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Journal of Biomedical Optics Sep 2016The recent developments in time-domain diffuse optics that rely on physical concepts (e.g., time-gating and null distance) and advanced photonic components (e.g.,... (Review)
Review
The recent developments in time-domain diffuse optics that rely on physical concepts (e.g., time-gating and null distance) and advanced photonic components (e.g., vertical cavity source-emitting laser as light sources, single photon avalanche diode, and silicon photomultipliers as detectors, fast-gating circuits, and time-to-digital converters for acquisition) are focused. This study shows how these tools could lead on one hand to compact and wearable time-domain devices for point-of-care diagnostics down to the consumer level and on the other hand to powerful systems with exceptional depth penetration and sensitivity.
Topics: Absorption, Physicochemical; Diffusion; Humans; Optical Imaging; Scattering, Radiation; Time Factors
PubMed: 27311627
DOI: 10.1117/1.JBO.21.9.091310 -
Biophysical Journal Nov 2023To characterize the mechanisms governing the diffusion of particles in biological scenarios, it is essential to accurately determine their diffusive properties. To do...
To characterize the mechanisms governing the diffusion of particles in biological scenarios, it is essential to accurately determine their diffusive properties. To do so, we propose a machine-learning method to characterize diffusion processes with time-dependent properties at the experimental time resolution. Our approach operates at the single-trajectory level predicting the properties of interest, such as the diffusion coefficient or the anomalous diffusion exponent, at every time step of the trajectory. In this way, changes in the diffusive properties occurring along the trajectory emerge naturally in the prediction and thus allow the characterization without any prior knowledge or assumption about the system. We first benchmark the method on synthetic trajectories simulated under several conditions. We show that our approach can successfully characterize both abrupt and continuous changes in the diffusion coefficient or the anomalous diffusion exponent. Finally, we leverage the method to analyze experiments of single-molecule diffusion of two membrane proteins in living cells: the pathogen-recognition receptor DC-SIGN and the integrin α5β1. The analysis allows us to characterize physical parameters and diffusive states with unprecedented accuracy, shedding new light on the underlying mechanisms.
Topics: Deep Learning; Diffusion
PubMed: 37853693
DOI: 10.1016/j.bpj.2023.10.015 -
Biophysical Journal Feb 2021Diffusion is a fundamental mechanism for protein distribution in cell membranes. These membranes often exhibit complex shapes, which range from shallow domes to...
Diffusion is a fundamental mechanism for protein distribution in cell membranes. These membranes often exhibit complex shapes, which range from shallow domes to elongated tubular or pearl-like structures. Shape complexity of the membrane influences the diffusive spreading of proteins and molecules. Despite the importance membrane geometry plays in these diffusive processes, it is challenging to establish the dependence between diffusion and membrane morphology. We solve the diffusion equation numerically on various static curved shapes representative for experimentally observed membrane shapes. Our results show that membrane necks become diffusion barriers. We determine the diffusive half-time, i.e., the time that is required to reduce the amount of protein in the budded region by one half, and find a quadratic relation between the diffusive half-time and the averaged mean curvature of the membrane shape, which we rationalize by a scaling law. Our findings thus help estimate the characteristic diffusive timescale based on the simple measure of membrane mean curvature.
Topics: Cell Membrane; Diffusion; Membranes; Proteins
PubMed: 33359464
DOI: 10.1016/j.bpj.2020.12.014 -
The Journal of Chemical Physics Aug 2023Most biological processes in living cells rely on interactions between proteins. Live-cell compatible approaches that can quantify to what extent a given protein... (Review)
Review
Most biological processes in living cells rely on interactions between proteins. Live-cell compatible approaches that can quantify to what extent a given protein participates in homo- and hetero-oligomeric complexes of different size and subunit composition are therefore critical to advance our understanding of how cellular physiology is governed by these molecular interactions. Biomolecular complex formation changes the diffusion coefficient of constituent proteins, and these changes can be measured using fluorescence microscopy-based approaches, such as single-molecule tracking, fluorescence correlation spectroscopy, and fluorescence recovery after photobleaching. In this review, we focus on the use of single-molecule tracking to identify, resolve, and quantify the presence of freely-diffusing proteins and protein complexes in living cells. We compare and contrast different data analysis methods that are currently employed in the field and discuss experimental designs that can aid the interpretation of the obtained results. Comparisons of diffusion rates for different proteins and protein complexes in intracellular aqueous environments reported in the recent literature reveal a clear and systematic deviation from the Stokes-Einstein diffusion theory. While a complete and quantitative theoretical explanation of why such deviations manifest is missing, the available data suggest the possibility of weighing freely-diffusing proteins and protein complexes in living cells by measuring their diffusion coefficients. Mapping individual diffusive states to protein complexes of defined molecular weight, subunit stoichiometry, and structure promises to provide key new insights into how protein-protein interactions regulate protein conformational, translational, and rotational dynamics, and ultimately protein function.
