ABSTRACT
Determining the physical and chemical properties of biologically important particles such as cells, organelles, viruses, exosomes, complexes, nucleotides, and proteins is needed to understand their function. These properties are determined with common analytical tools (mass spectrometry, cryo-EM, NMR, various spectroscopies, nucleotide sequencing, etc.) whose function can be improved when samples are pure and concentrated. Separations science plays a central role in conditioning samples, ranging from low-resolution benchtop operations like precipitations or extractions to higher-resolution chromatography and electrophoresis. In the last two decades, gradient insulator-based dielectrophoresis (g-iDEP) has emerged as a high-resolution separation technique capable of highly selective enrichment of cells, viruses, exosomes, and proteins. Specific evidence has been shown that pure homogeneous and concentrated fractions of cells and exosomes can be generated from complex mixtures. However, recovering those fractions for analysis has not been developed, limiting the technique to an analytical rather than a preparative one. Here, a finite element analysis was undertaken to identify geometries and operational parameters to efficiently remove the enriched fraction while retaining maximum concentration and providing total mass transfer. Geometric factors (e.g., side channel width and distance from the gradient-inducing gap) were studied, along with the addition of a second inlet side channel. Two flow-generating mechanisms-electroosmosis and hydrostatic pressure-were evaluated for semi-optimized device designs, including a comparison of the one- and two-inlet designs. Simulations indicate effectively one hundred percent mass transfer and a concentration increase by an order of magnitude for several device configurations and operational parameters.
Subject(s)
Electroosmosis , Microfluidic Analytical Techniques , Electrophoresis/methods , Electroosmosis/methods , Lab-On-A-Chip DevicesABSTRACT
Recently, trapped-particle experiments have probed the instantaneous velocity of Brownian motion revealing that, at early times, hydrodynamic history forces dominate Stokes damping. In these experiments, nonuniform particle motion is well described by the Basset-Boussinesq-Oseen (BBO) equation, which captures the unsteady Basset history force at a low Reynolds number. Building off of these results, earlier we showed that, at low temperature, BBO particles could exploit fluid inertia in order to overcome potential barriers (generically modeled as a tilted washboard), while its Langevin counter-part could not. Here, we explore the behavior of neutrally buoyant BBO particles at finite temperature for moderate Stokes damping. Remarkably, we find that the transport of particles injected into a bumpy potential with sufficiently high barriers can be completely quenched at intermediate temperatures, whereas itinerancy may be possible above and below that temperature window. This effect is present for both Langevin and BBO dynamics, though these occur over drastically different temperature ranges. Furthermore, hydrodynamic memory mitigates these effects by sustaining initial particle momentum, even in the difficult intermediate temperature regime.
ABSTRACT
We obtain a numerical solution of the equation for the synchronous unsteady motion of two spherical vesicles in incompressible viscous fluid in the presence of both Stokes drag and hydrodynamics memory. We find that for a given amount of work performed, the final distance traveled by each vesicle is increased by the presence of the other vesicle moving in the same direction. The result suggests that the unsteady transport of the vesicles by molecular motors in vivo may be facilitated due to an effective hydrodynamic interaction between the neighboring vesicles.
ABSTRACT
[This corrects the article DOI: 10.1371/journal.pcbi.1004568.].
ABSTRACT
Diverse classes of proteins function through large-scale conformational changes and various sophisticated computational algorithms have been proposed to enhance sampling of these macromolecular transition paths. Because such paths are curves in a high-dimensional space, it has been difficult to quantitatively compare multiple paths, a necessary prerequisite to, for instance, assess the quality of different algorithms. We introduce a method named Path Similarity Analysis (PSA) that enables us to quantify the similarity between two arbitrary paths and extract the atomic-scale determinants responsible for their differences. PSA utilizes the full information available in 3N-dimensional configuration space trajectories by employing the Hausdorff or Fréchet metrics (adopted from computational geometry) to quantify the degree of similarity between piecewise-linear curves. It thus completely avoids relying on projections into low dimensional spaces, as used in traditional approaches. To elucidate the principles of PSA, we quantified the effect of path roughness induced by thermal fluctuations using a toy model system. Using, as an example, the closed-to-open transitions of the enzyme adenylate kinase (AdK) in its substrate-free form, we compared a range of protein transition path-generating algorithms. Molecular dynamics-based dynamic importance sampling (DIMS) MD and targeted MD (TMD) and the purely geometric FRODA (Framework Rigidity Optimized Dynamics Algorithm) were tested along with seven other methods publicly available on servers, including several based on the popular elastic network model (ENM). PSA with clustering revealed that paths produced by a given method are more similar to each other than to those from another method and, for instance, that the ENM-based methods produced relatively similar paths. PSA applied to ensembles of DIMS MD and FRODA trajectories of the conformational transition of diphtheria toxin, a particularly challenging example. For the AdK transition, the new concept of a Hausdorff-pair map enabled us to extract the molecular structural determinants responsible for differences in pathways, namely a set of conserved salt bridges whose charge-charge interactions are fully modelled in DIMS MD but not in FRODA. PSA has the potential to enhance our understanding of transition path sampling methods, validate them, and to provide a new approach to analyzing conformational transitions.
