2, 092301(R) (2017)], the density front during sedimentation remains stable over long periods of time even though it develops a roughness on the order of tens of particle diameters. Through experimental measurements and particle-based computer simulations, we find that the Burgers equation can model the density profile along the sedimentation direction as a function of time remarkably well, with a modest improvement if the nonlinear conservation law accounts for the sublinear dependence of the collective sedimentation velocity on density.
Rapid prototyping by combining evolutionary computation with simulations is becoming a powerful tool for solving complex design problems in materials science. This method of optimization operates in a virtual design space that simulates potential material behaviors and after completion needs to be validated by experiment. However, in principle an evolutionary optimizer can also operate on an actual physical structure or laboratory experiment directly, provided the relevant material parameters can be accessed by the optimizer and information about the material's performance can be updated by direct measurements. Here we provide a proof of concept of such direct, physical optimization by showing how a reconfigurable, highly nonlinear material can be tuned to respond to impact. We report on an entirely computer controlled laboratory experiment in which a 6×6 grid of electromagnets creates a magnetic field pattern that tunes the local rigidity of a concentrated suspension of ferrofluid and iron filings. A genetic algorithm is implemented and tasked to find field patterns that minimize the force transmitted through the suspension. Searching within a space of roughly 10^10 possible configurations, after testing only 1500 independent trials the algorithm identifies an optimized configuration of layered rigid and compliant regions.
We use experiments and minimal numerical models to investigate the rapidly expanding monolayer formed by the impact of a dense suspension drop against a smooth solid surface. The expansion creates a lacelike pattern of particle clusters separated by particle-free regions. Both the expansion and the development of the spatial inhomogeneity are dominated by particle inertia and, therefore, are robust and insensitive to details of the surface wetting, capillarity, and viscous drag.