Topics: Single Molecule Imaging; Diffusion; Microscopy, Fluorescence; Photobleaching; Protein Conformation
PubMed: 37589409
DOI: 10.1063/5.0155638 -
European Biophysics Journal : EBJ Apr 2018Lateral movement of a molecule in a biomembrane containing small compartments (0.23-μm diameter) and large ones (0.75 μm) is analyzed using a fractal description of...
Lateral movement of a molecule in a biomembrane containing small compartments (0.23-μm diameter) and large ones (0.75 μm) is analyzed using a fractal description of its walk. The early time dependence of the mean square displacement varies from linear due to the contribution of ballistic motion. In small compartments, walking molecules do not have sufficient time or space to develop an asymptotic relation and the diffusion coefficient deduced from the experimental records is lower than that measured without restrictions. The model makes it possible to deduce the molecule step parameters, namely the step length and time, from data concerning confined and unrestricted diffusion coefficients. This is also possible using experimental results for sub-diffusive transport. The transition from normal to anomalous diffusion does not affect the molecule step parameters. The experimental literature data on molecular trajectories recorded at a high time resolution appear to confirm the modeled value of the mean free path length of DOPE for Brownian and anomalous diffusion. Although the step length and time give the proper values of diffusion coefficient, the DOPE speed calculated as their quotient is several orders of magnitude lower than the thermal speed. This is interpreted as a result of intermolecular interactions, as confirmed by lateral diffusion of other molecules in different membranes. The molecule step parameters are then utilized to analyze the problem of multiple visits in small compartments. The modeling of the diffusion exponent results in a smooth transition to normal diffusion on entering a large compartment, as observed in experiments.
Topics: Cell Membrane; Diffusion; Fractals; Models, Biological; Movement
PubMed: 29094176
DOI: 10.1007/s00249-017-1264-0 -
Proceedings of the National Academy of... Nov 2021Do some types of information spread faster, broader, or further than others? To understand how information diffusions differ, scholars compare structural properties of...
Do some types of information spread faster, broader, or further than others? To understand how information diffusions differ, scholars compare structural properties of the paths taken by content as it spreads through a network, studying so-called cascades. Commonly studied cascade properties include the reach, depth, breadth, and speed of propagation. Drawing conclusions from statistical differences in these properties can be challenging, as many properties are dependent. In this work, we demonstrate the essentiality of controlling for cascade sizes when studying structural differences between collections of cascades. We first revisit two datasets from notable recent studies of online diffusion that reported content-specific differences in cascade topology: an exhaustive corpus of Twitter cascades for verified true- or false-news content by Vosoughi et al. [S. Vosoughi, D. Roy, S. Aral. 359, 1146-1151 (2018)] and a comparison of Twitter cascades of videos, pictures, news, and petitions by Goel et al. [S. Goel, A. Anderson, J. Hofman, D. J. Watts. 62, 180-196 (2016)]. Using methods that control for joint cascade statistics, we find that for false- and true-news cascades, the reported structural differences can almost entirely be explained by false-news cascades being larger. For videos, images, news, and petitions, structural differences persist when controlling for size. Studying classical models of diffusion, we then give conditions under which differences in structural properties under different models do or do not reduce to differences in size. Our findings are consistent with the mechanisms underlying true- and false-news diffusion being quite similar, differing primarily in the basic infectiousness of their spreading process.
Topics: Communication; Diffusion; Humans; Information Dissemination; Social Media
PubMed: 34750252
DOI: 10.1073/pnas.2100786118 -
Analytical Chemistry Apr 2020Measuring the translational diffusion of proteins under physiological conditions can be very informative, especially when multiple diffusing species can be...
Measuring the translational diffusion of proteins under physiological conditions can be very informative, especially when multiple diffusing species can be distinguished. Diffusion NMR or diffusion-ordered spectroscopy (DOSY) is widely used to study molecular diffusion, where protons are used as probes, which can be further edited by the proton-attached heteronuclei to provide additional resolution. For example, the combination of the backbone amide protons (H) to measure diffusion with the well-resolved H/N correlations has afforded high-resolution DOSY experiments. However, significant amide-water proton exchange at physiological temperature and pH can affect the accuracy of diffusion data or cause complete loss of DOSY signals. Although aliphatic protons do not exchange with water protons, and thus are potential probes to measure diffusion rates, H/C correlations are often in spectral overlap or masked by the water signal, which hampers the use of these correlations. In this report, a method was developed that separates the nuclei used for diffusion (α protons, H) and those used for detection (H/N and C'/N correlations). This approach enables high-resolution diffusion measurements of polypeptides in a mixture of biomolecules, thereby providing a powerful tool to investigate coexisting species under physiologically relevant conditions.
Topics: Diffusion; Nuclear Magnetic Resonance, Biomolecular; Proteins
PubMed: 32163276
DOI: 10.1021/acs.analchem.9b05453 -
Journal of Molecular Biology Oct 2018DNA mismatch repair (MMR) corrects DNA base-pairing errors that occur during DNA replication. MMR catalyzes strand-specific DNA degradation and resynthesis by dynamic... (Review)
Review
DNA mismatch repair (MMR) corrects DNA base-pairing errors that occur during DNA replication. MMR catalyzes strand-specific DNA degradation and resynthesis by dynamic molecular coordination of sequential downstream pathways. The temporal and mechanistic order of molecular events is essential to insure interactions in MMR that occur over long distances on the DNA. Biophysical real-time studies of highly conserved components on mismatched DNA have shed light on the mechanics of MMR. Single-molecule imaging has visualized stochastically coordinated MMR interactions that are based on thermal fluctuation-driven motions. In this review, we describe the role of diffusivity and stochasticity in MMR beginning with mismatch recognition through strand-specific excision. We conclude with a perspective of the possible research directions that should solve the remaining questions in MMR.
Topics: Animals; Biophysical Phenomena; DNA; DNA Mismatch Repair; Diffusion; Humans; Multiprotein Complexes; Stochastic Processes; Thermodynamics
PubMed: 29792877
DOI: 10.1016/j.jmb.2018.05.032 -
International Journal of Molecular... Jul 2023Intracellular environment includes proteins, sugars, and nucleic acids interacting in restricted media. In the cytoplasm, the excluded volume effect takes up to 40% of...
Intracellular environment includes proteins, sugars, and nucleic acids interacting in restricted media. In the cytoplasm, the excluded volume effect takes up to 40% of the volume available for occupation by macromolecules. In this work, we tested several approaches modeling crowded solutions for protein diffusion. We experimentally showed how the protein diffusion deviates from conventional Brownian motion in artificial conditions modeling the alteration of medium viscosity and rigid spatial obstacles. The studied tracer proteins were globular bovine serum albumin and intrinsically disordered α-casein. Using the pulsed field gradient NMR, we investigated the translational diffusion of protein probes of different structures in homogeneous (glycerol) and heterogeneous (PEG 300/PEG 6000/PEG 40,000) solutions as a function of crowder concentration. Our results showed fundamentally different effects of homogeneous and heterogeneous crowded environments on protein self-diffusion. In addition, the applied "tracer on lattice" model showed that smaller crowding obstacles (PEG 300 and PEG 6000) create a dense net of restrictions noticeably hindering diffusing protein probes, whereas the large-sized PEG 40,000 creates a "less restricted" environment for the diffusive motion of protein molecules.
Topics: Caseins; Serum Albumin, Bovine; Motion; Diffusion
PubMed: 37446325
DOI: 10.3390/ijms241311148 -
European Biophysics Journal : EBJ Jul 2020A computational methodology to simulate the diffusion of ions from point sources (e.g., ion channels) is described. The outlined approach computes the ion concentration...
A computational methodology to simulate the diffusion of ions from point sources (e.g., ion channels) is described. The outlined approach computes the ion concentration from a cluster of many ion channels at pre-specified locations as a function of time using the theory of propagation integrals. How the channels' open/closed states evolve in time does not need to be known at the start of the simulation, but can be updated on-the-fly as the simulation goes along. The technique uses analytic formulas for the solutions of the diffusion equation for three common geometries: (1) ions diffusing from a membrane (planar symmetry); (2) ions diffusing into a narrow cleft for effective two-dimensional diffusion (cylindrical symmetry); and (3) ions diffusing into open space like the cytosol (spherical symmetry). Because these formulas are exact solutions valid for arbitrarily long timesteps, no spatial or time discretizations are necessary. The only discrete locations are where the ion concentration is computed, and the only discrete timesteps are when the channels' open/closed states are updated. Beyond pure diffusion, the technique is generalized to the Excess Buffer Approximation of ion chelation to give an analytic solution of this approximation of the full reaction/diffusion system. Both the pure diffusion and the diffusion/buffering algorithms scale linearly with the number of channels and the number of ion concentration locations.
Topics: Cell Membrane; Computer Simulation; Diffusion; Ion Channels; Models, Biological
PubMed: 32488299
DOI: 10.1007/s00249-020-01438-9